Development of the control system for electron cyclotron resonance heating on J-TEXT tokamak.

A 105 GHz/500 kW/1 s electron cyclotron resonance heating (ECRH) system has been developed on J-TEXT tokamak since 2017. The core component of the ECRH system is a gyrotron manufactured by Gyrotron Complexes Ltd. (GYCOM Ltd.), which generates microwaves of a certain frequency and power. To guarantee safe and stable operation, it is necessary to design a specialized control system. The control system is expected to perform time sequence trigger, protection, signal monitoring, communication, and data acquisition. The hardware is built with real-time processors and data acquisition modules from National Instruments. The control program is realized by LabVIEW. Test results indicate that the control system can commit stable and safe operation of the gyrotron, which guarantees the integrated commissioning tests of the whole ECRH system and ECRH related physics experiments. Under the operation of this control system, the gyrotron can generate microwaves as expected, and the ECRH system is well protected when a fault takes place.

Linewidth narrowing in self-injection-locked on-chip lasers.

Stable laser emission with narrow linewidth is of critical importance in many applications, including coherent communications, LIDAR, and remote sensing. In this work, the physics underlying spectral narrowing of self-injection-locked on-chip lasers to Hz-level lasing linewidth is investigated using a composite-cavity structure. Heterogeneously integrated III-V/SiN lasers operating with quantum-dot and quantum-well active regions are analyzed with a focus on the effects of carrier quantum confinement. The intrinsic differences are associated with gain saturation and carrier-induced refractive index, which are directly connected with 0- and 2-dimensional carrier densities of states. Results from parametric studies are presented for tradeoffs involved with tailoring the linewidth, output power, and injection current for different device configurations. Though both quantum-well and quantum-dot devices show similar linewidth-narrowing capabilities, the former emits at a higher optical power in the self-injection-locked state, while the latter is more energy-efficient. Lastly, a multi-objective optimization analysis is provided to optimize the operation and design parameters. For the quantum-well laser, minimizing the number of quantum-well layers is found to decrease the threshold current without significantly reducing the output power. For the quantum-dot laser, increasing the quantum-dot layers or density in each layer increases the output power without significantly increasing the threshold current. These findings serve to guide more detailed parametric studies to produce timely results for engineering design.

[Methylophiopogonanone a Inhibits LPS/ATP-Induced Macrophage Pyroptosis via ROS/NLRP3 Pathway].

As a byproduct of mitochondrial respiration or metabolism, reactive oxygen species (ROS) can act as a signaling molecule to activate NLR family pyrin domain containing 3 (NLRP3) inflammasome, thereby triggering immune response. NLRP3 inflammasome acts as a sensor of various danger signals and is central to the control of pyroptosis occurrence. Macrophage pyroptosis is closely related to atherosclerosis, arthritis, pulmonary fibrosis and other inflammatory diseases. Methylophiopogonanone A (MO-A) is a main homoisoflavonoid in Chinese herb Ophiopogonis Radix, which has antioxidant effect. However, it is not clear whether MO-A can alleviate macrophage pyroptosis by inhibiting oxidative stress. Here we have shown that MO-A increases the activities of superoxide dismutase (SOD) and catalase (CAT), inhibits the production of ROS, reduces the activation of NLRP3 inflammasome and the release of lactate dehydrogenase (LDH), and inhibits pyroptosis in macrophages induced by lipopolysaccharides (LPS) and adenosine triphosphate (ATP). These effects can be reversed by the ROS promoter H2O2. Therefore, MO-A can inhibit macrophage pyroptosis through the ROS/NLRP3 pathway and may be considered as a candidate drug for the treatment of inflammatory diseases.

[Quantitative analysis of myelofibrosis and its prognostic significance in patients with myelodysplastic syndrome].

Objective: To quantitatively analyze the reticulin fiber intensity density (RFD) in patients with myelodysplastic syndrome (MDS) by using the computer-aided grid point method, and preliminarily explore its correlation with the prognosis of MDS patients. Methods: Bone marrow (BM) slices from 32 primary MDS patients treated in Tongren Hospital Shanghai Jiao Tong University School of Medicine from February 2017 to December 2019 were observed. Images were taken by the optical microscope imaging system after the Gomori staining. The computer grid marking software was developed according to the principle of the mesh micrometer to assess RFD, meanwhile, the artificial semi-quantitative were used to assess the fibrosis of bone marrow. The co-relation between the above two methods was evaluated, and the relationship between RFD and prognosis of MDS patients were further investigated with Cox regression analysis. Results: Of the patients, there were 17 males and 15 females with a median age of 69 years (32-91 years). The RFD quantitatively analyzed by the computer-based method was positively correlated with the myelofibrosis grade by the artificial semi-quantitative analysis (r=0.497, P=0.004). The RFD in patients diagnosed with MDS complicated with excess blasts (MDS-EB) was significantly higher than that in the non-MDS-EB group((9.55%±0.75%) vs (1.71%±0.23%), P<0.001). Cox regression model analysis showed that the RFD of MDS patients had better prognostic value when compared with the artificial semi-quantitative analysis, which was also a poor prognostic factor (RR=1.337, 95%CI: 1.085-1.648, P=0.006). The overall survival (OS) of patients with RFD>5.54% was significantly shorter than that with RFD≤5.54% (P=0.001). The OS of MDS-EB patients with RFD>9.81% was significantly shorter than that in patients with RFD≤9.81% (P=0.003). Conclusion: Abnormal proliferative fibrosis of bone marrow is a potential high-risk factor for poor prognosis of MDS patients.

Sestamibi Single-Positron Emission Computed Tomography/Diagnostic-quality Computed Tomography for the localization of abnormal parathyroid glands in patients with primary hyperparathyroidism: What clinicopathologic factors affect its accuracy?

PURPOSE: Sestamibi Single-Positron Emission Computed Tomography/Diagnostic-quality Computed Tomography (MIBI-SPECT/CT) is a common technology used for primary hyperparathyroidism (PHPT) localization in clinical practice. However, the clinicopathologic factors affecting the accuracy of MIBI-SPECT/CT and the potential limitations remain unclear. METHODS: Retrospectively enrolled PHPT patients (n = 280) were analyzed from August 2017 to December 2019. RESULTS: Of 96 patients with PHPT (mean age, 54 years; 63 females), 17 had discordance between MIBI-SPECT/CT and intraoperative findings. Among the 17 patients with discordance, 58.8% had major discordance, which occurred in most patients with multigland disease (MGD). Compared with concordant patients, discordant patients exhibited increased frequencies of autoimmune thyroid disease (29.4% vs 10.1%, p = 0.035), MDG (41.2% vs 3.8%, p = 0.035), higher PTH (296 pg/mL vs 146 pg/mL; p = 0.012),and lower phosphorus levels (0.77 mmol/L vs 0.90 mmol/L; p = 0.024). MDG (odds ratio [OR], 16.95; 95% CI 2.10-142.86), parathyroid lesion size of 12 mm or less (OR, 6.93; 95% CI 1.41-34.10), and a PTH level higher than 192.5 pg/mL (OR, 12.66; 95% CI 2.17-71.43) were independently associated with discordant MIBI-SPECT/CT results. CONCLUSION: MGD was most strongly associated with discordance between MIBI-SPECT/CT and intraoperative findings followed by a PTH level higher than 192.5 pg/mL and parathyroid lesion size of 12 mm or less. Surgeons should recognize these potential limitations, which may improve the preoperative procedure by encouraging further localization imaging and promptly facilitate intraoperative troubleshooting.

A Bayesian Network Model for Seismic Risk Analysis.

Earthquakes are one of the most unpredictable natural disasters. A series of secondary and derived disaster events may occur afterwards and lead to even more consequences. In such situations, a seismic risk analysis that takes into account secondary and derived disaster events is vital in reducing the risks of such disasters. The absence of a holistic seismic risk analysis model-one that takes into account the derived disaster events-may mean that the serious consequences of the disaster chains set off by earthquakes are neglected. This article proposes a comprehensive seismic risk analysis that enables a better understanding of seismic disaster chains and rescue scenarios. The approach is based on a Bayesian network constructed using scenario-based methods. The final network structure is achieved by learning parameters. To determine the critical secondary disasters and the key emergency-response measures, probability adaptation and updating using the Bayesian model were performed. The practical application of the model is illustrated using the Wenchuan earthquake and the Jiuzhaigou earthquake in China. The two examples show that the model can be used to predict the potential effects of secondary disasters and the final seismic losses. The results of the model can help decisionmakers gain a comprehensive understanding of seismic risk and implement practical emergency-rescue measures to reduce risk and losses.

Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales.

Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake's watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.

[Prediction of short-term prognosis of hepatocellular carcinoma after TACE surgery based on MRI texture analysis technology].

Objective: To explore the feasibility of short-term efficacy prognosis prediction model for HCC patients undergoing transcatheter arterial chemoembolization (TACE) based on MRI-based radiomics technique. Methods: A total of 123 patients with liver cancer who received TACE treatment in Lishui Central Hospital from June 2016 to July 2018 were retrospectively collected, including 90 males and 33 females, with an average age of 24-83 (58±10) years. All the patients were pathologically confirmed as hepatocellular carcinoma and underwent MRI scan before surgery.All patients were followed up 3-4 months after TACE, and further divided into training group (n=85, 42 of which were effective and 43 cases were ineffective) and the validation group (n=38, 19 of which were effective and 19 were ineffective) according to the modified response evaluation criteria in solid tumors (mRECIST). There was no statistical difference in the general information between the two groups of patients, which was comparable. Then, preoperative T(2)WI images were used for radiomics analysis, texture parameters were screened based on R language, and short-term efficacy prediction model of TACE for training group and verification group was constructed. Results: T(2)WI image analysis of each patient received 396 different texture parameters, and further used Lasso dimensionality reduction and 10 times cross-validation screening to obtain 5 characteristic texture parameters, specifically stdDeviation, ClusterProminence_angle135_offset4, Correlation_angle135_offset4, Inertia_angle135_offset4, InverseDifferenceMoment_angle45_offset4. According to the above five texture parameters and their corresponding coefficient values, the corresponding radiomics scores (Radscore) were calculated, and the prediction models of the training group and the verification group were further constructed.It was found that the area under the ROC curve of the training group was 0.812 (95%CI: 0.722-0.901), the sensitivity and specificity were 83.7% and 69.0%, respectively. The area under the ROC curve of the validation group was 0.801 (95%CI:0.654-0.947), and the sensitivity and specificity were 89.5% and 63.2%, respectively. Conclusion: The constructed TACE prediction model in the present study has high prediction accuracy, sensitivity and specificity.The short-term efficacy prognosis prediction model for HCC based on MRI is constructed, stable and reliable.

Multimode description of self-mode locking in a single-section quantum-dot laser.

This paper describes a theory for mode locking and frequency comb generation by four-wave mixing in a semiconductor quantum-dot active medium. The derivation uses a multimode semiclassical laser theory that accounts for fast carrier collisions within an inhomogeneous distribution of quantum dots. Numerical simulations are presented to illustrate the role of active medium nonlinearities in mode competition, gain saturation, carrier-induced refractive index and creation of combination tones that lead to locking of beat frequencies among lasing modes in the presence of cavity material dispersion.

Longitudinal analysis of atherosclerotic cardiovascular disease risk and healthcare costs in newly diagnosed type 2 diabetes in a real-world setting.

AIMS: To assess longitudinal risk for atherosclerotic cardiovascular disease (ASCVD) and cost of healthcare resource utilization over 9 years in patients with or without newly diagnosed type 2 diabetes (T2DM) who had no ASCVD at baseline. METHODS: This retrospective, longitudinal analysis of a large, nationwide US administrative claims database compared adults with newly diagnosed T2DM (n = 22,468) and a propensity score matched non-T2DM cohort (n = 22,468). Longitudinal risk of ASCVD and total annual healthcare costs were determined. Subgroup analysis was conducted for 3 age categories: 18-44, 45-64, and 65+ years. RESULTS: From 2006 to 2015, ASCVD was identified in a significantly greater percentage of patients in the T2DM versus non-T2DM cohort (43.2% vs 32.3%; Hazard ratio [HR] = 1.45, P < 0.001). Total annual healthcare cost was markedly higher in T2DM versus non-T2DM cohorts (48.4% higher at year 9). The differences between cohorts were most pronounced in patients aged 18-44 years. CONCLUSIONS: This 9-year claims-based retrospective, longitudinal analysis showed a higher risk of ASCVD and higher healthcare costs in newly diagnosed T2DM patients versus those without T2DM, with highest relative risk and cost differences observed in younger patients.

[Clinicopathological features and outcome of gastroenteropancreatic high-grade (WHO G3) neuroendocrine tumors: a study of 60 cases].

Objective: To investigate the clinicopathological features and outcome of gastroenteropancreatic high-grade neuroendocrine tumors. Methods: A total of 60 gastroenteropancreatic high-grade neuroendocrine tumors were collected from January 1st, 2013 to December 31th, 2018 at Fudan University Shanghai Cancer Center, with available pathology databases and clinic follow-up information. At the same time, 157 cases of gastrointestinal pancreatic neuroendocrine neoplasm (NEN) diagnosed at the hospital in 2018 were collected and the incidence of NEN at all grades was compared. Results: There were 32 males and 28 females, aged 13-80 years (mean 54 years). Pancreas primary was the most common (48%, 29/60). Nodal metastatic rate was 9/16 and distant metastatic rate was 41%(18/44). Liver was the most common site of metastasis. Among all the gastroenteropancreatic neuroendocrine neoplasms diagnosed in the hospital in 2018, the incidence of high-grade neuroendocrine tumors was the lowest (7%, 11/157). High-grade neuroendocrine tumors had typical pathologic features of well-differentiated/moderate neuroendocrine tumors, but with significant differences in mitotic rates. By immunohistochemical staining, most of the tumors expressed neuroendocrine markers and somatostatin receptor 2 was positive in 60% (12/20) of the cases. The average Ki-67 index was 30%-40%, and there was significant difference between cases (18%-80%). The overall survival of high-grade neuroendocrine tumors was 43 months, and the disease-free survival was 12 months. Conclusions: High-grade neuroendocrine tumor is a rare group of neuroendocrine tumors, with unique clinicopathological features and good prognosis. Pathological classification and grading of gastroenteropancreatic neuroendocrine neoplasms can help clinicians to select appropriate treatment and accurately evaluate prognosis.

Intensification patterns and the probability of HbA1c goal attainment in Type 2 diabetes mellitus: real-world evidence for the concept of 'intensification inertia'.

AIMS: To assess the effects of 'clinical' and 'intensification inertia' by evaluating the impact of different intensification interventions on the probability of HbA1c goal attainment using real-world data. METHODS: Electronic health records (Cleveland Clinic, 2005-2016) were used to identify 7389 people with Type 2 diabetes mellitus and HbA1c ≥53 mmol/mol (≥7.0%), despite a stable regimen of two oral antihyperglycaemic drugs for ≥6 months. The participants were stratified by index HbA1c and analysed over a 6-month period for pharmacological intensification, and then for 12 additional months for HbA1c goal attainment (<53 mmol/mol). RESULTS: The probability of HbA1c goal attainment (Kaplan-Meier analysis) in the group with index HbA1c 53-63 mmol/mol (7.0-7.9%) was highest with the addition of oral antidiabetic drugs [57.3% (95% CI 52.1, 62.0)] or glucagon-like peptide-1 receptor agonists [56.7% (95% CI 40.4, 68.6)], in the 64-74 mmol/mol (8.0-8.9%) group with the addition of oral antidiabetic drugs [31.9% (95% CI 25.1, 38.1)] or insulin [30.6% (95% CI 18.3, 41.0)], and in the ≥75 mmol/mol (≥9.0%) group with the addition of glucagon-like peptide-1 receptor agonists [53.0% (95% CI 31.8, 67.6)] or insulin [43.5% (95% CI 36.4, 49.8)]. CONCLUSIONS: Numerical, but not statistically significant, differences in HbA1c goal attainment probability by type of intensification were most marked in people with the highest index HbA1c [≥75 mmol/mol (≥9.0%)]; in this group, injectable therapy showed trends toward greater glycaemic control benefits. Additional research into the phenomenon of intensification inertia is warranted.

Autologous oxygen release nano bionic scaffold composite miR-106a induced BMSCs enhances osteoblast conversion and promotes bone repair through regulating BMP-2.

OBJECTIVE: Suitable seed cells and selection of bioactive scaffold materials are the main research contents of bone tissue engineering. It was showed that autologous oxygen release nano bionic scaffold could promote the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). The role of microRNA-106a (miR-106a) in regulating BMSCs differentiation has not been reported. We intend to investigate the role of autologous oxygen release nano bionic scaffold composite miR-106a in inducing BMSCs constructing tissue engineering bone. MATERIALS AND METHODS: Rat BMSCs were isolated and transfected by using miR-106a scramble or miR-106a inhibitor. Healthy male Sprague-Dawly (SD) rats were randomly divided into three groups, including bone fracture group established as rat tibial fracture model, negative control group implanted by autologous oxygen release nano bionic scaffold composite miR-106a scramble BMSCs, and miR-106a inhibitor group implanted by autologous oxygen release nano bionic scaffold composite miR-106a inhibitor BMSCs. Callus growth was observed. Alkaline phosphatase (ALP) activity was detected. Bone morphogenetic protein 2 (BMP-2) expression was tested by Real-time PCR (RT-PCR) and Western blot assay. Collagen II production was determined by RT-PCR. RESULTS: Autologous oxygen release nano bionic scaffold composite BMSCs significantly increased local bone mineral density, promoted callus healing, facilitated ALP secretion, elevated collagen II expression, and up-regulated BMP-2 mRNA and protein levels compared with fracture group (p<0.05). Autologous oxygen release nano bionic scaffold composite miR-106a induced BMSCs exhibited more significant effect on bone repair (p<0.05). CONCLUSIONS: Autologous oxygen release nano bionic scaffold composite miR-106a induced BMSCs enhanced osteoblast conversion and promoted bone repair through regulating BMP-2.

Glucagon-like peptide-1 receptor agonists and fracture risk: a network meta-analysis of randomized clinical trials.

Our network meta-analysis analyzed the effects of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) on fracture risk. By combining data from randomized controlled trials, we found that GLP-1 RAs were associated with a decreased bone fracture risk, and exenatide is the best option agent with regard to the risk of fracture. This study is registered with PROSPERO (CRD42018094433). INTRODUCTION: Data on the effects of GLP-1 RAs on fracture risk are conflicted. This study aimed to analyze the available evidence on the effects of GLP-1 RAs on fracture risk in type 2 diabetes mellitus patients. METHODS: Electronic databases were searched for relevant published articles, and unpublished studies presented at ClinicalTrials.gov were searched for relevant clinical data. All analyses were performed with STATA 12.0 and R software (Version 3.4.4). We estimated the risk ratio (RR) and 95% confidence interval (CI) by combining RRs for fracture effects of included trials. RESULTS: There were 54 eligible random control trials (RCTs) with 49,602 participants, including 28,353 patients treated with GLP-1 RAs. Relative to placebo, exenatide (RR, 0.17; 95% CI 0.03-0.67) was associated with lowest risk of fracture among other GLP-1 RAs. Exenatide had the highest probability to be the safest option with regard to the risk of fracture (0.07 ‰), followed by dulaglutide (1.04%), liraglutide (1.39%), albiglutide (5.61%), lixisenatide (8.07%), and semaglutide (18.72%). A statistically significant inconsistency was observed in some comparisons. CONCLUSION: The Bayesian network meta-analysis suggests that GLP-1 RAs were associated with a decreased bone fracture risk compared to users of placebo or other anti-hyperglycemic drugs in type 2 diabetes mellitus patients, and exenatide is the best option agent with regard to the risk of fracture.

Projecting the Burden of Chronic Kidney Disease in a Developed Country and Its Implications on Public Health.

BACKGROUND: Chronic Kidney Disease (CKD) is a major public health problem worldwide. There is limited literature on a model to project the number of people with CKD. This study projects the number of residents with CKD in Singapore by 2035 using a Markov model. METHODS: A Markov model with nine mutually exclusive health states was developed according to the clinical course of CKD, based on a discrete time interval of 1 year. The model simulated the transition of cohorts across different health states from 2007 to 2035 using prevalence, incidence, mortality, disease transition, and disease detection rates. RESULTS: From 2007 to 2035, the number of residents with CKD is projected to increase from 316,521 to 887,870 and the prevalence from 12.2% to 24.3%. Patients with CKD stages 1-2 constituted the largest proportion. The proportion of undiagnosed cases will decline from 72.1% to 56.4%, resulting from faster progression to higher CKD stages and its eventual detection. CONCLUSION: By 2035, about one-quarter of the Singapore residents are expected to have CKD. National policies need to focus on primary disease prevention and early disease detection to avoid delayed treatment of CKD which eventually leads to end-stage renal disease.

Trends in comorbidity burden and treatment patterns in type 2 diabetes: Longitudinal data from a US cohort from 2006 to 2014.

AIMS: To gather real-world data on treatment characteristics and comorbidity progression in patients with newly-diagnosed type 2 diabetes (T2D) and evaluate differences by patient age. METHODS: Retrospective analysis of a US administrative claims database including 16,950 subjects with newly-diagnosed T2D in 2006 and a baseline Diabetes Complications Severity Index (DCSI) score of 0. Patients were categorized by DCSI score at year 8 (0, 1-2, or ≥3) and comparatively analyzed based on demographic variables, drug usage, and diabetes-related comorbidities. RESULTS: Year 8 DCSI score distribution was 0 (29.9%), 1-2 (36.2%), and ≥3 (33.9%). The highest DCSI score subgroup (≥3) was characterized by a significantly greater percentage of males, older age at T2D diagnosis, and higher Medicare enrollment. DCSI progressed most rapidly in the oldest age group (≥65). Among all subjects at year 8, insulin use was significantly highest among subjects with DCSI ≥3 compared with those having a lower DCSI. However, for subjects with DCSI ≥3, insulin use was lower among those in the oldest age group (≥65) relative to younger age groups. CONCLUSIONS: These real-world data suggest a relationship between age at T2D diagnosis and disease progression based on comorbidity burden and lower usage of injectable therapies in older patients.