Implantable cardiac monitor and leadless pacemaker in the management of syncope due to intermittent high-degree atrioventricular block: a case report.

BACKGROUND: Lead dislodgements, tricuspid valve failure, and wound infections are prominent issues addressed by leadless pacemakers (LPM). These devises have emerged as viable alternatives to conventional transvenous pacemakers. LPMs offer minimized complications and effective pacing, particularly beneficial for elderly patients with a low body mass index (BMI) who are at heightened infection of risk. The Micra AV leadless pacemaker was released in the US in 2020, featuring a VDD pacing mode akin to conventional pacemakers. It senses atrial activity to pace ventricular beats while maintaining the natural atrioventricular activation sequence. Micra AV achieves atrioventricular synchronization through mechanical sensing principles. Ongoing research aims to assess its efficacy, implantation feasibility, and clinical safety. CASE PRESENTATION: An 83-year-old man with a history of syncope was the focus of this case study. An implantable cardiac monitor (ICM) recorded occasional high-degree atrioventricular block in the patient. Subsequently, the Micra AV was implanted via the left femoral vein, and its settings were adjusted in accordance with data obtained from the ICM. No significant issues regarding pacing threshold or impedance were found during the follow-up examinations post-surgery. Importantly, the patient experienced a noticeable reduction in symptoms compared to before the implantation. DISCUSSION: This case underscores the significance of ICM monitoring in elucidating cardiac events leading to syncope and guiding appropriate treatment. It also highlights the successful outcomes and reliable implantation of the Micra AV for managing high-degree atrioventricular block. This study contributes to the growing body of evidence supporting the adoption of leadless pacemakers as a viable option for patients requiring cardiac pacing, particularly those vulnerable to complications associated with traditional pacemakers. It provides real-world evidence of Micra AV's efficacy and safety, further validating its role in clinical practice.

Study on the photoaging process and metal ion release of plastic films with two kinds of structures in marine environment: Aliphatic and aromatic polymers.

The prevalence of plastics in the oceans has significantly intensified microplastic pollution, contributing to broader marine secondary pollution issues. This paper examines how plastic structure affects the aging characteristics of plastics and the release of metal ions, to better understand this secondary source of marine pollution. This study simulate the photoaging of plastics in natural environments, focusing on aliphatic and aromatic polymers. The results showed that the photodegradation degree was higher for aliphatic than aromatic polymers. All polymers contained thirteen detectable metals, with their release increasing over time due to photoaging, The release dynamics of these metal ions correlated more strongly with the level of polymer degradation rather than with the polymer structure itself, adhering to a second-order kinetic model driven by surface and intraparticle diffusion processes. The results will help control and treat marine plastic pollution.

Beneficial effects of upgrading to His-Purkinje system pacing in patients with pacing-induced cardiomyopathy: a systematic review and meta-analysis.

Background: The purpose of this study was to evaluate the effectiveness of His-Purkinje system pacing (HPSP) in the management of patients with pace-induced cardiomyopathy (PICM). Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched comprehensively to collect related studies published from the inception of databases to June 1, 2022. R 4.04 software, including the Metafor package, matrix package, and the Meta package, was utilized to conduct the singe-arm meta-analysis. The methodology index for non-randomized studies (MINORS) was used to assess the methodological quality of the included studies. Results: A total of seven studies were included, involving 164 PICM patients. The meta-analysis showed that HPSP ameliorated the left ventricular ejection fraction (LVEF) by 13.41% (95% CI [11.21-15.61]), improved the New York Heart Association (NYHA) classification by 1.02 (95% CI [-1.41 to -0.63]), and shortened the QRS duration (QRSd) by 60.85 ms (95% CI [-63.94 to -57.75]), resulting in improved cardiac functions in PICM patients. Besides, HPSP reversed the ventricular remodeling, with a 32.46 ml (95% CI [-53.18 to -11.75]) decrease in left ventricular end systolic volume (LVESV) and a 5.93 mm (95% CI [-7.68 to -4.19]) decrease in left ventricular end-diastolic dimension (LVEDD). HPSP also showed stable electrical parameters of pacemakers, with a 0.07 V (95% CI [0.01-0.13]) increase in pacing threshold, a 0.02 mV (95% CI [-0.85 to 0.90]) increase in sensed R-wave amplitude, and a 31.12 Ω reduction in impedance (95% CI [-69.62 to 7.39]). Compared with LBBP, HBP improved LVEF by 13.28% (95% CI [-11.64 to 14.92]) vs 14.43% (95% CI [-13.01 to 15.85]), ameliorated NHYA classification by 1.18 (95% CI [-1.97 to -0.39]) vs 0.95 (95% CI [-1.33 to -0.58]), shortened QRSd by 63.16 ms (95% CI [-67.00 to -59.32]) vs 57.98 ms (95% CI [-62.52 to -53.25]), and decreased LVEDD by 4.12 mm (95% CI [-5.79 to -2.45]) vs 6.26 mm (95% CI [-62.52 to -53.25]). The electrical parameters of the pacemaker were stable in both groups. Conclusions: This meta-analysis showed that HPSP could significantly improve cardiac function, promote reverse remodeling, and provide stable electrical parameters of pacemakers for PICM patients.

Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring.

We consider a novel class of semiparametric joint models for multivariate longitudinal and survival data with dependent censoring. In these models, unknown-fashion cumulative baseline hazard functions are fitted by a novel class of penalized-splines (P-splines) with linear constraints. The dependence between the failure time of interest and censoring time is accommodated by a normal transformation model, where both nonparametric marginal survival function and censoring function are transformed to standard normal random variables with bivariate normal joint distribution. Based on a hybrid algorithm together with the Metropolis-Hastings algorithm within the Gibbs sampler, we propose a feasible Bayesian method to simultaneously estimate unknown parameters of interest, and to fit baseline survival and censoring functions. Intensive simulation studies are conducted to assess the performance of the proposed method. The use of the proposed method is also illustrated in the analysis of a data set from the International Breast Cancer Study Group.

Mechanisms Underlying the Differences in the Pharmacokinetics of Six Active Constituents of Huangqi Liuyi Decoction between Normal and Diabetic Nephropathy Mouse Models.

The aim of this study was to explore the mechanisms underlying the differences in the pharmacokinetics of Huangqi Liuyi decoction extract (HQD) under physiological and pathological conditions. The roles of liver cytochrome P450 metabolic enzymes (Cyp450) and small intestinal transporters were also investigated. The cocktail probe drug method was used to investigate the effects of diabetic nephropathy (DN) and HQD on metabolic enzyme activity. The expression levels of liver Cyp450 metabolic enzymes (Cyp1A2, Cyp2C37, Cyp3A11, Cyp2E1, and Cyp2C11) and small intestinal transporters (breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), organic cation transporters (OCTs), and multidrug resistance-associated protein (MRPs) were determined using western blot. Compared to normal mice, the expression of OCT1, OCT2, MRP1, and MRP2 was increased in DN mice, while that of P-gp and BCRP (P < 0.05 and P < 0.001) was inhibited. HQD inhibited expression of Cyp1A2 and Cyp3A11 and increased the expression of P-gp and BCRP in normal mice. In DN mice, HQD induced expression of BCRP and inhibited expression of Cyp2C37, Cyp3A11, OCT2, MRP1, and MRP2. The activity of each Cyp450 enzyme was consistent with changes in expression. The changes in pharmacokinetic parameters of HQD in DN might, in part, be secondary to decreased expression of P-gp and BCRP. HQD varied in regulating transporter activities between health and disease. These findings support careful application of HQD-based treatment in DN, especially in combination with other drugs.

Investigation on Depression of College Students Majoring in Physical Education and Nonphysical Education: A StudyBased on the Age Region and Gender of 374 Students.

In the research on the relationship between depression and college students' major, there are some differences in the degree of depression between sports major and nonsports major students. Based on these results, we assume that there is the possibility of emotional differences between professional and nonprofessional sports. A total of 374 samples of students majoring in physical education and nonphysical education at the same university were analyzed by using the methods of literature review and data analysis. A total of 188 subjects, including 121 males and 253 females (186 majoring in sports and nonsports), were asked to fill in the SDS (Self-Rating Depression Scale). SDS is widely used in rough screening, emotional state evaluation, investigation, and scientific research of outpatients in clinical psychology departments. The research obtained the difference in depression degree in the whole sample and further compared the depression degree of students of different ages and native places. Statistical analysis was performed on all data using SPSS 23.0 software. Basic data description, paired chi-square analysis, and covariance analysis were used. The results show that in this sample, the maximum value (minimum/maximum value) of one item of the total depression score of nonphysical education students exceeds the average value by 3 standard deviations, and this shows that the general level of depression scores of non-PE majors is high; most non-PE majors are in mild depression, which is equal to the number of PE majors who are in a normal mood; and nonsports majors in cities are more likely to have mild depression.

Multivariate piecewise joint models with random change-points for skewed-longitudinal and survival data.

Methodological development and application of joint models for longitudinal and time-to-event data have mostly coupled a single longitudinal outcome-based linear mixed-effects model with normal distribution and Cox proportional hazards model. In practice, however, (i) profile of subject's longitudinal response may follow a `broken-stick nonlinear' (piecewise) trajectory. Such multiple phases are an important indicator to help quantify treatment effect, disease diagnosis and clinical decision-making. (ii) Normality in longitudinal models is a routine assumption, but it may be unrealistically obscuring important features of subject variations. (iii) Data collected are often featured by multivariate longitudinal outcomes which are significantly correlated, ignoring their correlation may lead to biased estimation. (iv) It is of importance to investigate how multivariate longitudinal outcomes are associated with event time of interest. In the article, driven by a motivating example, we propose Bayesian multivariate piecewise joint models with a skewed distribution and random change-points for longitudinal measures with an attempt to cope with correlated multivariate longitudinal data, adjust departures from normality, mediate accuracy from longitudinal trajectories with random change-point and tailor linkage in specifying a time-to-event process. A real example is analyzed to demonstrate methodology and simulation studies are conducted to evaluate performance of the proposed models and method.

Bayesian Joint Modeling of Multivariate Longitudinal and Survival Data With an Application to Diabetes Study.

Joint models of longitudinal and time-to-event data have received a lot of attention in epidemiological and clinical research under a linear mixed-effects model with the normal assumption for a single longitudinal outcome and Cox proportional hazards model. However, those model-based analyses may not provide robust inference when longitudinal measurements exhibit skewness and/or heavy tails. In addition, the data collected are often featured by multivariate longitudinal outcomes which are significantly correlated, and ignoring their correlation may lead to biased estimation. Under the umbrella of Bayesian inference, this article introduces multivariate joint (MVJ) models with a skewed distribution for multiple longitudinal exposures in an attempt to cope with correlated multiple longitudinal outcomes, adjust departures from normality, and tailor linkage in specifying a time-to-event process. We develop a Bayesian joint modeling approach to MVJ models that couples a multivariate linear mixed-effects (MLME) model with the skew-normal (SN) distribution and a Cox proportional hazards model. Our proposed models and method are evaluated by simulation studies and are applied to a real example from a diabetes study.

Release of the additive metals from 3 commonly used plastics during the degradation under the treatment of UV irradiation.

Additive metals are continuously released into the environment during the photo-degradation of plastics into microplastics, but this phenomenon has not been reported by many studies. Herein, we investigated the surface morphology changes along with the release of additive metals (Cr, Mn, Fe, Co, Cu, Zn, and Pb) during the degradation of three types of plastics, i.e., polypropylene (PP), polyethylene terephthalate (PET) and polyvinyl chloride (PVC), under UV light irradiation. FTIR results showed that 168 days of UV-irradiation led to the primary degradation of each plastic sample. The metal release could be found after 70 days UV-irradiation. The rate of metal release for the three plastics showed the following order: PP > PET ≈ PVC. In addition, the distribution and concentrations of the metals in the plastic could influence the release characteristics of each metal. Low release rate of Fe symbolized by the total metal release in the range of 4.28 ~10.27% as evident from the results of the primary degradation experiment, indicated the release of Fe occurring in the late stage of the plastic degradation or even in the microplastics-formation stage. As for the release of Co from PP, it was far lower than that of the other elements (0.35%), showing the same release characteristics as that of Fe. On the contrary, the release ratio of Pb from PP was 78.89% and was mainly concentrated in the early stage of the plastic degradation. The results help understanding the release behavior of the additive metals during the degradation of typical plastics under ultraviolet light irradiation.

Room temperature monitoring of SF6decomposition byproduct SO2F2based on TiO2/NiSO4composite nanofibers.

Sulfuryl fluoride (SO2F2) is one of the ideal decomposition components of sulfur hexafluoride (SF6), which is widely used as an insulating and arc extinguishing medium in gas-insulated switchgear. To detect the decomposition component of SF6at room temperature, the use of SO2F2is still a challenge. In this work, we have successfully fabricated TiO2nanofibers and nickel sulfate (NiSO4NPs) via simple electrospun and hydrothermal methods, followed by calcination process to improve the sensing performance. Metal oxide semiconductor materials (MOSs) are widely used in gas sensing applications due to their superior performance and fast recovery speed. Although the performance of our TiO2/NiSO4composite nanofiber sensor decreases at higher temperatures, it shows an excellent response to target gasses at room temperature. Ni-decoration on the outer surface of the nanofibers could maximize the sensing response of 100 ppm SO2F2by up to 189% at room temperature, showing that the TiO2/NiSO4composite nanofibers are 2.5 times superior to the pure TiO2nanofiber sensors. Thus, the approach for this novel composite nanofiber-based material is promising for the fabrication of superior gas sensors for decomposition of SF6.

Survival of Patients with Primary Cardiac Tumors in an 11-Year Single Center Study.

BACKGROUND: Primary cardiac tumors are rare, but few studies have examined the relationship between risk factors and the prognosis. The aim of this study was to provide a survival analysis and risk factors for mortality in patients with primary cardiac tumors. METHODS: We retrospectively enrolled 71 patients diagnosed with primary cardiac tumors from June 2006 to November 2017 in our hospital. Patients' population characteristics, treatment information, pathology, and follow-up data were obtained and analyzed. RESULTS: Of the 71 patients, 60 cases were benign, and 11 cases were malignant. Sex, age, New York Heart Association classification, the percentage of peripheral embolism, and surgery had no significant difference between benign and malignant groups (P >.05), but the percentage of arrhythmia, leg edema, and mortality rate was higher in the malignant tumor group than in the benign tumor group (P <.05). Compared with the benign tumor group, the percentage of biatrial lesions in the malignant tumor group was significantly higher (P <.05). Moreover, Independent risk factors included the treatment choice, pathology type, and number of tumor lesions (P <.05). CONCLUSION: Our study suggests that conservative therapy, malignant cardiac tumor, and biatrial tumor lesion are independent risk factors for poor prognosis.

New Insights into CO2 Adsorption on Layered Double Hydroxide (LDH)-Based Nanomaterials.

The interlamellar spacing of layered double hydroxides (LDHs) was enlarged by dodecyl sulfonate ions firstly, and then, (3-aminopropyl)triethoxysilane (APS) was chemically grafted (APS/LDHs). The structural characteristics and thermal stability of these prepared samples were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), reflectance Fourier transform infrared spectrometer (FTIR), thermogravimetric analysis (TG), and elemental analysis (EA) respectively. The CO2 adsorption performance was investigated adopting TG and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). The results presented that the CO2 adsorption capacity on APS/LDHs was as high as 90 mg/g and showed no obvious reduction during a five cyclic adsorption-desorption test, indicating its superior performance stability. The DRIFTS results showed that both carbamates and weakly bounded CO2 species were generated on APS/LDHs. The weakly adsorbed species was due to the different local chemical environment for CO2 capture provided by the surface moieties of LDHs like free silanol and hydrogen bonds.

Influence analysis for skew-normal semiparametric joint models of multivariate longitudinal and multivariate survival data.

The normality assumption of measurement error is a widely used distribution in joint models of longitudinal and survival data, but it may lead to unreasonable or even misleading results when longitudinal data reveal skewness feature. This paper proposes a new joint model for multivariate longitudinal and multivariate survival data by incorporating a nonparametric function into the trajectory function and hazard function and assuming that measurement errors in longitudinal measurement models follow a skew-normal distribution. A Monte Carlo Expectation-Maximization (EM) algorithm together with the penalized-splines technique and the Metropolis-Hastings algorithm within the Gibbs sampler is developed to estimate parameters and nonparametric functions in the considered joint models. Case deletion diagnostic measures are proposed to identify the potential influential observations, and an extended local influence method is presented to assess local influence of minor perturbations. Simulation studies and a real example from a clinical trial are presented to illustrate the proposed methodologies. Copyright © 2017 John Wiley & Sons, Ltd.

Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data.

This paper presents a novel semiparametric joint model for multivariate longitudinal and survival data (SJMLS) by relaxing the normality assumption of the longitudinal outcomes, leaving the baseline hazard functions unspecified and allowing the history of the longitudinal response having an effect on the risk of dropout. Using Bayesian penalized splines to approximate the unspecified baseline hazard function and combining the Gibbs sampler and the Metropolis-Hastings algorithm, we propose a Bayesian Lasso (BLasso) method to simultaneously estimate unknown parameters and select important covariates in SJMLS. Simulation studies are conducted to investigate the finite sample performance of the proposed techniques. An example from the International Breast Cancer Study Group (IBCSG) is used to illustrate the proposed methodologies.

Therapeutic Observation of Moxibustion plus Tuina for Early-stage Diabetic Foot / 上海针灸杂志

Objective To observe the clinical efficacy of moxibustion plus tuina in treating early-stage diabetic foot. Method Seventy patients with early-stage diabetic foot were randomized into a treatment group and a control group, 35 cases each. The control group was intervened by conventional medication, while the treatment group was additionally intervened by moxibustion plus tuina. After 2 treatment courses, the changes of ankle bronchial index (ABI) in the two groups were observed, and the clinical efficacies were compared. Result Patients in the treatment group showed significant improvement in symptoms, and the total effective rate was 96.9%. The total effective rate was 75.8% in the control group. The difference between the two groups was statistically significant (P<0.05). Conclusion Moxibustion plus tuina is safe and effective in treating diabetic foot. With significant Chinese medicine feature and acceptable to patients, this method is a good choice in treating early-stage diabetic foot.

[Effect of Electroacupunctrue on ERp57 in NAFLD Rats].

OBJECTIVE: To investigate the effect of electroacupunctrue on ERp57 in non-alcoholic fatty liver disease (NAFLD) rats, and study the therapeutic mechanism of electroacupunctrue in patients with NAFLD. METHODS: Sixty male SD rats were randomly divided into common diet group (n = 15) and high-fat diet group (n = 45). 5 weeks later, two rats from the two groups were executed and confirmed that the model was successful. Then 10 rats in common diet group were chosen as control group (Control), and 40 rats in high-fat diet group were randomly chosen and divided into diet group 1 (D1), diet group 2 (D2), electroacupuncture group 1 (EA) and electroacupuncture group 2 (EA2) (n = 10 each). D1 and EA1 were fed by high fat diet; D2 and EA2 were fed with common diet. In EA1 and EA2, filiform needle acupuncture was applied to ST36, SP6 and Liv3 and electroacupunctrue was applied to one-side of ST36, SP6 for 20 min once daily for 4 weeks. The rats in each group were weighed per-week. After the treatment the changes of blood lipid and liver functions of these rats were observed. ERp57 gene expression and protein expression were detected by RT-PCR and Western blot, and expression of ERp57 downstream SREBP-1c was detected. RESULTS: The body mass of D1 increased slowly and were lower than D2 and EA1 (P < 0.05); the body weights of EA2 increased rapidly and were higher than EA1 (P < 0.05), but without significant difference with D2 (P > 0.05). The contents of blood lipid, liver functions and the expression of ERp57 and SREBP-1c were significantly higher than those in Control, D2 and EA1 (P < 0.05). While compared to D2 and EA1 respectively, the index mentioned above in EA2 decreased more significantly (P < 0.05). CONCLUSION: Electroacupunctrue can decrease expression of ERp57 to improve endoplasmic reticulum stress (ERS) of rats with NAFLD and then decrease expression of SREBP-1c to regulate rat lipid, which could be one of mechanism to cure NAFLD.

Confidence intervals construction for difference of two means with incomplete correlated data.

BACKGROUND: Incomplete data often arise in various clinical trials such as crossover trials, equivalence trials, and pre and post-test comparative studies. Various methods have been developed to construct confidence interval (CI) of risk difference or risk ratio for incomplete paired binary data. But, there is little works done on incomplete continuous correlated data. To this end, this manuscript aims to develop several approaches to construct CI of the difference of two means for incomplete continuous correlated data. METHODS: Large sample method, hybrid method, simple Bootstrap-resampling method based on the maximum likelihood estimates (B 1) and Ekbohm's unbiased estimator (B 2), and percentile Bootstrap-resampling method based on the maximum likelihood estimates (B 3) and Ekbohm's unbiased estimator (B 4) are presented to construct CI of the difference of two means for incomplete continuous correlated data. Simulation studies are conducted to evaluate the performance of the proposed CIs in terms of empirical coverage probability, expected interval width, and mesial and distal non-coverage probabilities. RESULTS: Empirical results show that the Bootstrap-resampling-based CIs B 1, B 2, B 4 behave satisfactorily for small to moderate sample sizes in the sense that their coverage probabilities could be well controlled around the pre-specified nominal confidence level and the ratio of their mesial non-coverage probabilities to the non-coverage probabilities could be well controlled in the interval [0.4, 0.6]. CONCLUSIONS: If one would like a CI with the shortest interval width, the Bootstrap-resampling-based CIs B 1 is the optimal choice.

Confidence interval construction for the difference between two correlated proportions with missing observations.

Under the assumption of missing at random, eight confidence intervals (CIs) for the difference between two correlated proportions in the presence of incomplete paired binary data are constructed on the basis of the likelihood ratio statistic, the score statistic, the Wald-type statistic, the hybrid method incorporated with the Wilson score and Agresti-Coull (AC) intervals, and the Bootstrap-resampling method. Extensive simulation studies are conducted to evaluate the performance of the presented CIs in terms of coverage probability and expected interval width. Our empirical results evidence that the Wilson-score-based hybrid CI and the Wald-type CI together with the constrained maximum likelihood estimates perform well for small-to-moderate sample sizes in the sense that (i) their empirical coverage probabilities are quite close to the prespecified confidence level, (ii) their expected interval widths are shorter, and (iii) their ratios of the mesial non-coverage to non-coverage probabilities lie in interval [0.4, 0.6]. An example from a neurological study is used to illustrate the proposed methodologies.

[Effects of Electroacupunctrue Combined with Dietary Control on Peroxisome Proliferator-activa- ted Receptor-α, and Liver Fatty Acid-binding Protein Levels in Non-alcoholic Fatty Liver Disease Rats].

OBJECTIVE: To observe the effect of electroacupunctrue (EA) intervention or EA combined with dietary control on peroxisome proliferator-activated receptor (PPAR)-α, and liver fatty acid-binding protein (L-FABP) levels in non-alcoholic fatty liver disease (NAFLD) rats, so as to reveal its mechanism underlying improvement of NAFLD. METHODS: Sixty SD male rats were randomly divided into common diet (control) group (n = 10) and high-fat diet group (n = 45). The NAFLD model was established by feeding the animals with high-fat forage (HFF, including cholesterol, sodium cholate, propylthiouracil, sucrose, lard and common forage) for 5 weeks. Forty NAFLD rats were then randomized into model, EA + HFF, low-fat forage (LFF) and EA+ LFF groups (n = 10 rats in each group). EA (4 Hz/20 Hz, 3 mA) was applied to ipsilateral "Zusanli" (ST 36),"Sanyinjiao" (SP 6) and "Taichong" (LR 3) for 20 min, once daily for 4 weeks. The pathologic changes of the hepatic tissue were detected by H. E. staining. Serum total cholesterol (TC) and triglyceride (TG) contents were determined by using enzymatic methods, serum free fat acids (FFA) content was detected by colorimetry. The expression levels of PPAR-α and L-FABP protein and gene of the liver tissue were determined by Western blot and RT-PCR, respectively. RESULTS: H. E. staining showed that the hepatocytes presented moderate or severe bullous adipose degeneration in rats of the model group, vesicular steatosis in the EA + HFF and LFF groups, turned to almost normal but with small amount of lipid droplets in the EA + LFF group. The contents of serum TC, TG and FFA were significantly higher in the model group than in the control group (P < 0.05), and were obviously decreased in the EA + HFF, LFF and EA + LFF groups in comparison with the model group (P < 0.05). Compared to the control group, hepatic PPAR-α protein and mRNA were markedly down-regulated in the model group, and hepatic L-FABP protein and mRNA considerably up-regulated in the model group (P < 0.05). Following EA intervention and low fat diet feeding, PPAR-α protein and mRNA were markedly up-regulated while L-FABP protein and mRNA remarkably down-regulated in the EA + HFF, LFF and EA + LFF groups (P < 0.05). CONCLUSION: EA intervention or EA combined with dietary control can relieve hepatic pathological changes in NAFLD rats, which may be related to its effects in down-regulating blood lipid level and hepatic L-FABP protein and mRNA expression and in up-regulating PPAR-α protein and mRNA expression, and the effect of combined treatment was relatively better than simple EA or LFF treatment.

Investigation of Hexagonal Mesoporous Silica-Supported Composites for Trace Moisture Adsorption.

Moisture control is an important part of effective maintenance program for gas-insulated switchgear (GIS). Herein, hexagonal mesoporous silica (HMS) materials were synthesized by adopting dodecylamine as a structure directing agent, which was then employed as a host for supporting polyethylenimine (PEI) without further calcinations or extraction treatment. The physicochemical properties of the silica support and composites were characterized, and the moisture adsorption capacity of these composites was determined. The reserved template agents resulted in a dramatic improvement in moisture adsorption amount. Among them, 50PEI/DHMS showed the highest adsorption value. The enhanced adsorption could be attributed to the generated hydrogen bonding between amino groups and H2O molecules and the improved diffusion of moisture into the bulk networks of PEI polymers due to its better spatial dispersion imposed by the long alkyl chains of template agents, which was confirmed by thermogravimetry results and hydrogen efficiency analysis. Moreover, the maintained terminal amino groups of templates could also function as active sites for moisture adsorption. The results herein imply that the PEI/DHMS composites could be appealing materials for capturing moisture in GIS.