A novel risk prediction nomogram for early death in patients with resected synchronous multiple primary colorectal cancer based on the SEER database.

BACKGROUND: Synchronous multiple primary colorectal cancer (SMPCC) involves the simultaneous occurrence of 2 or more independent primary malignant tumors in the colon or rectum. Although SMPCC is rare, it results in a higher incidence of postoperative complications and mortality compared to patients with single primary colorectal cancer (SPCRC). METHODS: The clinical factors and survival outcomes of SMPCC patients registered on the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2017 were extracted. The patients were divided into the training and validation cohorts using a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for early death. The performance of the nomogram was evaluated using the concordance index (C-index), calibration curves, and the area under the curve (AUC) of a receiver operating characteristics curve (ROC). A decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram and standard TNM system. RESULTS: A total of 4386 SMPCC patients were enrolled in the study and randomly assigned to the training (n = 3070) and validation (n = 1316) cohorts. The multivariate logistic analysis identified age, chemotherapy, radiotherapy, T stage, N stage, and M stage as independent risk factors for all-cause and cancer-specific early death. The marital status was associated with all-cause early death, and the tumor grade was associated with cancer-specific early death. In the training cohort, the nomogram achieved a C-index of 0.808 (95% CI, 0.784-0.832) and 0.843 (95% CI, 0.816-0.870) for all-cause and cancer-specific early death, respectively. Following validation, the C-index was 0.797 (95% CI, 0.758-0.837) for all-cause early death and 0.832 (95% CI, 0.789-0.875) for cancer-specific early death. The ROC and calibration curves indicated that the model had good stability and reliability. The DCA showed that the nomogram had a better clinical net value than the TNM staging system. CONCLUSION: Our nomogram can provide a simple and accurate tool for clinicians to predict the risk of early death in SMPCC patients undergoing surgery and could be used to optimize the treatment according to the patient's needs.

Ponder: Enabling Balloon-Borne Based Solar Unmanned Aerial Vehicle's Take Off Diagnosis under Little Data.

Balloon-borne based solar unmanned aerial vehicle (short for BS-UAV) has been researched prevalently due to the promising application area of near-space (i.e., 20-100 km above the ground) and the advantages of taking off. However, BS-UAV encounters serious fault in its taking off phase. The fault in taking off hinders the development of BS-UAV and causes great loss to human property. Thus, timely diagnosing the running state of BS-UAV in taking off phase is of great importance. Unfortunately, due to lack of fault data in the taking off phase, timely diagnosing the running state becomes a key challenge. In this paper, we propose Ponder to diagnose the running state of BS-UAV in the taking off phase. The key idea of Ponder is to take full advantage of existing data and complement fault data first and then diagnose current states. First, we compress existing data into a low-dimensional space. Then, we cluster the low-dimensional data into normal and outlier clusters. Third, we generate fault data with different aggression at different clusters. Finally, we diagnose fault state for each sampling at the taking off phase. With three datasets collected on real-world flying at different times, we show that Ponder outperforms existing diagnosing methods. In addition, we demonstrate Ponder's effectiveness over time. We also show the comparable overhead.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Developing prognostic nomograms to predict overall survival and cancer-specific survival in synchronous multiple primary colorectal cancer based on the SEER database.

BACKGROUND: Synchronous multiple primary colorectal cancer (SMPCC) is a rare subtype of CRC, characterized by the presence of two or more primary CRC lesions simultaneously or within 6 months from the detection of the first lesion. We aim to develop a novel nomogram to predict OS and CSS for SMPCC patients using data from the SEER database. METHODS: The clinical variables and survival data of SMPCC patients between 2004 and 2018 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Appropriate inclusion and exclusion criteria were established to screen the enrolled patients. Univariate and multivariate Cox regression analyses were used to identify the independent risk factors for OS and CSS. The performance of the nomogram was evaluated using the concordance index (C-index), calibration curves, and the area under the curve (AUC) of a receiver operating characteristics curve (ROC). A decision curve analysis (DCA) was generated to compare the net benefits of the nomogram with those of the TNM staging system. RESULTS: A total of 6772 SMPCC patients were enrolled in the study and randomly assigned to the training (n = 4670) and validation (n = 2002) cohorts. Multivariate Cox analysis confirmed that race, marital status, age, histology, tumor position, T stage, N stage, M stage, chemotherapy, and the number of dissected LNs were independent prognostic factors.The C-index values for OS and CSS prediction were 0.716 (95% CI 0.705-0.727) and 0.718 (95% CI 0.702-0.734) in the training cohort, and 0.760 (95% CI 0.747-0.773) and 0.749 (95% CI 0.728-0.769) in the validation cohort. The ROC and calibration curves indicated that the model had good stability and reliability. Decision curve analysis revealed that the nomograms provided a more significant clinical net benefit than the TNM staging system. CONCLUSION: We developed a novel nomogram for clinicians to predict OS and CSS, which could be used to optimize the treatment in SMPCC patients.

Synthesis, pharmacokinetics, and pharmacodynamics studies of valsartan peptide derivatives.

In order to increase the intestinal permeability of valsartan, 14 esters and peptide derivatives of valsartan were chemically synthesized and their absorption characteristics were described. All derivatives were stable and could be better absorbed into the small intestine than valsartan. There are two barriers for the absorption of valsartan derivatives. The elongated half-life (t(1/2)) and stable blood concentrations for compound 4 due to the hydrolysis of the ester group in the second barrier were demonstrated in pharmacokinetic experiments. Furthermore, compound 4 also displayed modest anti-hypertension activity in vivo, which makes structural modification of valsartan, especially for the purpose of improvement of its intestinal permeability, valuable for further studies.

Effect of Interlaminar Toughness on the Residual Compressive Capacity of Carbon Fiber Laminates with Different Types of Delamination.

In this paper, the effect of interlaminar properties and the type of delamination defects on the residual compression properties of carbon fiber laminates were experimentally investigated. A new method, which employed magnetic force to guide the arrangement direction of stainless steel particles between layers of laminates, was adopted to improve the interlayer toughness. The digital image correlation, C-scan, and micro-CT were used to measure and identify the compression failure damages. Test results showed that the compressive strength of the intact carbon fiber laminates was 299.37 MPa, and the one of specimens containing the deeply buried delamination, the through-width delamination, and the surface delamination decreased by 55.98 MPa, 58.69 MPa, and 60.23 MPa, respectively. The compressive strength of the specimens containing the deeply buried delamination only decreased by 14.01 MPa when the mode I toughness increased by 81.88%, and the specimen containing the surface delamination only decreased by 30.86 MPa when the mode II fracture toughness increased by 87.72%. However, improving the fracture toughness could not strengthen the specimens containing the through-width delamination. Moreover, a qualitative dynamic damage relationship, which described the relationship between delamination expansion and compression damage vividly, was proposed. The reason the increase of the toughness could improve the residual compression performance of the laminates containing delamination was that the higher fracture toughness hindered the secondary expansion of the delamination during the compression process so that the delamination area could almost remain unchanged.

Computational optimal launching control for balloon-borne solar-powered unmanned aerial vehicles in near-space.

The near-space solar-powered unmanned aerial vehicle has broad prospects in application owing to its high altitude long-endurance performance. Launching solar-powered unmanned aerial vehicle into the near-space with balloon-borne approach has advantages over the traditional sliding take-off methods, in that it is able to quickly and safely cross the turbulent zone. In this article, we investigate the control technology of balloon-borne launching for the solar-powered unmanned aerial vehicles. First, the motion of the launching process is divided into longitudinal and lateral-directional motion, with the longitudinal process and its equation addressed in detail. We then analyze the flight state and restriction conditions that the unmanned aerial vehicle should meet during the process. Second, the target variables and constraints are selected to formulate the optimization problem. The control variable parameterization method is applied to find the optimal pitch angle in the releasing-and-pulling process. More explicitly, a three-channel attitude stabilization controller is designed, in which the longitudinal channel takes the optimal pitch angle as the pitch instruction, the transverse channel carries out the zero control of the inclination angle, and the course channel takes the stabilization control, respectively. Numerical simulation results show that our proposed control design is capable of accelerating the solar-powered unmanned aerial vehicles from the vertical state and pulling them up to the horizontal cruising flight state, with the flight angle of attack, the maximum speed, and the maximum axial acceleration in the pulling process all within the designed range.

The Study of Reactive Ion Etching of Heavily Doped Polysilicon Based on HBr/O2/He Plasmas for Thermopile Devices.

Heavily doped polysilicon layers have been widely used in the fabrication of microelectromechanical systems (MEMS). However, the investigation of high selectivity, anisotropy, and excellent uniformity of heavily doped polysilicon etching is limited. In this work, reactive ion etching of undoped and heavily doped polysilicon-based hydrogen bromide (HBr) plasmas have been compared. The mechanism of etching of heavily doped polysilicon is studied in detail. The final results demonstrate that the anisotropy profile of heavily doped polysilicon can be obtained based on a HBr plasma process. An excellent uniformity of resistance of the thermocouples reached ± 2.11%. This technology provides an effective away for thermopile and other MEMS devices fabrication.