Social Determinants of Cardiovascular Risk Factors Among Asian American Subgroups.

BACKGROUND: Social determinants of health (SDOH) play a significant role in the development of cardiovascular risk factors. We investigated SDOH associations with cardiovascular risk factors among Asian American subgroups. METHODS AND RESULTS: We utilized the National Health Interview Survey, a nationally representative survey of US adults, years 2013 to 2018. SDOH variables were categorized into economic stability, neighborhood and social cohesion, food security, education, and health care utilization. SDOH score was created by categorizing 27 SDOH variables as 0 (favorable) or 1 (unfavorable). Self-reported cardiovascular risk factors included diabetes, high cholesterol, high blood pressure, obesity, insufficient physical activity, suboptimal sleep, and nicotine exposure. Among 6395 Asian adults aged ≥18 years, 22.1% self-identified as Filipino, 21.6% as Asian Indian, 21.0% as Chinese, and 35.3% as other Asian. From multivariable-adjusted logistic regression models, each SD increment of SDOH score was associated with higher odds of diabetes among Chinese (odds ratio [OR], 1.45; 95% CI, 1.04-2.03) and Filipino (OR, 1.24; 95% CI, 1.02-1.51) adults; high blood pressure among Filipino adults (OR, 1.28; 95% CI, 1.03-1.60); insufficient physical activity among Asian Indian (OR, 1.42; 95% CI, 1.22-1.65), Chinese (OR, 1.58; 95% CI, 1.33-1.88), and Filipino (OR, 1.24; 95% CI, 1.06-1.46) adults; suboptimal sleep among Asian Indian adults (OR, 1.20; 95% CI, 1.01-1.42); and nicotine exposure among Chinese (OR, 1.56; 95% CI, 1.15-2.11) and Filipino (OR, 1.50; 95% CI, 1.14-1.97) adults. CONCLUSIONS: Unfavorable SDOH are associated with higher odds of cardiovascular risk factors in Asian American subgroups. Culturally specific interventions addressing SDOH may help improve cardiovascular health among Asian Americans.

Association of Acculturation with Cardiovascular Risk Factors in Asian-American Subgroups.

Objective: This cross-sectional study aims to better understand the heterogeneous associations of acculturation level on CV risk factors among disaggregated Asian subgroups. We hypothesize that the association between acculturation level and CV risk factors will differ significantly by Asian subgroup. Methods: We used the National Health Interview Survey (NHIS), a nationally representative US survey, years 2014-18. Acculturation was defined using: (a) years in the US, (b) US citizenship status, and (c) level of English proficiency. We created an acculturation index, categorized into low vs. high (scores of 0-3 and 4, respectively). Self-reported CV risk factors included diabetes, high cholesterol, hypertension, obesity, tobacco use, and sufficient physical activity. Rao-Scott Chi Square was used to compare age-standardized, weighted prevalence of CV risk factors between Asian subgroups. We used logistic regression analysis to assess associations between acculturation and CV risk factors, stratified by Asian subgroup. Results: The study sample consisted of 6,051 adults ≥ 18 years of age (53.9% female; mean age 46.6 [SE 0.33]). The distribution by race/ethnicity was Asian Indian 26.9%, Chinese 22.8%, Filipino 18.1%, and other Asian 32.3%. The association between acculturation and CV risk factors differed by Asian subgroups. From multivariable adjusted models, high vs. low acculturation was associated with: high cholesterol amongst Asian Indian (OR=1.57, 95% CI: 1.11, 2.37) and other Asian (OR=1.48, 95% CI: 1.10, 2.01) adults, obesity amongst Filipino adults (OR= 1.62, 95% CI: 1.07, 2.45), and sufficient physical activity amongst Chinese (OR= 1.54, 95% CI: 1.09, 2.19) and Filipino adults (OR=1.58, 95% CI: 1.10, 2.27). Conclusion: This study demonstrates that acculturation is heterogeneously associated with higher prevalence of CV risk factors among Asian subgroups. More studies are needed to better understand these differences that can help to inform targeted, culturally specific interventions.

Efficacy of alanyl glutamine in nutritional support therapy for patients with sepsis: A protocol for systematic review and meta-analysis.

BACKGROUND: Sepsis is a systemic inflammatory response caused by infection, which is a common complication after severe infection, trauma, shock, and surgery, and is also an important factor in inducing septic shock and multiple organ dysfunction syndrome (MODS), and has become one of the important causes of death in critically ill patients. Septic patients with gastrointestinal transport function weakened, are prone to malnutrition, resulting in decreased immune function, thereby affecting the therapeutic effect. Clinical practice shows that the nutritional metabolism and immune response of patients with sepsis can be effectively improved by giving alanyl glutamine nutritional support treatment, but there is no evidence of evidence-based medicine. The study carried out in this protocol aims to evaluate the effectiveness of alanyl glutamine in nutritional support therapy for patients with sepsis. METHODS: The Cochrane Library, PubMed, Embase, Web of Science, WHO International Clinical Trials Registry Platform, CNKI, CBM, VIP, and Wanfang databases were searched by computer, to retrieve all randomized controlled trials (RCTs) on nutritional support for the treatment of sepsis with alanyl glutamine from the date of database establishment to December 2020. Two researchers independently selected the study, extracted and managed the data. RevMan5.3 software was used to analyze the included literature. RESULTS: This study observed the changes of serum albumin (ALB), prealbumin (PAB), hemoglobin (Hb), C-reactive protein (CRP), immunoglobulin (IgG, IgA, and IgM), APACHE II score before and after treatment to evaluate the efficacy of alanyl glutamine in nutritional support therapy for patients with sepsis. CONCLUSION: This study will provide reliable evidence for the application of alanyl glutamine in nutritional support therapy for patients with sepsis. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/VRZPJ.

DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection.

Pulmonary nodule detection plays an important role in lung cancer screening with low-dose computed tomography (CT) scans. It remains challenging to build nodule detection deep learning models with good generalization performance due to unbalanced positive and negative samples. In order to overcome this problem and further improve state-of-the-art nodule detection methods, we develop a novel deep 3D convolutional neural network with an Encoder-Decoder structure in conjunction with a region proposal network. Particularly, we utilize a dynamically scaled cross entropy loss to reduce the false positive rate and combat the sample imbalance problem associated with nodule detection. We adopt the squeeze-and-excitation structure to learn effective image features and utilize inter-dependency information of different feature maps. We have validated our method based on publicly available CT scans with manually labelled ground-truth obtained from LIDC/IDRI dataset and its subset LUNA16 with thinner slices. Ablation studies and experimental results have demonstrated that our method could outperform state-of-the-art nodule detection methods by a large margin.

Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis.

Feature dimensionality reduction plays an important role in radiomic studies with a large number of features. However, conventional radiomic approaches may suffer from noise, and feature dimensionality reduction techniques are not equipped to utilize latent supervision information of patient data under study, such as differences in patients, to learn discriminative low dimensional representations. To achieve robustness to noise and feature dimensionality reduction with improved discriminative power, we develop a robust collaborative clustering method to simultaneously cluster patients and radiomic features into distinct groups respectively under adaptive sparse regularization. Our method is built upon matrix tri-factorization enhanced by adaptive sparsity regularization for simultaneous feature dimensionality reduction and denoising. Particularly, latent grouping information of patients with distinct radiomic features is learned and utilized as supervision information to guide the feature dimensionality reduction, and noise in radiomic features is adaptively isolated in a Bayesian framework under a general assumption of Laplacian distributions of transform-domain coefficients. Experiments on synthetic data have demonstrated the effectiveness of the proposed approach in data clustering, and evaluation results on an FDG-PET/CT dataset of rectal cancer patients have demonstrated that the proposed method outperforms alternative methods in terms of both patient stratification and prediction of patient clinical outcomes.

SLICR super-voxel algorithm for fast, robust quantification of myocardial blood flow by dynamic computed tomography myocardial perfusion imaging.

We created and evaluated a processing method for dynamic computed tomography myocardial perfusion imaging (CT-MPI) of myocardial blood flow (MBF), which combines a modified simple linear iterative clustering algorithm (SLIC) with robust perfusion quantification, hence the name SLICR. SLICR adaptively segments the myocardium into nonuniform super-voxels with similar perfusion time attenuation curves (TACs). Within each super-voxel, an α-trimmed-median TAC was computed to robustly represent the super-voxel and a robust physiological model (RPM) was implemented to semi-analytically estimate MBF. SLICR processing was compared with another voxel-wise MBF preprocessing approach, which included a spatiotemporal bilateral filter (STBF) for noise reduction prior to perfusion quantification. Image data from a digital CT-MPI phantom and a porcine ischemia model were evaluated. SLICR was ∼ 50 -fold faster than voxel-wise RPM and other model-based methods while retaining sufficient resolution to show clinically relevant features, such as a transmural perfusion gradient. SLICR showed markedly improved accuracy and precision, as compared with other methods. At a simulated MBF of 100 mL/min-100 g and a tube current-time product of 100 mAs (50% of nominal), the MBF estimates were 101 ± 12 , 94 ± 56 , and 54 ± 24 mL / min - 100 g for SLICR, the voxel-wise Johnson-Wilson model, and a singular value decomposition-model independent method with STBF, respectively. SLICR estimated MBF precisely and accurately ( 103 ± 23 mL / min - 100 g ) at 25% nominal dose, while other methods resulted in larger errors. With the porcine model, the SLICR results were consistent with the induced ischemia. SLICR simultaneously accelerated and improved the quality of quantitative perfusion processing without compromising clinically relevant distributions of perfusion characteristics.

Anti-aging effects exerted by Tetramethylpyrazine enhances self-renewal and neuronal differentiation of rat bMSCs by suppressing NF-kB signaling.

In order to improve the therapeutic effects of mesenchymal stem cell (MSC)-based therapies for a number of intractable neurological disorders, a more favorable strategy to regulate the outcome of bone marrow MSCs (bMSCs) was examined in the present study. In view of the wide range of neurotrophic and neuroprotective effects, Tetramethylpyrazine (TMP), a biologically active alkaloid isolated from the herbal medicine Ligusticum wallichii, was used. It was revealed that treatment with 30-50 mg/l TMP for 4 days significantly increased cell viability, alleviated senescence by suppressing NF-κB signaling, and promoted bMSC proliferation by regulating the cell cycle. In addition, 40-50 mg/l TMP treatment may facilitate the neuronal differentiation of bMSCs, verified in the present study by presentation of neuronal morphology and expression of neuronal markers: microtubule-associated protein 2 (MAP-2) and neuron-specific enolase (NSE). The quantitative real-time polymerase chain reaction (qRT-PCR) revealed that TMP treatment may promote the expression of neurogenin 1 (Ngn1), neuronal differentiation 1 (NeuroD) and mammalian achaete-scute homolog 1 (Mash1). In conclusion, 4 days of 40-50 mg/l TMP treatment may significantly delay bMSC senescence by suppressing NF-κB signaling, and enhancing the self-renewal ability of bMSCs, and their potential for neuronal differentiation.

Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis.

Radiomic approaches have achieved promising performance in prediction of clinical outcomes of cancer patients. Particularly, feature dimensionality reduction plays an important role in radiomic studies. However, conventional feature dimensionality reduction techniques are not equipped to suppress data noise or utilize latent supervision information of patient data under study (e.g. difference in patients) for learning discriminative low dimensional representations. To achieve feature dimensionality reduction with improved discriminative power and robustness to noisy radiomic features, we develop an adaptive sparsity regularization based collaborative clustering method to simultaneously cluster patients and radiomic features into distinct groups respectively. Our method is built on adaptive sparsity regularized matrix tri-factorization for simultaneous feature denoising and dimension reduction so that the noise is adaptively isolated from the features, and grouping information of patients with distinctive features provides latent supervision information to guide feature dimension reduction. The sparsity regularization is grounded on distribution modeling of transform-domain coefficients in a Bayesian framework. Experiments on synthetic data have demonstrated the effectiveness of the proposed approach in data clustering, and empirical results on an FDG-PET/CT dataset of rectal cancer patients have demonstrated that the proposed method outperforms alternative methods in terms of both patient stratification and prediction of patient clinical outcomes.

[The application of popliteal vein anatomy study and valve construction procedure].

OBJECTIVE: To analyze anatomy data of popliteal veins (PV), with the purpose of selection of popliteal venous valves construction segment via venography, and to evaluate the surgical results. METHODS: From February 1998 to November 2010, after analyzing the popliteal vessel anatomy data of 39 limbs and related phlebography research of 862 cases, 102 patients (69 male and 33 female patients, aged from 48 to 71 years, mean 59 years) with severe deep venous insufficiency were selected for popliteal venous valve construction procedures. Doppler ultrasound, continuous dynamic venography, and intraoperative venous pressure measurements were used to assess the hemodynamic changes pre- and postoperatively. Venous clinical severity score (VCSS) were used to evaluate long-term results of deep venous valve construction procedures. RESULT: In the 102 patients, 93.7% patients had one pair of valves in popliteal vein (PV), locating in the distal 1/3 segment of PV, with gastrocnemius veins (GV) joining with PV above PV valves. Postoperative blood flow volume of the PV was significantly higher than the preoperative volume (732.3 ml/min vs. 150.2 ml/min, t = 8.979, P < 0.001). The proximal pressure was significantly lower than the distal pressure ((12 ± 3) cm H(2)O vs. (15 ± 3) cm H(2)O, 1 cm H(2)O = 0.098 kPa, t = 8.049, P < 0.001). VCSS score was significantly lower after the surgery ((34 ± 15) cm H(2)O vs. (41 ± 14) cm H(2)O, t = 59.780, P < 0.001). Pre- and postoperative hemodynamic changes and VCSS scores were statistically significant (9.3 ± 1.9 vs. 1.8 ± 1.0, t = 59.780, P < 0.001). Mean follow-up were 8.9 years with an ulcer recovery rate of 96.3%, and a 3.7% ulcer recurrent rate. CONCLUSIONS: Popliteal vessel anatomy study and venography research provide critical information for the PV valve construction part selection, which stayed proximal to the communications of GV and PV. Restoration of gastrocnemius pump function and satisfactory long-term efficacy are received after valve construction.

[Treatment of long-segment iliofemoral occlusive disease: two extra-anatomic bypass surgeries].

OBJECTIVE: To report and evaluate the clinical results of surgical treatment for long-segment iliofemoral arteriosclerosis obliterans, including external iliac-popliteal (EIP) and femoral-deep femoral (FDF) crossover bypass surgeries. METHODS: From July 1995 to December 2009, 85 patients (61 male, 24 female, aged from 64 to 91 years, mean age 75 years) with comprehensive unilateral iliac-superficial femoral arteriosclerosis obliterans were involved in this research. According to Fontaine classification, the 85 patients could be graded as 62 class IIb-III patients (72.9%), and 23 class IV patients (27.1%). In CT angiography or DSA examinations, the 85 patients were grouped into EIP (n = 49) and FDF (n = 36) surgical groups on the basis of visualizations in the affected deep femoral, supra-knee/infra-knee popliteal arteries. The healing time of ulcers and toe amputation wound, ankle-brachial index, and blood flow velocity in the affected limb together with accumulative patency rates in 1, 3 and 5 years and limb salvage rates in 3 and 5 years were analyzed. RESULTS: None of the 85 patients died or had extremity amputated in perioperatively. Seventy-four patients (87.1%) had been followed up from 2 to 13 years (mean 5.7 years). Postoperative ankle-brachial index of FDF and EIP groups was 0.55 ± 0.11, and 0.94 ± 0.13 (t = -21.88, P = 0.000). Postoperative velocity of popliteal artery blood flow in FDF and EIP groups was (32 ± 9) cm/s, and (48 ± 4) cm/s (t = 16.76, P = 0.000); velocity of anterior or posterior tibial artery was (22 ± 7) cm/s, and (42 ± 4) cm/s (t = 10.50, P = 0.000). The primary and secondary patency rates of FDF and EIP groups were 87.8% and 88.3%, 80.7% and 81.2%, 68.4% and 57.4% at 1, 3 and 5 years, respectively. Limb salvage rates of FDF and EIP groups were 87.6% and 88.6%, 76.7% and 71.3%, at 3 and 5 years, respectively. There were no statistically significant differences in 1, 3, and 5 years' cumulative secondary patency rate and limb salvage rate between FDF and EIP groups. CONCLUSIONS: As extra-anatomic bypass surgeries, FDF and EIP are both determined to be alternative procedures for unilateral common iliac-superficial femoral artery occlusive disease, especially suitable for high-risk patients. EIP group patients have better clinical outcomes than those in FDF group.