The ratio of systolic and diastolic pressure is associated with carotid and femoral atherosclerosis.

Background: Although the impact of hypertension on carotid intima-media thickness (IMT) and plaques has been well established, its association with femoral IMT and plaques has not been extensively examined. In addition, the role of the ratio of systolic and diastolic pressure (SDR) in the subclinical atherosclerosis (AS) risk remains unknown. We assessed the relationship between SDR and carotid and femoral AS in a general population. Methods: A total of 7,263 participants aged 35-74 years enrolled from January 2019 to June 2021 in a southeast region of China were included in a cross-sectional study. Systolic and diastolic blood pressure (SBP and DBP) were used to define SDR. Ultrasonography was applied to assess the AS, including thickened IMT (TIMT) and plaque in the carotid and femoral arteries. Logistic regression and restricted cubic spline (RCS) models were the main approaches. Results: The prevalence of TIMT, plaque, and AS were 17.3%, 12.4%, and 22.7% in the carotid artery; 15.2%, 10.7%, and 19.5% in the femoral artery; and 23.8%, 17.9% and 30.0% in either the carotid or femoral artery, respectively. Multivariable logistic regression analysis found a significant positive association between high-tertile SDR and the higher risk of overall TIMT (OR = 1.28, 95% CI = 1.10-1.49), plaques (OR = 1.36, 95%CI = 1.16-1.61), or AS (OR = 1.36, 95% CI = 1.17-1.57), especially in the carotid artery. RCS analysis further revealed the observed positive associations were linear. Further analyses showed that as compared to the low-tertile SDR and non-hypertension group, high-tertile SDR was associated with increased risks of overall and carotid TIMT, plaques, or AS in both groups with or without hypertension. Conclusions: SDR is related to a higher risk of subclinical AS, regardless of hypertension or not, suggesting that as a readily obtainable index, SDR can contribute to providing additional predictive value for AS.

Epilepsy and driving: A preliminary survey of people with epilepsy at an epilepsy clinic in China.

BACKGROUND: Driving is an important part of the daily life for most adults, and restrictions on driving can significantly affect the quality of life for people with epilepsy. This study aimed to investigate the current driving status of patients at an epilepsy clinic in China. METHOD: Study participants were administered a survey by a questionnaire including the demographic and clinical characteristics of seizure, driving-related questions and attitudes to driving. RESULTS: A total of 101 patients responded the survey. Among 33(32.7%) who hold the driving license, 20 (60.6%) still drive, 3 had seizures while driving, and the rate of traffic accidents was 0. There was no significant difference in seizure frequency and type of medication between patients with and without the driving license, but compliance with medication was significantly better for those who held the driving license. CONCLUSIONS: One-third of people with epilepsy hold the driving license and good drug compliance is a favorable factor for driving. Standardizing different levels of restriction on driving for people with epilepsy is urgently needed.

Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter-cohort validation of Shanghai Memory Study and ADNI.

Mild cognitive impairment (MCI) is a critical prodromal stage of Alzheimer's disease (AD), and the mechanism underlying the conversion is not fully explored. Construction and inter-cohort validation of imaging biomarkers for predicting MCI conversion is of great challenge at present, due to lack of longitudinal cohorts and poor reproducibility of various study-specific imaging indices. We proposed a novel framework for inter-cohort MCI conversion prediction, involving comparison of structural, static, and dynamic functional brain features from structural magnetic resonance imaging (sMRI) and resting-state functional MRI (fMRI) between MCI converters (MCI_C) and non-converters (MCI_NC), and support vector machine for construction of prediction models. A total of 218 MCI patients with 3-year follow-up outcome were selected from two independent cohorts: Shanghai Memory Study cohort for internal cross-validation, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for external validation. In comparison with MCI_NC, MCI_C were mainly characterized by atrophy, regional hyperactivity and inter-network hypo-connectivity, and dynamic alterations characterized by regional and connectional instability, involving medial temporal lobe (MTL), posterior parietal cortex (PPC), and occipital cortex. All imaging-based prediction models achieved an area under the curve (AUC) > 0.7 in both cohorts, with the multi-modality MRI models as the best with excellent performances of AUC > 0.85. Notably, the combination of static and dynamic fMRI resulted in overall better performance as relative to static or dynamic fMRI solely, supporting the contribution of dynamic features. This inter-cohort validation study provides a new insight into the mechanisms of MCI conversion involving brain dynamics, and paves a way for clinical use of structural and functional MRI biomarkers in future.

High-Precision Control of Aviation Photoelectric-Stabilized Platform Using Extended State Observer-Based Kalman Filter.

The accuracy of the line-of-sight of aviation photoelectric optoelectronic stabilization platforms is limited by two factors: external disturbance and sensor noise. An extended state observer (ESO) can effectively improve their anti-interference ability. However, due to the serious problem of gyroscope noise, further improvement of an ESO's disturbance suppression effect is limited. This article proposes a control structure that combines a Kalman filter (KF) and ESO, effectively improving upon the interference suppression ability of a traditional ESO under the influence of noise. Firstly, an ESO was used to observe the lumped disturbance of the system, and then, the observed disturbance was compensated for in the control loop. Secondly, based on the compensation servo control system, the state equation of the system was reconstructed using a Kalman filter. Finally, the reconstructed filtered state variables were iterated onto the universal state observer, achieving the observation of disturbances while filtering out sensor noise. Under the conditions of a laboratory flight simulation turntable, the line-of-sight stability accuracy level was improved under disturbance excitation. It can be seen that the combination of a Kalman filter and extended disturbance observer proposed in this project improves the ESO's anti-interference ability under the influence of noise.

Efficacy of Poria cocos and Alismatis rhizoma against diet-induced hyperlipidemia in rats based on transcriptome sequencing analysis.

Hyperlipidemia, a common metabolic disease, is a risk factor for cardiovascular diseases, Poria cocos (PC) and Alismatis rhizoma (AR) serve as a potential treatment. A systematic approach based on transcriptome sequencing analysis and bioinformatics methods was developed to explore the synergistic effects of PC-AR and identify major compounds and potential targets. The phenotypic characteristics results indicated that the high dose (4.54 g/kg) of PC-AR reduced total cholesterol (TC), elevated high-density lipoprotein cholesterol (HDL-C) levels, and improved hepatocyte morphology, as assessed via hematoxylin and eosin (H&E) staining. Transcriptomic profiling processing results combined with GO enrichment analysis to identify the overlapping genes were associated with inflammatory responses. The cytokine-cytokine receptor interaction pathway was found as a potential key pathway using geneset enrichment analysis. Core enrichment targets were selected according to the PC-AR's fold change versus the model. Real-time quantitative PCR analysis validated that PC-AR significantly downregulated the expression of Cxcl10, Ccl2, Ccl4, Cd40 and Il-1ß mRNA (P < 0.05). Molecular docking analysis revealed the significant compounds of PC-AR and the potential binding patterns of the critical compounds and targets. This study provides further evidence that the therapeutic effects of PC-AR on hyperlipidemia in rats through the regulation of inflammation-related targets.

Mouse Abdominal Aortic Aneurysm Model Induced by Periarterial Incubation of Papain.

For decades, numerous experimental animal models have been developed to examine the pathophysiologic mechanisms and potential treatments for abdominal aortic aneurysms (AAAs) in diverse species with varying chemical or surgical approaches. This study aimed to create an AAA mouse model by the periarterial incubation with papain, which can mimic human AAA with advantages such as simplicity, convenience, and high efficiency. Eighty C57BL/6J male mice were randomly assigned to 1 of the 4 groups: papain (1.0 or 2.0 mg), porcine pancreatic elastase, and phosphate-buffered solution. The aortic segment was wrapped for 20 minutes, and the diameter was measured using ultrasound preoperatively and postoperative days 7 and 14. Then, the mice were killed for histomorphometric and immunohistochemical analyses. According to ultrasound measurements and histomorphometric analyses, on postoperative day 7, 65% of mice in the 1.0-mg papain group and 60% of mice in the 2.0-mg papain group developed AAA. In both papain groups, 100% of mice developed AAA, and 65% of mice in the porcine pancreatic elastase group developed AAA on postoperative day 14. Furthermore, hematoxylin/eosin, elastin van Gieson, and Masson staining of tissues from the papain group revealed thickened media and intimal hyperplasia, collagen sediments, and elastin destruction, indicating that AAA histochemical alteration was similar to that of humans. In addition, the immunohistochemical analysis was conducted to detect infiltrated inflammatory cells, such as macrophages and leukocytes, in the aortic wall and hyperplasic adventitia. The expression of matrix metalloproteinase 2 and 9 was significantly upregulated in papain and human AAA tissues. Periarterial incubation with 1.0 mg of papain for 20 minutes can successfully create an experimental AAA model in mice for 14 days, which can be used to explore the mechanism and treatment of human AAA.

The modulation of potassium channels by estrogens facilitates neuroprotection.

Estrogens, the sex hormones, have the potential to govern multiple cellular functions, such as proliferation, apoptosis, differentiation, and homeostasis, and to exert numerous beneficial influences for the cardiovascular system, nervous system, and bones in genomic and/or non-genomic ways. Converging evidence indicates that estrogens serve a crucial role in counteracting neurodegeneration and ischemic injury; they are thereby being considered as a potent neuroprotectant for preventing neurological diseases such as Alzheimer's disease and stroke. The underlying mechanism of neuroprotective effects conferred by estrogens is thought to be complex and multifactorial, and it remains obscure. It is well established that the K+ channels broadly expressed in a variety of neural subtypes determine the essential physiological features of neuronal excitability, and dysfunction of these channels is closely associated with diverse brain deficits, such as ataxia and epilepsy. A growing body of evidence supports a neuroprotective role of K+ channels in malfunctions of nervous tissues, with the channels even being a therapeutic target in clinical trials. As multitarget steroid hormones, estrogens also regulate the activity of distinct K+ channels to generate varying biological actions, and accumulated data delineate that some aspects of estrogen-mediated neuroprotection may arise from the impact on multiple K+ channels, including Kv, BK, KATP, and K2P channels. The response of these K+ channels after acute or chronic exposure to estrogens may oppose pathological abnormality in nervous cells, which serves to extend our understanding of these phenomena.

Stability preserving data-driven models with latent dynamics.

In this paper, we introduce a data-driven modeling approach for dynamics problems with latent variables. The state-space of the proposed model includes artificial latent variables, in addition to observed variables that can be fitted to a given data set. We present a model framework where the stability of the coupled dynamics can be easily enforced. The model is implemented by recurrent cells and trained using backpropagation through time. Numerical examples using benchmark tests from order reduction problems demonstrate the stability of the model and the efficiency of the recurrent cell implementation. As applications, two fluid-structure interaction problems are considered to illustrate the accuracy and predictive capability of the model.

Resonance Suppression of Servo System Based on State Equalizer Method.

Aiming at the problem of mechanical resonance faced by the servo control system of the aero-optical stabilization platform, based on the proportional integral and disturbance observer combination (PI+DOB) control algorithm, a state equalizer speed closed loop is proposed. Compared with the traditional PI+DOB control algorithm, this new control structure can suppress the resonance peak and the anti-resonance peak at the same time. The experimental results show that compared with the PI+DOB control algorithm, after adding the state equalizer speed closed-loop to compensate for the model, the closed-loop bandwidth is increased by 42%. The anti-disturbance capability of the control system has been significantly improved, and it has good robustness under vibration conditions. To sum up, adding the state equalizer speed closed loop on the basis of PI+DOB has an obvious effect on the suppression of mechanical resonance and the performance improvement of the control system.

Beneficial effects of carvedilol modulating potassium channels on the control of glucose.

The increased prevalence of hypertensive patients with type 2 diabetes mellitus (T2DM) is evident worldwide, leading to a higher risk of cardiovascular disease onset, which is substantially associated with disabilities and mortality in the clinic. In order to achieve the satisfyingly clinical outcomes and prognosis, the comprehensive therapies have been conducted with a beneficial effect on both blood pressure and glucose homeostasis, and clinical trials reveal that some kind of antihypertensive drugs such as angiotensin converting enzyme inhibitors (ACE-I) may, at least in part, meet the dual requirement during the disease management. As a nonselective ß-blocker, carvedilol is employed for treating many cardiovascular diseases in clinical practice, including hypertension, angina pectoris and heart failure, and also exhibit the effectiveness for glycemic control and insulin resistance. Apart from alleviating sympathetic nervous system activity, several causes, such as lowering oxygen reactive species, may contribute to the effects of carvedilol on controlling plasma glucose levels, suggesting a feature of this drug having multiple targets. Interestingly, numerous distinct K+ channels expressed in pancreatic ß-cells and peripheral insulin-sensitive tissues, which play a sentential role in glucose metabolism, are subjected to extensive modulation of carvdilol, establishing a linkage between K+ channels and drug's effects on the control of glucose. A variety of evidence shows that the impact of carvedilol on different K+ channels, including Kv, KAch, KATP and K2 P, can lead to positive influences for glucose homeostasis, contributing to its clinical beneficial effectiveness in treatment of hypertensive patients with T2DM. This review focus on the control of plasma glucose conferred by carvedilol modulation on K+ channels, providing the novel mechanistic explanation for drug's actions.

Adenosine Downregulates the Activities of Glutamatergic Neurons in the Paraventricular Hypothalamic Nucleus Required for Sleep.

Adenosine is an endogenous substance that regulates sleep homeostasis. It plays an important role in sleep induction under physiological condition. So far, the neural mechanisms underlying sleep-promoting effects of adenosine are not completely clear. Recent studies have shown that glutamatergic neurons in the paraventricular hypothalamic nucleus (PVH) play an important role in wakefulness. Using whole-cell patch-clamp, we found that adenosine can inhibit glutamatergic neurons in PVH. This inhibition is mainly achieved by activating adenosine type 1 receptors, thereby reducing hyperpolarization-activated cyclic nucleotide-gated cation channels. By recording electroencephalogram (EEG) and electromyography (EMG), it was found that local administration of adenosine type 1 receptor blocker in PVH could significantly reduce the NREM sleep. On the contrary, if adenosine was given, it could increase the NREM sleep. These results suggest that adenosine can promote sleep by reducing the excitability of PVH neurons. This findings reveal a novel mechanism of adenosine regulating sleep homeostasis.

Early Renal-Replacement Therapy May Reduce the All-Cause Mortality of Severe COVID-19: An Observational Cohort Study.

INTRODUCTION: The efficacy of renal-replacement treatment (RRT) remains to be validated in COVID-19. In this retrospective cohort study, we aimed to assess the efficacy of early initiation of RRT in intensive care unit (ICU) adults with severe COVID-19. METHODS: Fifty-eight adult patients in ICU with critically ill or severe COVID-19 with a tendency of critical illness were recruited from February 9, 2020, to March 30, 2020. Early RRT were determined by the ICU medical team based on boom in cytokines levels, increased organs injury/failure, and rapid aggravation of condition. All participants were followed up from the first day of ICU admission to March 30, 2020. The primary outcome was all-cause mortality in ICU. RESULTS: The mean age of the cohort was 68.4 ± 14.6 years, with 81.0% having at least one comorbidity before hospitalization. Twenty patients (34.5%) initiated early RRT after 24.1 ± 10.4 days from the onset and 6.4 ± 3.6 days from ICU admission. Thirty-four of 58 participants (58.6%) died during ICU follow-up. Univariate and multivariate Cox proportional-hazards model showed that early RRT was associated with a lower risk of all-cause mortality in ICU with an adjusted HR of 0.280 (95% CI: 0.106-0.738, p = 0.010). Sudden unexpected death (SUD) was remarkably reduced in the early RRT group, compared with the control group (0.2 vs. 2.9 per 100 person-day, p = 0.02). CONCLUSION: Early RRT can reduce the all-cause in-hospital mortality, especially SUD in patients with severe COVID-19, but not improve multi-organ impairment or increase the risk of AKI. Early initiation of RRT merits an optional strategy in critically ill patients with COVID-19 (ChiCTR2000030773).

Iterative Learning-Based Negative Effect Compensation Control of Disturbance to Improve the Disturbance Isolation of System.

At present, the cogging torque of permanent magnet synchronous motors (PMSM) seriously limits the Los pointing accuracy of aviation photoelectric stabilization platforms based on PMSM, which also restricts the requirements of ultra-long-distance and high-precision aviation reconnaissance and detection. For this problem, an off-line iterative learning control (ILC) was designed, and on this basis, a control method of negative effect compensation of disturbance (NECOD) is proposed. Firstly, the "dominant disturbance torque" in the system, that is, the cogging torque with the characteristics of position periodicity, was suppressed by off-line ILC according to different positions. Then, for the "residual disturbance" after compensation, NECOD was used to suppress it. In the constant speed scanning experiment of the aviation photoelectric stabilization platform, the method of combining the off-line iterative learning controller and the negative effect compensation of disturbance (NECOD + ILC) proposed in this paper significantly improved the Los control accuracy of the platform when compared with the classical active disturbance rejection control (ADRC) and ADRC + ILC methods, and the Los pointing error of the constant speed scanning process had only increased by less than 5% when the system had ±15% parameter perturbation. In addition, NECOD + ILC has fewer parameters and is easy to adjust, which is conducive to engineering application and promotion.

Alzheimer's disease therapy based on acetylcholinesterase inhibitor/blocker effects on voltage-gated potassium channels.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder with progressive loss of memory and other cognitive functions. The pathogenesis of this disease is complex and multifactorial, and remains obscure until now. To enhance the declined level of acetylcholine (ACh) resulting from loss of cholinergic neurons, acetylcholinesterase (AChE) inhibitors are developed and successfully approved for AD treatment in the clinic, with a limited therapeutic effectiveness. At present, it is generally accepted that multi-target strategy is potently useful for designing novel drugs for AD. Accumulated evidence reveals that Kv channels, which are broadly expressed in brain and possess crucial functions in modulating the neuronal activity, are inhibited by several acetylcholinesterase (AChE) inhibitors, such as tacrine, bis(7)-tacrine, donepezil and galantamine. Inhibition of Kv channels by these AChE inhibitors can generate neuroprotective effects by either mitigating Aß toxicity and neuronal apoptosis, or facilitating cell proliferation. These inhibitory effects provide additional explanations for clinical beneficial effectiveness of AChE inhibitors, meaning that Kv channel is a promising candidate target for novel drugs for AD therapy.

Projection-based model reduction for the immersed boundary method.

Fluid-structure interactions are central to many biomolecular processes, and they impose a great challenge for computational and modeling methods. In this paper, we consider the immersed boundary method (IBM) for biofluid systems, and to alleviate the computational cost, we apply reduced-order techniques to eliminate the degrees of freedom associated with the large number of fluid variables. We show how reduced models can be derived using Petrov-Galerkin projection and subspaces that maintain the incompressibility condition. More importantly, the reduced-order model (ROM) is shown to preserve the Lyapunov stability. We also address the practical issue of computing coefficient matrices in the ROM using an interpolation technique. The efficiency and robustness of the proposed formulation are examined with test examples from various applications.

Estrogen-induced downregulation of TASK-1 expression through estrogen receptor ß in N2A cells.

BACKGROUND: Our previous data revealed that reduction of TASK-1 expression, as a consequence of exposure to 17ß-estradiol, could participate in neuroprotective effects in N2A cells. However, it is unclear which estrogen receptor underlies these effects of 17ß-estradiol. METHODS AND RESULTS: In this study, the knockdown experiments are carried out to clarify the estrogen receptor responsible for effects of estrogen on TASK-1 channels. Subsequently, data from QPCR measurements reveal that estrogen receptor ß (ERß), but not estrogen receptor α, serves as a binding target for 17ß-estradiol after a 48-h treatment. CONCLUSIONS: The current result suggests the implication of the ERß-dependent manner in the pro-proliferative action of estrogen via TASK-1 channels.

Test-Retest Reliability of the Coronary Heart Disease Damp Phlegm and Blood Stasis Pattern Questionnaire: Results from a Multicenter Clinical Trial.

BACKGROUND: Damp phlegm and blood stasis pattern (DPBSP) is the main pattern in coronary heart disease (CHD) patients. To quantify and standardize the diagnosis of DPBSP, questionnaires are usually administered. The CHD Damp Phlegm and Blood Stasis Pattern Questionnaire (CHD-DPBSPQ) is the standard metric for measuring CHD-DPBSP signs and symptoms in practice and clinical research. The CHD-DPBSPQ has moderate diagnostic efficiency, as evidenced by its receiver operating characteristic curves. Furthermore, and high reliability and validity have been shown in some studies but not in a multicenter clinical trial. Our purpose was to evaluate the test-retest reliability of a proprietary CHD-DPBSPQ. METHODS: The CHD-DPBSPQ uses a standard procedure for measuring symptoms. The (interrater) reliability and validity of this questionnaire have been previously studied. Here, we evaluated the test interval and weighted kappa value of items of test-retest (intrarater) reliability of the CHD-DPBSPQ. The test-retest reliability was evaluated by the intraclass correlation coefficient (ICC) for the total CHD-DPBSPQ score and the phlegm domain and blood stasis domain scores. Weighted kappa statistics were calculated for the individual CHD-DPBSPQ items. RESULTS: Using the CHD-DPBSPQ, 79 patients with late-stage CHD who were participating in a multicenter clinical trial were assessed twice. The ICCs for the CHD-DPBSPQ score were as follows: 0.827 for the total CHD-DPBSPQ, 0.778 for the phlegm domain score, and 0.828 for the blood stasis domain score. The reliability was slightly better in patients whose test interval was ≤14 days. The weighted kappa values of individual items showed moderate consistency. CONCLUSIONS: The CHD-DPBSPQ was found to have excellent test-retest reliability in this sample of patients.

A projection-based reduced-order method for electron transport problems with long-range interactions.

Long-range interactions play a central role in electron transport. At the same time, they present a challenge for direct computer simulations since sufficiently large portions of the bath have to be included in the computation to accurately compute the Coulomb potential. This article presents a reduced-order approach by deriving an open quantum model for the reduced density matrix. To treat the transient dynamics, the problem is placed in a reduced-order framework. The dynamics described by the Liouville-von Neumann equation is projected to subspaces using a Petrov-Galerkin projection. In order to recover the global electron density profile as a vehicle to compute the Coulomb potential, we propose a domain decomposition approach, where the computational domain also includes segments of the bath that are selected using logarithmic grids. This approach leads to a multi-component self-energy that enters the effective Hamiltonian. We demonstrate the accuracy of the reduced model using a molecular junction built from lithium chains.

CTLA-4 promotes lymphoma progression through tumor stem cell enrichment and immunosuppression.

The recurrence rate of lymphoma is very high, and tumor stem cells may be an important mechanism. Cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) can inhibit antitumor immunity and promote cancer progression, but its role and mechanism in lymphoma are still unclear. Here we collected lymphoma tissue and peripheral blood from patients with diffuse large B-cell lymphoma (DLBCL). Results showed that CTLA-4 expression and CD44+ cell in the high-risk group were significantly higher than that in the low-risk group. Correlation analysis showed that CTLA-4 expression positively correlated with CD44+ cell in lymphoma tissue and regulatory T (Treg) cells in lymphocytes. In vitro experiment showed that CTLA-4 increased the ratio of lymphoma stem cells, and proliferation and invasion of lymphoma cells through TGF-ß pathway. Moreover, CTLA-4 enhanced the proliferation of Treg cells induced by lymphoma cells. Animal experiments showed that CTLA-4 can promote transplanted lymphoma growth. Immunohistochemistry results showed that both Ki-67 and CD44+ cells increased significantly in the CTLA-4 group. TGF-ß neutralization can significantly block these effects of CTLA-4. In conclusion, CTLA-4 promoted DLBCL progression through lymphoma stem cell enrichment and immunosuppression.

Petrov-Galerkin methods for the construction of non-Markovian dynamics preserving nonlocal statistics.

A common observation in coarse-graining a molecular system is the non-Markovian behavior, primarily due to the lack of scale separations. This is reflected in the strong memory effect and the non-white noise spectrum, which must be incorporated into a coarse-grained description to correctly predict dynamic properties. To construct a stochastic model that gives rise to the correct non-Markovian dynamics, we propose a Galerkin projection approach, which transforms the exhausting effort of finding an appropriate model to choosing appropriate subspaces in terms of the derivatives of the coarse-grained variables and, at the same time, provides an accurate approximation to the generalized Langevin equation. We introduce the notion of fractional statistics that embodies nonlocal properties. More importantly, we show how to pick subspaces in the Galerkin projection so that those statistics are automatically matched.