Dyadic effects of financial toxicity and social support on the fear of cancer recurrence in breast cancer patients and caregivers: an actor-partner interdependence mediation model.

PURPOSE: In this study, the actor-partner interdependence mediation model (APIMeM) was applied to breast cancer patients and their caregivers to assess the factors that affect the fear of cancer recurrence. In particular, the purpose of this study was to evaluate the mediating effect of social support on financial toxicity and the fear of cancer recurrence, providing an effective basis for developing plans to reduce the level of fear of cancer recurrence. METHODS: This study employed a cross-sectional design, and 405 dyads of breast cancer patients and their caregivers were enrolled. Financial toxicity, social support, and fear of cancer recurrence were assessed by computing comprehensive scores for financial toxicity based on patient-reported outcome measures, the Social Support Rating Scale, and the Fear of Cancer Recurrence Inventory Short Form, respectively. The data were analysed using SPSS 24.0 and AMOS 23.0. RESULTS: The results showed that the fear of cancer recurrence of breast cancer patients and their caregivers was significantly related to dyadic financial toxicity and social support. In addition, the financial toxicity of breast cancer patients and their caregivers had significant actor effects and partner effects on the fear of cancer recurrence through dyadic social support. CONCLUSIONS: The financial toxicity of breast cancer patients and their caregivers could produce actor and partner effects on the fear of cancer recurrence through the mediation of social support, which provided empirical support for improving reducing the level of fear of cancer recurrence among patients and caregivers at the dyadic level.

MediDRNet: Tackling category imbalance in diabetic retinopathy classification with dual-branch learning and prototypical contrastive learning.

BACKGROUND AND OBJECTIVE: The classification of diabetic retinopathy (DR) aims to utilize the implicit information in images for early diagnosis, to prevent and mitigate the further worsening of the condition. However, existing methods are often limited by the need to operate within large, annotated datasets to show significant advantages. Additionally, the number of samples for different categories within the dataset needs to be evenly distributed, because the characteristic of sample imbalance distribution can lead to an excessive focus on high-frequency disease categories, while neglecting the less common but equally important disease categories. Therefore, there is an urgent need to develop a new classification method that can effectively alleviate the issue of sample distribution imbalance, thereby enhancing the accuracy of diabetic retinopathy classification. METHODS: In this work, we propose MediDRNet, a dual-branch network model based on prototypical contrastive learning. This model adopts prototype contrastive learning, creating prototypes for different levels of lesions, ensuring they represent the core features of each lesion level. It classifies by comparing the similarity between data points and their category prototypes. Our dual-branch network structure effectively resolves the issue of category imbalance and improves classification accuracy by emphasizing subtle differences in retinal lesions. Moreover, our approach combines a dual-branch network with specific lesion-level prototypes for core feature representation and incorporates the convolutional block attention module for enhanced lesion feature identification. RESULTS: Our experiments using both the Kaggle and UWF classification datasets have demonstrated that MediDRNet exhibits exceptional performance compared to other advanced models in the industry, especially on the UWF DR classification dataset where it achieved state-of-the-art performance across all metrics. On the Kaggle DR classification dataset, it achieved the highest average classification accuracy (0.6327) and Macro-F1 score (0.6361). Particularly in the classification tasks for minority categories of diabetic retinopathy on the Kaggle dataset (Grades 1, 2, 3, and 4), the model reached high classification accuracies of 58.08%, 55.32%, 69.73%, and 90.21%, respectively. In the ablation study, the MediDRNet model proved to be more effective in feature extraction from diabetic retinal fundus images compared to other feature extraction methods. CONCLUSIONS: This study employed prototype contrastive learning and bidirectional branch learning strategies, successfully constructing a grading system for diabetic retinopathy lesions within imbalanced diabetic retinopathy datasets. Through a dual-branch network, the feature learning branch effectively facilitated a smooth transition of features from the grading network to the classification learning branch, accurately identifying minority sample categories. This method not only effectively resolved the issue of sample imbalance but also provided strong support for the precise grading and early diagnosis of diabetic retinopathy in clinical applications, showcasing exceptional performance in handling complex diabetic retinopathy datasets. Moreover, this research significantly improved the efficiency of prevention and management of disease progression in diabetic retinopathy patients within medical practice. We encourage the use and modification of our code, which is publicly accessible on GitHub: https://github.com/ReinforceLove/MediDRNet.

Soreness Reminds Me of Grief: Patients With Chronic Pain Show Less Differentiated Representations of Emotional Feelings and Bodily States.

People experience similarities between emotional feelings and bodily states on a daily basis, but both the magnitude and pervasiveness of this experiential similarity vary across individuals. Inspired by previous findings that chronic pain (CP) is characterized by strengthened pain-affect coupling and reduced interoceptive accuracy, we conducted 2 cross-sectional studies to examine whether patients with CP would exhibit less differentiated perception and mental representation of emotional feelings and bodily states. In study 1 (N = 500), patients with CP and healthy controls (HCs) completed a self-report questionnaire that asked explicitly about the perceived similarity between 5 basic emotion categories and a series of bodily states. In study 2 (N = 73), a specially designed false memory test was administered to examine whether patients with CP would have reduced differentiation of concepts of negative emotion and somatic distress. We found that patients with CP perceived greater and more pervasive similarities between emotional feelings and bodily states, as indicated by higher questionnaire scores and denser, less specialized bipartite emotion-body networks, both associated with lower subjective interoceptive accuracy. Furthermore, patients with CP formed false memories of negative emotion words (eg, grief) more readily than HCs after memorizing somatic distress words (eg, soreness), as if they represented negative emotion and somatic distress as a single, enmeshed semantic category. Our findings extend previous literature by demonstrating reduced discrimination between emotional and bodily experiences in CP that is not restricted to pain-related emotional and sensory experiences and may be related to a fundamentally less differentiated interoception. PERSPECTIVES: This study shows that patients with chronic pain have a profoundly less differentiated perception and implicit conceptualization of emotional feelings and bodily states, which appears to be associated with altered interoception. These findings may provide new perspectives on why they often experience a stronger pain-affect coupling.

Applications of nanomaterials in anti-VEGF treatment for ophthalmic diseases.

Angiogenesis has been determined to be essential in the occurrence and metastasis of diabetic retinopathy (DR), age-related macular degeneration (AMD), retinal vein occlusion (RVO), choroidal neovascularization (CNV), retinopathy of prematurity (ROP), tumor, etc. However, the clinical use of anti-vascular endothelial growth factors (VEGF) drugs is currently limited due to its high cost, potential side effects, and need for repeated injections. In recent years, nanotechnology has shown promising results in inhibiting neovascularization and reducing reactive oxygen species (ROS) or inflammatory factors. Some nanomaterials can also act as vehicles for drug delivery, such as lipid nanoparticles and PLGA. The process of angiogenesis and its molecular mechanism are discussed in this article. At the same time, this study aims to systematically review the research progress of nanotechnology and offer more treatment options for neovascularization-related diseases in clinical ophthalmology.

A new ultra-wide-field fundus dataset to diabetic retinopathy grading using hybrid preprocessing methods.

Diabetic retinopathy(DR) is a common early diabetic complication and one of the main causes of blindness. In clinical diagnosis and treatment, regular screening with fundus imaging is an effective way to prevent the development of DR. However, the regular fundus images used in most DR screening work have a small imaging range, narrow field of vision, and can not contain more complete lesion information, which leads to less ideal automatic DR grading results. In order to improve the accuracy of DR grading, we establish a dataset containing 101 ultra-wide-field(UWF) DR fundus images and propose a deep learning(DL) automatic classification method based on a new preprocessing method. The emerging UWF fundus images have the advantages of a large imaging range and wide field of vision and contain more information about the lesions. In data preprocessing, we design a data denoising method for UWF images and use data enhancement methods to improve their contrast and brightness to improve the classification effect. In order to verify the efficiency of our dataset and the effectiveness of our preprocessing method, we design a series of experiments including a variety of DL classification models. The experimental results show that we can achieve high classification accuracy by using only the backbone model. The most basic ResNet50 model reaches an average of classification accuracy(ACA) 0.66, Macro F1 0.6559, and Kappa 0.58. The best-performing Swin-S model reaches ACA 0.72, Macro F1 0.7018, and Kappa 0.65. DR grading using UWF images can achieve higher accuracy and efficiency, which has practical significance and value in clinical applications.

The mediating effects of coping styles on the relationship between trait mindfulness and romantic relationship satisfaction.

The purpose of the current study was to explore the influence of coping styles and trait mindfulness on the satisfaction of romantic relationships (RRS) among college students. Of the 305 participants, 258 (males: 115, 44.6%) had previously been in, or were presently in a romantic relationship. All participants completed the MAAS, CSQ, and questions about RRS. There was a significant meditating role of mature coping styles in the relationship between trait mindfulness and RRS (indirect effect [95% CI] = 0.021 [0.001, 0.052]). However, the mediating effect of immature coping styles was not significant (indirect effect [95% CI] = 0.038 [-0.020, 0.097]). Mature coping style plays an important mediating role in the relationship between mindfulness and relationship satisfaction.

The Relationship between Perfectionism and Social Anxiety: A Moderated Mediation Model.

Social anxiety is one of the mental health problems associated with perfectionism. The present study investigated the possible mediation of perceived stress in the relationship between perfectionism and social anxiety, and whether this mediation depends on the level of trait mindfulness. A total of 425 college students (female: 82.9%; mean age: M = 19.90 ± 1.06 years old) completed the Multidimensional Perfectionism Scale (MPS), the Chinese Perceived Stress Scale (CPSS), the Interaction Anxiousness Scale (IAS), and the Five-Facet Mindfulness Questionnaire (FFMQ). After controlling for age and gender, the moderated mediation analysis suggested that perfectionism significantly and positively predicted social anxiety and that perceived stress mediated the link between perfectionism and social anxiety. In addition, the indirect effect of perfectionism on social anxiety was moderated by trait mindfulness. Specifically, the indirect effect was weaker among the individuals with a high level of mindfulness compared to those with a low level of mindfulness. The findings of this study suggest that trait mindfulness significantly moderates the indirect effect of perfectionism on social anxiety via perceived stress.

Identification of 5 microRNA biomarkers associated with the prognosis of uveal melanoma.

To uncover the role of microRNAs in the occurrence and development of uveal melanoma (UM), we used R language packages in this study to analyze the correlations between the expression of microRNA isoforms, their target genes, and the clinical data for UM patients retrieved from The Cancer Genome Atlas (TCGA). We used Weighted Correlation Network Analysis (WGCNA) to divide the expression profiles of different microRNAs into 10 modules, among which blue and yellow modules were associated with UM survival. Hsa-miR-513a-5p, miR-506-3p, miR-508-3p, miR-140-3p, and miR-103a-2-5p were further identified as the top 5 node microRNAs based on the risk scores in both modules using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. After combining these 5 microRNAs into an integrated risk signature, the prognostic performance of the risk signature was evaluated by area under the receiver operating characteristic (AUROC) curve, and their association with UM clinical characteristics was further analyzed using multiple Cox regression. Our results showed that this risk signature was sensitivity and specificity, and could serve as an independent prognostic factor. In addition, Spearman correlation analysis showed that expression of almost all target mRNAs were significantly positively or negatively correlated with the associated microRNAs. The gene ontology (GO), pathways, and disease enrichment analyses also showed that these 5 microRNAs were closely related to the incidence and progression of tumor, indicating their potential for predicting the outcome of UM.

The Trend of 2D Transistors toward Integrated Circuits: Scaling Down and New Mechanisms.

2D transition metal chalcogenide (TMDC) materials, such as MoS2 , have recently attracted considerable research interest in the context of their use in ultrascaled devices owing to their excellent electronic properties. Microprocessors and neural network circuits based on MoS2 have been developed at a large scale but still do not have an advantage over silicon in terms of their integrated density. In this study, the current structures, contact engineering, and doping methods for 2D TMDC materials for the scaling-down process and performance optimization are reviewed. Devices are introduced according to a new mechanism to provide the comprehensive prospects for the use of MoS2 beyond the traditional complementary-metal-oxide semiconductor in order to summarize obstacles to the goal of developing high-density and low-power integrated circuits (ICs). Finally, prospects for the use of MoS2 in large-scale ICs from the perspectives of the material, system performance, and application to nonlogic functionalities such as sensor circuits and analogous circuits, are briefly analyzed. The latter issue is along the direction of "more than Moore" research.

The more mindfulness practice, the more post-trauma stress symptoms? Trait mindfulness and PTSS during the COVID-19 pandemic.

Investigating the contributing factors of post-traumatic stress symptoms (PTSS) has always been an important topic in the field of traumatic psychology research. The current study explored the influences of pandemic/epidemic experiences, meditation experiences, and trait mindfulness on PTSS and the mediating role of emotional resilience during the COVID-19 pandemic. A total of 522 participants in Hubei province completed the Five Facet Mindfulness Questionnaire, the Adolescents' Emotional Resilience Questionnaire, and the PTSD Checklist for DSM-5. The results showed that (1) participants who had family or friends diagnosed with COVID-19 scored higher on avoidance. (2) Participants who had family or friends had been diagnosed with SARS or H1N1 scored higher on PTSS. (3) Participants with meditation experience scored significantly higher on all dimensions of PTSS, other than avoidance. (4) The mediating role of recovering from negative emotions in the relationship between trait mindfulness and PTSS was significant (95%CI= [-0.212, -0.094]), while the generating positive emotion was not significant (95%CI= [-0.050, 0.071]). Individuals with pandemic/epidemic experience are more likely to have a high level of PTSS. Individuals who have meditation experience also express a higher level of PTSS, which may be a result of the quality of meditation. Trait mindfulness and the ability to recover from negative emotions were protective factors against PTSS.

Vertical MoS2 transistors with sub-1-nm gate lengths.

Ultra-scaled transistors are of interest in the development of next-generation electronic devices1-3. Although atomically thin molybdenum disulfide (MoS2) transistors have been reported4, the fabrication of devices with gate lengths below 1 nm has been challenging5. Here we demonstrate side-wall MoS2 transistors with an atomically thin channel and a physical gate length of sub-1 nm using the edge of a graphene layer as the gate electrode. The approach uses large-area graphene and MoS2 films grown by chemical vapour deposition for the fabrication of side-wall transistors on a 2-inch wafer. These devices have On/Off ratios up to 1.02 × 105 and subthreshold swing values down to 117 mV dec-1. Simulation results indicate that the MoS2 side-wall effective channel length approaches 0.34 nm in the On state and 4.54 nm in the Off state. This work can promote Moore's law of the scaling down of transistors for next-generation electronics.

A Bibliometric and Visualization Analysis of Mindfulness and Meditation Research from 1900 to 2021.

This study comprehensively summarizes research in the field of meditation, especially mindfulness meditation from 1900 to 2021, by analyzing the knowledge map through CiteSpace and VOSviewer software. Using "mindfulness *" or "meditation *" as the topic, articles included in the Science Citation Index Expanded and Social Sciences Citation Index were searched in the web of science core database, resulting in the selection of 19,752 articles. Over half a century ago, Deikman published the field's first article in the Journal of Nervous and Mental Disease in 1963, and publications have soared in subsequent decades. The USA is in the core position in terms of global collaboration, total publication numbers, and total citations. The Mindfulness journal ranked first for the most published articles and citations. "The benefits of being present: Mindfulness and its role in psychological well-being," written by Brown and Ryan, was the most cited article. Mindfulness, meditation, depression, intervention, stress reduction, stress, and anxiety are the top co-occurrence keywords. The timeline of cluster analysis discloses that before 2010, hypertension, cancer, mindfulness, generalized anxiety disorder, and other topics received great attention. In the decade since 2010, scholars have shown interest in meta-analysis, attention, and self-assessment, and keen attention to mindfulness-based interventions. These findings provide an important foundation to direct future research.

Ultrafast non-volatile flash memory based on van der Waals heterostructures.

Flash memory has become a ubiquitous solid-state memory device widely used in portable digital devices, computers and enterprise applications. The development of the information age has demanded improvements in memory speed and retention performance. Here we demonstrate an ultrafast non-volatile flash memory based on MoS2/hBN/multilayer graphene van der Waals heterostructures, which achieves an ultrafast writing/erasing speed of 20 ns through two-triangle-barrier modified Fowler-Nordheim tunnelling. Using detailed theoretical analysis and experimental verification, we postulate that a suitable barrier height, gate coupling ratio and clean interface are the main reasons for the breakthrough writing/erasing speed of our flash memory devices. Because of its non-volatility this ultrafast flash memory could provide the foundation for the next generation of high-speed non-volatile memory.

Xinmai 'an extract enhances the efficacy of sildenafil in the treatment of pulmonary arterial hypertension via inhibiting MAPK signalling pathway.

CONTEXT: Xinmai 'an tablet has been used to improve myocardial blood supply. Recently, some compounds from its formula have shown that they can treat pulmonary arterial hypertension (PAH). OBJECTIVE: This study investigates the effects of Xinmai 'an extract (XMA) on PAH and further tests the co-therapeutic enhancement with sildenafil (SIL). MATERIALS AND METHODS: Pulmonary artery smooth muscle cells were subjected to stimulation with SIL (12.5 µM) and XMA (250 µg/mL) for 48 h. Sprague-Dawley rats were randomly grouped into eight groups (n = 8 per group): (I) control group received saline; (II) MCT group received MCT (60 mg/kg); (III) SIL-Low group received MCT + SIL at 10 mg/kg/day; (IV) SIL-high group received MCT + SIL at 30 mg/kg/day; (V) XMA-High group received MCT + XMA at 251.6 mg/kg/day; (VI) SIL (Low)+XMA (Low) group received SIL (10 mg/kg) + XMA at 62.9 mg/kg/day; (VII) SIL (Low)+XMA (Medium) group received SIL (10 mg/kg) + XMA at 125.8 mg/kg/day; (VIII) SIL (Low)+XMA (High) group received SIL (10 mg/kg) + XMA at 251.6 mg/kg/day. Both XMA and SIL were given by gavage and were maintained daily for 2 weeks. RESULTS: XMA could improve SIL's efficacy in the treatment of PAH by decreasing cell viability more effectively at non-cytotoxic concentrations (250 µg/mL) and reducing Right Ventricular Systolic Pressure (RVSP) in PAH rat. Potential mechanisms might at least in part be through activating the MAPK signalling pathway. DISCUSSION AND CONCLUSIONS: The combination of XMA and SIL can improve the efficacy of pulmonary hypertension and reduce the dosage of SIL.

Numerical Analysis of a Continuous Vulcanization Line to Enhance CH4 Reduction in XLPE-Insulated Cables.

Herein, we apply a computational diffusion model based on Fick's law to study the manner in which a cable production line and its operating conditions can be enhanced to effectively reduce the CH4 concentration in cables insulated with cross-linked polyethylene (XLPE). Thus, we quantitatively analyze the effect of the conductor temperature, curing tube temperature distribution, transition zone length, and online relaxation on CH4 generation and transport during the production of 132 kV cables with an insulation thickness of 16.3 mm. Results show that the conductor temperature, which is initially controlled by a preheater, and the curing tube temperature distribution considerably affect the CH4 concentration in the cable because of their direct impact on the insulation temperature. The simulation results show 2.7% less CH4 remaining in the cable when the preheater is set at 160 °C compared with that when no preheater is used. To study the curing tube temperature distribution, we consider three distribution patterns across the curing tube: constant temperature and linear incremental and decremental temperature. The amount of CH4 remaining in the cable when the temperature was linearly increased from 300 to 400 °C was 1.6% and 3.7% lower than in the cases with a constant temperature at 350 °C and a linear temperature decrease from 400 to 300 °C, respectively. In addition, simulations demonstrate that the amount of CH4 removal from the cable can be increased up to 9.7% by applying an elongated and insulated transition zone, which extends the residence time for CH4 removal and decelerates the decrease in cable temperature. Finally, simulations show that the addition of the online relaxation section can reduce the CH4 concentration in the cable because the high cable temperature in this section facilitates CH4 removal up to 2.2%, and this effect becomes greater at low production speeds.

Numerical Study of CH4 Generation and Transport in XLPE-Insulated Cables in Continuous Vulcanization.

In this work, we apply a computational diffusion model based on Fick's laws to study the generation and transport of methane (CH 4 ) during the production of a cross-linked polyethylene (XLPE) insulated cable. The model takes into account the heating process in a curing tube where most of the cross-linking reaction occurs and the subsequent two-stage cooling process, with water and air as the cooling media. For the calculation of CH 4 generation, the model considers the effect of temperature on the cross-linking reaction selectivity. The cross-linking reaction selectivity is a measure of the preference of cumyloxy to proceed either with a hydrogen abstraction reaction, which produces cumyl alcohol, or with a ß -scission reaction, which produces acetophenone and CH 4 . The simulation results show that, during cable production, a significant amount of CH 4 is generated in the XLPE layer, which diffuses out of the cable and into the conductor part of the cable. Therefore, the diffusion pattern becomes a non-uniform radial distribution of CH 4 at the cable take-up point, which corresponds well with existing experimental data. Using the model, we perform a series of parametric studies to determine the effect of the cable production conditions, such as the curing temperature, line speed, and cooling water flow rate, on CH 4 generation and transport during cable production. The results show that the curing temperature has the largest impact on the amount of CH 4 generated and its distribution within the cable. We found that under similar curing and cooling conditions, varying the line speed induces a notable effect on the CH 4 transport within the cable, while the cooling water flow rate had no significant impact.

San-Huang-Tang protects obesity/diabetes induced NAFLD by upregulating PGC-1α/PEPCK signaling in obese and galr1 knockout mice models.

ETHNOPHARMACOLOGICAL RELEVANCE: San-Huang-Tang (ST), a classic prescription, has been clinically used to cure diabetes and diabetes-associated metabolic disorders. Established studies have reported that ST can alleviate inflammation, obesity, hyperglycemia and insulin resistance. AIM OF THE STUDY: To the best of our knowledge, here, we reported for the first time the underlying mechanistic therapeutic efficacy of the ST against nonalcoholic fatty liver disease (NAFLD) in high-fat induced obese and galr1-deficient diabetic mice. MATERIALS AND METHODS: The obese and galr1-deficient mice were treated with ST at a dose of 10 g/kg every day for three weeks. Then food intake, body weight and insulin resistance indexes were measured. Western blotting, qRT-PCR, and plasma biochemical analyses were applied. RESULTS: ST reduced food intake, body weight, blood glucose level and insulin resistance, improved glucose tolerance in obese and galr1-deficient mice. Mechanistically, we confirmed that ST protected against NAFLD through activation of PGC-1α and its downstream signaling pathways as shown by the attenuated hepatic adipogenesis and lipid accumulation, increased hepatic fatty acid oxidation, regulated plasma lipid parameters, and increased energy expenditure and metabolic function in fat and muscle. CONCLUSIONS: Reduction in food intake produced by ST may contribute to the observed metabolic effects. Our findings strongly suggest that ST might be a potential novel therapeutic drug against obesity/diabetes-induced NAFLD and other metabolic disorders.

Ambiguity Processing Bias Induced by Depressed Mood Is Associated with Diminished Pleasantness.

Depressed individuals are biased to perceive, interpret, and judge ambiguous cues in a negative/pessimistic manner. Depressed mood can induce and exacerbate these biases, but the underlying mechanisms are not fully understood. We theorize that depressed mood can bias ambiguity processing by altering one's subjective emotional feelings (e.g. pleasantness/unpleasantness) of the cues. This is because when there is limited objective information, individuals often rely on subjective feelings as a source of information for cognitive processing. To test this theory, three groups (induced depression vs. spontaneous depression vs. neutral) were tested in the Judgement Bias Task (JBT), a behavioral assay of ambiguity processing bias. Subjective pleasantness/unpleasantness of cues was measured by facial electromyography (EMG) from the zygomaticus major (ZM, "smiling") and from the corrugator supercilii (CS, "frowning") muscles. As predicted, induced sad mood (vs. neutral mood) yielded a negative bias with a magnitude comparable to that in a spontaneous depressed mood. The facial EMG data indicates that the negative judgement bias induced by depressed mood was associated with a decrease in ZM reactivity (i.e., diminished perceived pleasantness of cues). Our results suggest that depressed mood may bias ambiguity processing by affecting the reward system.

Baicalin ameliorates hepatic insulin resistance and gluconeogenic activity through inhibition of p38 MAPK/PGC-1α pathway.

BACKGROUND: Although the results of our and other studies show that baicalin can enhance glucose uptake and insulin sensitivity in skeletal muscle and adipocytes of mice, the specific metabolic contribution of baicalin on hepatic insulin resistance and gluconeogenic activity is still unclear. PURPOSE: The aim of this study is to investigate whether baicalin is involved in regulation of hepatic insulin resistance and gluconeogenic activity and its underlying mechanisms. STUDY DESIGN/METHODS: In the present study, high-fat diet-induced obese mice were given 50 mg/kg baicalin intraperitoneally (i.p.) once a day for 21 consecutive days, and hepatocytes were treated with baicalin (100 µM) or metformin (100 µM) in the presence of glucagon (200 nM) for 12 h. Then insulin resistance indexes and genes related to gluconeogenesis were examined in liver tissues. RESULTS: The present findings showed that baicalin decreased body weight, HOMA-IR, and alleviated high fat diet-induced glucose intolerance, hyperglycemia and insulin resistance in diet-induced obese mice. Furthermore, baicalin markedly suppressed p-p38 MAPK, p-CREB, FoxO1, PGC-1α, PEPCK and G6Pase expression in liver of obese mice and hepatocytes. Moreover, inhibition of gluconeogenic genes by baicalin was also strengthened by p38MAPK inhibitor in hepatocytes. CONCLUSION: Baicalin suppressed expression of PGC-1α and gluconeogenic genes, and reduced glucose production in high-fat diet-induced obese mice. Baicalin ameliorated hepatic insulin resistance and gluconeogenic activity mainly through inhibition of p38 MAPK/PGC-1α signal pathway. This study provides a possibility of using baicalin to treat hyperglycemia and hepatic insulin resistance in clinic.

Controlling Factors of Degassing in Crosslinked Polyethylene Insulated Cables.

Here, we analyze the degassing process of a byproduct (methane) formed during the peroxide-induced crosslinking of polyethylene. A diffusion model based on Fick's law is used to obtain the controlling factors of degassing in a crosslinked polyethylene (XLPE) insulated power cable (132 kV with 18 mm of insulation). We quantitatively analyze different scenarios of the diffusion of methane through the XLPE insulation and two semiconductor layers under various in situ degassing conditions. The analyzed degassing conditions include heat transfer and its effect on the diffusion properties, the different transport and boundary conditions due to the free spaces within the cable conductor, and the nonuniform distribution of methane concentrations within the insulation layers. Our simulation results clearly demonstrate that the free spaces between the copper strands in the cable conductor significantly affect the degassing efficiency. However, the temperature-diffusion coupling has a relatively minor effect on the overall degassing efficiency due to the rapid temperature increase of the polymer layers during the initial stages of degassing. Moreover, we find that the nonuniform distribution of methane in the initial stages also plays an important role in degassing in the cable, but this effect varies significantly during the degassing process.