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Background Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in clinical practice and has a well-established association with coronary artery bypass graft (CABG) surgery. Being able to predict post-operative atrial fibrillation (POAF) may improve surgical outcomes. This study aims to understand the efficacy of incorporating intraoperative medication data to predict first-time POAF in patients undergoing CABG surgery. Methods This study aims to understand the efficacy of incorporating intraoperative medication data to predict first-time POAF in patients undergoing CABG surgery. A large cohort of 3807 first-time CABG patients with no known history of atrial fibrillation was retrospectively assembled to study factors that contribute to occurrence of post-operative atrial fibrillation, in addition to testing models that may predict its incidence. To do so, several clinical features with established relevance to POAF were extracted from the electronic health record, along with a record of medications administered intra-operatively. Tests of performance with logistic regression, decision tree, and neural network predictive models showed slight improvements when incorporating medication information. Results Analysis of the collected set of clinical and medications data indicate that there may be effects contributing to POAF incidence captured in the medication administration records. However, a definitive causal relationship between the medications and POAF incidence is not established. Conclusions Our results show that improved predictive performance is achievable by incorporating a record of medications administered intra-operatively, but further investigation is needed to understand the implications of this for clinical practice.

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP1-RAs) reduce cardiovascular events and mortality in patients with type 2 diabetes mellitus (T2DM). We sought to describe trends in prescribing for SGLT2is and GLP1-RAs in diverse care settings, including (1) the outpatient clinics of a midwestern integrated health system and (2) small- and medium-sized community-based primary care practices and health centers in 3 midwestern states. We included adults with T2DM and ≥1 outpatient clinic visit. The outcomes of interest were annual active prescription rates for SGLT2is and GLP1-RAs (separately). In the integrated health system, 22,672 patients met the case definition of T2DM. From 2013 to 2019, the overall prescription rate for SGLT2is increased from 1% to 15% (absolute difference [AD] 14%, 95% confidence interval [CI] 13% to 15%, p0.01). The GLP1-RA prescription rate was stable at 10% (AD 0%, 95% CI -1% to 1%, p = 0.9). In community-based primary care practices, 43,340 patients met the case definition of T2DM. From 2013 to 2017, the SGLT2i prescription rate increased from 3% to 7% (AD 4%, 95% CI 3% to 6%, p0.01), whereas the GLP1-RA prescription rate was stable at 2% to 3% (AD 1%, 95% CI -1 to 1%, p = 0.40). In a fully adjusted regression model, non-Hispanic Black patients had lower odds of SGLT2i or GLP1-RA prescription (odds ratio 0.56, 95% CI 0.34 to 0.89, p = 0.016). In conclusion, the increase in prescription rates was greater for SGLT2is than for GLP1-RAs in patients with T2DM in a large integrated medical center and community primary care practices. Overall, prescription rates for eligible patients were low, and racial disparities were observed.

Background The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both. However, the performance of these survival neural network models compared to each other and to PCEs in ASCVD prediction is unknown. Methods In this study, we used 6 cohorts from the Lifetime Risk Pooling Project (with 5 cohorts as training/internal validation and one cohort as external validation) and compared the performance of the PCEs in 10-year ASCVD risk prediction with an all two-way interactions Cox PH model (Cox PH-TWI) and three state-of-the-art neural network survival models including Nnet-survival, Deepsurv, and Cox-nnet. For all the models, we used the same 7 covariates as used in the PCEs. We fitted each of the aforementioned models in white females, white males, black females, and black males, respectively. We evaluated models’ internal and external discrimination power and calibration. Results The training/internal validation sample comprised 23216 individuals. The average age at baseline was 57.8 years old (SD = 9.6); 16% developed ASCVD during average follow-up of 10.50 (SD = 3.02) years. Based on 10 × 10 cross-validation, the method that had the highest C-statistics was Deepsurv (0.7371) for white males, Deepsurv and Cox PH-TWI (0.7972) for white females, PCE (0.6981) for black males, and Deepsurv (0.7886) for black females. In the external validation dataset, Deepsurv (0.7032), Cox-nnet (0.7282), PCE (0.6811), and Deepsurv (0.7316) had the highest C-statistics for white male, white female, black male, and black female population, respectively. Calibration plots showed that in 10 × 10 validation, all models had good calibration in all race and sex groups. In external validation, all models overestimated the risk for 10-year ASCVD. Conclusions We demonstrated the use of the state-of-the-art neural network survival models in ASCVD risk prediction. Neural network survival models had similar if not superior discrimination and calibration compared to PCEs.

Avoidable emergency department (ED) visits contribute increased costs to the healthcare system and lead to overcrowding that can limit capacity to treat patients. There has been little work to develop models from patient characteristics that can predict avoidable ED visits. Here we apply machine learning methods using the NHAMCS dataset to predict avoidable ED visits and identify patient characteristics associated with avoidable ED.

Introduction: Multiple randomized clinical trials have shown that sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP1) receptor agonists reduce the risk of cardiovascular events and mortality in patients with type 2 diabetes (T2D) and cardiovascular disease (CVD). In order to inform implementation strategies, we sought to describe prescribing trends among patients with T2D in clinical practice. Methods: We developed a clinical T2D cohort using a validated computable phenotype from the electronic data warehouse of a large academic health system among patients receiving care from January 1, 2013 through December 31, 2019. We retrospectively reviewed outpatient prescribing patterns in this cohort, and stratified results by CVD subtype (heart failure [HF] and atherosclerotic CVD [ASCVD]). Results: There were 23,485 patients identified with T2D. Mean (SD) age was 67 years (13), 46% were women, 61% were white, 32% had comorbid CVD (HF or ASCVD), and the mean (SD) hemoglobin A1c was 8.0% (5.7%). The majority of SGLT2 inhibitors and GLP1 receptor agonists were first prescribed by endocrinologists, 52% and 65% respectively. The prescription rate for both medication classes was low, and though SGLT2 inhibitor use increased over time (1% in 2013 to 14% in 2019; p Conclusions: Prescription rates of SGLT2 inhibitors and GLP1 receptor agonists remains low, especially for patients with T2D and CVD, despite a proven reduction in mortality and cardiovascular events. Strategies to increase the use of these proven medical therapies represent a major opportunity to improve outcomes in this high-risk group.

As part of a national study in the United States to recruit one million Americans (All of Us Research Program) and their Electronic Health Record data, we set out to determine the degree to which care is fragmented across a sample of participating health provider organizations (HPOs). We distributed a previously validated Privacy-Preserving Record Linkage (PPRL) tool to participating sites to generate a unique set of keyed encrypted hashes for seven participating institutions across three States in the Upper Midwest of the U.S. An honest broker received the resulting encrypted hashes to identify patients with the same encrypted hashes shared across any combination of more than one institution as a proxy for patients receiving care across institutions. Out of 5,831,238 individuals, we identified 458,680 patients with data at more than one institution. Care fragmentation varied significantly by State and by Institution ranging from 6.1% up to 32.7%. Patients with fragmented care were more likely to be black (11.8% vs 10.8%), and slightly older (Median birth year 1968 vs 1969) compared with patients receiving care at only one participating institution. In contrast, patients who maintained an address in a warmer state (“snowbirds”) were the least likely to be black (7.5%) of all study groups. We identified conflicting or inconsistent demographic information in 49.1% of patients with care fragmentation compared with 5.6% of patients without care fragmentation. Privacy-preserving record linkage can be an effective means to identify populations with care fragmentation and poor data quality for focused clinical and data improvement efforts.

Cobalt chloride (CoCl2) has long been accepted as a suitable in vitro hypoxia-mimetic agent. The gene CXCR4, which encodes a chemokine receptor, plays a key role in hypoxic retinal disease. Here, we investigated the mRNA and protein expression of CXCR4 in WERI-Rb1 retinoblastoma cells and human umbilical vein endothelial cells (HUVECs) under CoCl2-induced hypoxic conditions, by means of real-time PCR and western blot. We found that CoCl2-induced hypoxia profoundly increased CXCR4 expression at the mRNA level, but not at the protein level, at 12, 24, 48 and 72 h in these cells. Interestingly, this result differed from observations of 1% O2 hypoxic conditions. Additionally, luciferase assays demonstrated that CoCl2-induced hypoxia significantly increased transcription at the CXCR4 promoter. In order to compare our in vitro findings with the effects of hypoxia in vivo, an OIR (Oxygen-induced retinopathy) rat model was constructed. However, both CXCR4 mRNA and protein levels in OIR rats were significantly increased compared to controls. Thus taken together, our findings suggest that the relationship between CXCR4 mRNA and protein expression is not strictly linear under in vitro CoCl2-induced hypoxic conditions. through comparative in vitro and in vivo experiments, this study implies that CoCl2 is an imperfect simulation of hypoxia in retinal disease.

Aiming at the problems of complex structure, heavy weight and difficult manufacturing of manipulator, a design scheme of rope-driven three-fingered manipulator is proposed based on bionics principle to meet different functional requirements. The actual motion of the manipulator is controlled by the cable drive and the bending of the distal knuckle is realized by coupling connection. The three-dimensional solid model of the manipulator is established by using the design software, and the motion simulation analysis of the solid model is carried out to obtain its motion law. The results of motion analysis show that the speed of the manipulator changes smoothly in the motion process, and the change of speed has little effect on the stability of the objects grasped by the manipulator. Finally, a prototype of the manipulator is made according to the design results. The prototype model can be used not only in practical teaching, but also in theoretical research. It can provide some reference for the practical application of multi-fingered and multi-joint manipulators.

The identification and compensation of angle kappa is crucial for the centration of the operative zone in corneal refractive surgeries, such as the prevalent Small Incision Lenticule Extraction (SMILE) surgery. However, SMILE still relies on the surgeons’ subjective estimation rather than the precise measurement to compensate for the angle kappa. This may expose potential issues in prior studies of the centration technique in SMILE as well as affect actual surgical outcomes. Therefore, we have developed a method to identify angle kappa based on the surgical machine VisuMax with image recognition with computer vision techniques.

This study aimed to construct and evaluate a novel prediction model for postoperative atrial fibrillation (PoAF) with the addition of intraoperative medications. The study patient population included 4731 patients who underwent CABG surgery, of which 1363 developed PoAF, and the prediction methods included three logistic regression models. Multivariate logistic regression was performed with traditional clinical variables only for the first model, intraoperative medications added in the second model, and a subset of all variables chosen by the Least Absolute Shrinkage and Selection Operator (LASSO) in the third model. Age and prior AF diagnosis were consistently the strongest predictors for PoAF across all three models. The specific intra-operative medications moderately improved predictive accuracy as compared to the clinical feature-only model.

Visually guided regulation is a sophisticated and active process, whereby sensory input helps to shape ocular development. Here, we sought to investigate the potential involvement of SorCS1, an important protein in synaptic transmission in neuron, in retinal development. A form-deprivation (FD) rat model was established. Ocular variations induced by FD were examined, including changes to eye axial length and retinal thickness. Scotopic electroretinogram (ERG) was used to examine retinal function. RD-PCR assays were screened for differentially expressed genes in FD rat eyes. Immunofluorescence staining identified the expression pattern and localization of SorCS1 in rat retina, with or without FD treatment. Additionally, primary retinal neural cells were cultured and incubated with or without a light–dark cycle, and western blot and real-time PCR assays were used to examine the expression of SorCS1. Retinal neural cells were treated with recombinant SorCS1 (h-SorCS1) coated with beads in serum-free conditions to test for effects on cellular physiology and expression of neurotransmitters involved in visual development. To monitor cell viability, a CCK8 assay was employed. Our data demonstrated that FD led to ocular axial elongation and retinal thinning. ERG tests showed FD impaired electrophysiological function in rat. An age-related expression pattern of SorCS1 was observed in the rat retina, and SorCS1 was significantly up-regulated in the FD rat retina. In addition, in vitro evidence suggested a strong correlation between light exposure and SorCS1 expression. Furthermore, treatment of retinal neural cells with h-SorCS1-beads promoted cell viability, neurite outgrowth, and up-regulation of inhibitory neurotransmitter expression, which implies that over-expression of SorCS1 may cause abnormal retinal development. Our findings suggest that SorCS1 is involved in the physiological processes of light/visually guided ocular growth.

Purpose Tetramethylpyrazine (TMP) is the active ingredient extracted from the Chinese herb Chuanxiong. The purpose of our study was to identify the mechanism of therapeutic TMP suppression of pathologic chemokine receptor 4 (CXCR4) transcription. Methods C57BL/6J mice with alkali-burned corneas were treated with either TMP eye drops (1.5 mg/mL) or PBS. Corneal neovascularization (CNV) was measured and a clinical assessment was made by slit lamp microscopy. Expression of CXCR4 and the transcription factors nuclear respiratory factor-1 (NRF-1), nuclear factor kappa B (NFκB), forkhead box C1, and yin yang 1 were tracked by real-time RT-PCR and immunofluorescence staining of murine corneas. Western blot, real-time PCR, and immunofluorescence evaluated expression of related genes in human umbilical vein endothelial cells (HUVECs) after 200-μmol/L TMP treatment. In addition, plasmid transfection and chromatin immunoprecipitation assays elucidated the relationship among NRF-1, NFκB, and CXCR4. Results Corneas treated with TMP had smaller areas of neovascularization and scored better in clinical assessments. Injured corneas showed significantly elevated expressions of NRF-1, NFκB, and CXCR4 that were normalized in vivo by TMP treatment. Similarly, in HUVECs in vitro, TMP decreased expression of NRF-1, NFκB, and CXCR4. Overexpression of NFκB or NRF-1 raised the expression of CXCR4 in HUVECs, but not synergistically. Chromatin immunoprecipitation assays detected only NRF-1 bound to the CXCR4 promoter region, suggesting NFκB controls CXCR4 expression by upregulating NRF-1. Together, our data suggest TMP downregulates CXCR4 by repressing NRF-1 expression in CNV, likely indirectly by downregulating NFκB. Conclusions Our results implicate a novel mechanism wherein TMP inhibits neovascularization via an NFκB/NRF-1/CXCR4 circuit.

Natural gases from the Qiudong and Hongtai gas fields in the Taibei sag in the Turpan-Hami Basin of China were analyzed for stable hydrogen and carbon isotopic characteristics, to investigate the origin of the gas and the gas-source correlation. Natural gases from the two gas fields are dominated by alkane gases with methane content varying from 81.61% to 92.57%. Dryness ranges from 0.76 to 0.93, indicating an abundance of wet gas. The carbon and hydrogen isotopic compositions of the methane vary from − 39.8‰ to − 42.6‰ and from − 263‰ to − 279‰ in the Qiudong gas field, respectively, and from − 37.7‰ to − 39.0‰ and from − 250‰ to − 257‰ in the Hongtai gas field, respectively. All gases have a characteristic carbon and hydrogen isotopic distribution pattern among the C1–C5 alkanes, in which δ13CCH4

Cobalt chloride (CoCl

Three kinds of complexing agents were selected to investigate their effects on the morphology and porosity of electroless nickel (EN) deposits on a mild steel substrate. The porosity of the EN coating was tested as a function of the variety of complexing agents with both an electrochemical technique and commonly used chemical spot tests. Meanwhile, the morphology and surface roughness of deposits were examined by atom force microscopy (AFM). It was found that the more stable is the nickel complex, the lower the roughness and the less the porosity of the coating. The reason for this is discussed, considering the complexing agent's effect on the deposition process of EN.

Cognitive radio (CR) is a promising technique for improving the efficiency of utilizing the precious radio spectrum. A cognitive radio network (CRN) testbed not only can verify concepts, algorithms, and protocols for CR, but also can reveal practical problems and guide future research. Vision, architecture, intensive computing, frequency band shifting, security, ultra-wideband receiver and potential applications are discussed in this paper. In support of our arguments, experiments and demonstrations are reported as well.

This is the second paper in a series of using cognitive radio network as wireless sensor network. The motivation of the paper is to push the convergence of radar and communication systems into a unified cognitive network. This paper studies this vision from a secure point of view. We propose two methods for robust spectrum sensing in the same framework of cognitive radio network. The first method is based on robust principal component analysis (PCA), to separate spectrum sensing results into the low rank signal matrix and the sparse attack matrix. Using sparse attack cancellation in least squares, the second method iteratively estimates the relative transmitted power of primary user under the threats of attackers. Then the relative transmitted power of primary user can be calculated from the recovered signal matrix. Both two methods can detect the sparse compromised cognitive radio nodes and effectively obtain the relative transmitted power.

This paper explores the vision of a dual-use sensing/communication system based on Cognitive Radio Network (CRN). The motivation of the paper is to push the convergence of sensing and communication systems into a unified cognitive network. The concept design of this sensing/communication system is presented along with potential functions and challenges. A through tree target detection using real data collected by CRN testbed is demonstrated. The CRN testbed will be built based on Rice WARP nodes. To further exploit the advantages of dynamic spectrum access and frequency diversity, multi-frequency signal, which is similar to OFDM signal, are employed to for detection experiment in the harsh radio environment. The experiment results illustrate the vision of employing a CRN as wireless sensor network.