Energy expenditure of type-specific sedentary behaviors estimated using sensewear mini armband: a metabolic chamber validation study among adolescents

SenseWear Mini Armband, an accelerometer with multiple physiological sensors, could be a practical means to estimate energy expenditure (EE) of children and adolescents, but its validity reported for these age groups has not been consistent within the literature. EE of twenty-six healthy Chinese 12-year-old adolescents was measured simultaneously using both SenseWear Mini Armband (SWMA) and metabolic chamber (MC) during a 16-hour stay in a MC. SWMA systematically underestimated the adolescents’ EE during sedentary behaviors, resting metabolic rate (RMR), basal metabolic rate (BMR), and total EE, with the absolute error rate ranging from 14.85% to 28.65%. The SWMA significantly underestimated EE compared with MC in Chinese adolescents. However, the amount of error can be reduced by applying correction equation proposed in this study

OR-009 The expression and roles of lncRNAs in the regeneration of skeletal muscle contusion

Objective In recent years, Accumulating evidence from myoblast differentiation in vitro, cardiotoxin (CTX)-mediated injury or mdx mice suggested that some lncRNAs such as Malat1, H19, linc-MD1, linc-YY1, Sirt1 AS and lnc-mg may modulate myogenesis and muscle regeneration. However, the change of lncRNAs in skeletal muscle contusion and their possible roles are still unclear. We hypothesize that the lncRNAs may be involved in the repair of skeletal muscle contusion. Methods Forty C57BL/6 male mice were randomly divided into two groups, uninjured control group (group C) and muscle contusion group (group S). The mice of group S suffered from contusion injury. All the mice were killed to harvest gastrocnemius at 3, 6, 12 and 24 days post-injury. The gene expression were detected by PCR technique. Gastrocnemius were stained with H & E to evaluate the general morphology. Data were analyzed by One-way analysis of variance, with statistical significance being set at p ≤ 0.05. Results The expression levels of linc-MD1 and Sirt1 AS were significantly higher than that of the uninjured control group at 3, 6 and 12 days post-injury (p<0.01). And Malat1 was highly expressed in the skeletal muscle of the muscle contusion group at 3 days post-injury and continuously up-regulated at 6 days (p<0.01). Moreover, linc-YY1 and H19 were all elevated significantly at 6 days (all p<0.01), but their gene expression levels did not change significantly at 3, 12 and 24 days post-injury, as compared to the uninjured control group. Furthermore, lnc-mg mRNA level did not change significantly in the whole process of regeneration after muscle contusion except the time point of 12 days post-injury which decreased significantly (p<0.01). The expression of myogenic regulatory factors (MyoD, myogenin, myf5, myf6) were studied, they were all elevated significantly at 3 and 6 days (all p<0.01; except myogenin ), and returned to normal at 24 days post-injury, as compared to the uninjured control group. Meanwhile, Pearson correlations showed that there was an correlation between lincRNAs and myogenic regulatory factors mentioned above. Conclusions The expression of myogenic regulatory factors increased significantly after muscle contusion. Meanwhile, varieties of lncRNAs (Malat1, H19, lnc-mg, linc-MD1, linc-YY1, Sirt1 AS) were also up-regulated. Moreover, there was correlation between lncRNAs and myogenic regulatory factors for skeletal muscle regeneration. These results suggest that lncRNAs may play important roles in the regeneration of skeletal muscle contusion

Identifying complementary and alternative medicine recommendations for insomnia treatment and care : a systematic review and critical assessment of comprehensive clinical practice guidelines

Background: There is a need for evidence-informed guidance on the use of complementary and alternative medicine (CAM) for insomnia because of its widespread utilization and a lack of guidance on the balance of benefits and harms. This systematic review aimed to identify and summarize the CAM recommendations associated with insomnia treatment and care from existing comprehensive clinical practice guidelines (CPGs). The quality of the eligible guidelines was appraised to assess the credibility of these recommendations. Methods: Formally published CPGs incorporating CAM recommendations for insomnia management were searched for in seven databases from their inception to January 2023. The NCCIH website and six websites of international guideline developing institutions were also retrieved. The methodological and reporting quality of each included guideline was appraised using the AGREE II instrument and RIGHT statement, respectively. Results: Seventeen eligible GCPs were included, and 14 were judged to be of moderate to high methodological and reporting quality. The reporting rate of eligible CPGs ranged from 42.9 to 97.1%. Twenty-two CAM modalities were implicated, involving nutritional or natural products, physical CAM, psychological CAM, homeopathy, aromatherapy, and mindful movements. Recommendations for these modalities were mostly unclear, unambiguous, uncertain, or conflicting. Logically explained graded recommendations supporting the CAM use in the treatment and/or care of insomnia were scarce, with bibliotherapy, Tai Chi, Yoga, and auriculotherapy positively recommended based on little and weak evidence. The only consensus was that four phytotherapeutics including valerian, chamomile, kava, and aromatherapy were not recommended for insomnia management because of risk profile and/or limited benefits. Conclusions: Existing guidelines are generally limited in providing clear, evidence-informed recommendations for the use of CAM therapies for insomnia management due to a lack of high-quality evidence and multidisciplinary consultation in CPG development. More well-designed studies to provide reliable clinical evidence are therefore urgently needed. Allowing the engagement of a range of interdisciplinary stakeholders in future updates of CPGs is also warranted. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=369155, identifier: CRD42022369155. Copyright © 2023 Zhao, Xu, Kennedy, Conduit, Zhang, Wang, Fu and Zheng

BMSC Transplantation Aggravates Inflammation, Oxidative Stress, and Fibrosis and Impairs Skeletal Muscle Regeneration

Skeletal muscle contusion is one of the most common muscle injuries in sports medicine and traumatology. Bone marrow mesenchymal stem cell (BMSC) transplantation has been proposed as a promising strategy to promote skeletal muscle regeneration. However, the roles and underlying mechanisms of BMSCs in the regulation of skeletal muscle regeneration are still not completely clear. Here, we investigated the role of BMSC transplantation after muscle contusion. BMSCs were immediately transplanted into gastrocnemius muscles (GMs) following direct contusion. Comprehensive morphological and genetic analyses were performed after BMSC transplantation. BMSC transplantation exacerbated muscle fibrosis and inflammation, as evidenced by increased leukocyte and macrophage infiltration, increased inflammatory cytokines and chemokines, and increased matrix metalloproteinases. BMSC transplantation also increased muscle oxidative stress. Overall, BMSC transplantation aggravated inflammation, oxidative stress and fibrosis and impaired skeletal muscle regeneration. These results, shed new light on the role of BMSCs in regenerative medicine and indicate that caution is needed in the application of BMSCs for muscle injury

A capsule network-based method for identifying transcription factors

Transcription factors (TFs) are typical regulators for gene expression and play versatile roles in cellular processes. Since it is time-consuming, costly, and labor-intensive to detect it by using physical methods, it is desired to develop a computational method to detect TFs. Here, we presented a capsule network-based method for identifying TFs. This method is an end-to-end deep learning method, consisting mainly of an embedding layer, bidirectional long short-term memory (LSTM) layer, capsule network layer, and three fully connected layers. The presented method obtained an accuracy of 0.8820, being superior to the state-of-the-art methods. These empirical experiments showed that the inclusion of the capsule network promoted great performances and that the capsule network-based representation was superior to the property-based representation for distinguishing between TFs and non-TFs. We also implemented the presented method into a user-friendly web server, which is freely available at http://www.biolscience.cn/Capsule_TF/ for all scientific researchers

Flexoelectricity-stabilized ferroelectric phase with enhanced reliability in ultrathin La:HfO2 films

Doped HfO2 thin films exhibit robust ferroelectric properties even for nanometric thicknesses, are compatible with current Si technology and thus have great potential for the revival of integrated ferroelectrics. Phase control and reliability are core issues for their applications. Here we show that, in (111)-oriented 5%La:HfO2 (HLO) epitaxial thin films deposited on (La0.3Sr0.7)(Al0.65Ta0.35)O3 substrates, the flexoelectric effect, arising from the strain gradient along the films normal, induces a rhombohedral distortion in the otherwise Pca21 orthorhombic structure. Density functional calculations reveal that the distorted structure is indeed more stable than the pure Pca21 structure, when applying an electric field mimicking the flexoelectric field. This rhombohedral distortion greatly improves the fatigue endurance of HLO thin films by further stabilizing the metastable ferroelectric phase against the transition to the thermodynamically stable non-polar monoclinic phase during repetitive cycling. Our results demonstrate that the flexoelectric effect, though negligibly weak in bulk, is crucial to optimize the structure and properties of doped HfO2 thin films with nanometric thicknesses for integrated ferroelectric applications

Strain-restricted transfer of ferromagnetic electrodes for constructing reproducibly superior-quality spintronic devices

Spintronic device is the fundamental platform for spin-related academic and practical studies. However, conventional techniques with energetic deposition or boorish transfer of ferromagnetic metal inevitably introduce uncontrollable damage and undesired contamination in various spin-transport-channel materials, leading to partially attenuated and widely distributed spintronic device performances. These issues will eventually confuse the conclusions of academic studies and limit the practical applications of spintronics. Here we propose a polymer-assistant strain-restricted transfer technique that allows perfectly transferring the pre-patterned ferromagnetic electrodes onto channel materials without any damage and change on the properties of magnetism, interface, and channel. This technique is found productive for pursuing superior-quality spintronic devices with high controllability and reproducibility. It can also apply to various-kind (organic, inorganic, organic-inorganic hybrid, or carbon-based) and diverse-morphology (smooth, rough, even discontinuous) channel materials. This technique can be very useful for reliable device construction and will facilitate the technological transition of spintronic study

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction

Abstract Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer numerical mapping and accumulated amino acid frequency as initial representation of non-classical HLA binder sequence. The deep learning module was used to further refine high-level representations. The deep learning module comprised two parallel convolutional neural networks, each followed by maximum pooling layer, dropout layer, and bi-directional long short-term memory network. The experimental results showed that the DeepHLAPred reached the state-of-the-art performanceson the cross-validation test and the independent test. The extensive test demonstrated the rationality of the DeepHLAPred. We further analyzed sequence pattern of non-classical HLA class I binders by information entropy. The information entropy of non-classical HLA binder sequence implied sequence pattern to a certain extent. In addition, we have developed a user-friendly webserver for convenient use, which is available at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful to detect non-classical HLA Class I binder. The source code and data is available at https://github.com/tangxingyu0/DeepHLApred

Disulfidptosis: a new target for metabolic cancer therapy

Abstract Altered metabolism is a hallmark of cancer and presents a vulnerability that can be exploited in cancer treatment. Regulated cell death (RCD) plays a crucial role in cancer metabolic therapy. A recent study has identified a new metabolic-related RCD known as disulfidptosis. Preclinical findings suggest that metabolic therapy using glucose transporter (GLUT) inhibitors can trigger disulfidptosis and inhibit cancer growth. In this review, we summarize the specific mechanisms underlying disulfidptosis and outline potential future research directions. We also discuss the challenges that may arise in the clinical translation of disulfidptosis research