The smallest Schwarzite carbon with only heptagonal carbon rings.

Carbon materials with full sp2-hybridized buckling is a major challenge pervading fundamental nanoscience and nanotechnology research. Carbon atoms that are sp2 hybridized prefer to form hexagonal rings, such as in carbon nanotubes and graphene, which are low-dimensional materials. The incorporation of heptagonal, octagonal, and/or larger rings into a hexagonal sp2 carbon meshwork has been identified as a strategy for assembling three-dimensional (3D) sp2 carbon crystals, and one of the typical representatives are Schwarzite carbons, which possess a negative surface Gaussian curvature as well as unique physical properties. Herein, a 3D Schwarzite carbon consisting of only sp2-buckled heptagonal carbon rings, which is referred to as Hepta-carbon, is proposed based on first-principles calculations. Hepta-carbon is mechanically and thermodynamically stable, and energetically more favourable than experimental graphdiyne, fullerene C20 and most Schwarzite carbons under ambient conditions. Molecular dynamics simulations indicate that Hepta-carbon exhibits high-temperature thermostability up to 1500 K. Band structure and mechanical property simulations indicate that Hepta-carbon is a semi-metallic material with electron conduction and exhibits impressive mechanical properties such as high strength with quasi-isotropy, high incompressibility similar to diamonds, elastic deformation behaviour under uniaxial stress, and high ductility. Hepta-carbon presents a porous network with a low mass density of 1.84 g cm-3 and connected channels with diameters of 3.3-6.1 Å. Theoretical simulations of gas adsorption energy demonstrate that Hepta-carbon can effectively adsorb and stabilize greenhouse gases, including N2O, CO2, CH4, and SF6.

Impact of specific electromagnetic radiation on wakefulness in mice.

Electromagnetic radiation (EMR) in the environment, particularly in the microwave range, may constitute a public health concern. Exposure to 2.4 GHz EMR modulated by 100 Hz square pulses was recently reported to markedly increase wakefulness in mice. Here, we demonstrate that a similar wakefulness increase can be induced by the modulation frequency of 1,000 Hz, but not 10 Hz. In contrast to the carrier frequency of 2.4 GHz, 935 MHz EMR of the same power density has little impact on wakefulness irrespective of modulation frequency. Notably, the replacement of the 100 Hz square-pulsed modulation by sinusoidal-pulsed modulation of 2.4 GHz EMR still allows a marked increase of wakefulness. In contrast, continuous sinusoidal amplitude modulation of 100 Hz with the same time-averaged power output fails to trigger any detectable change of wakefulness. Therefore, alteration of sleep behavior by EMR depends upon not just carrier frequency but also frequency and mode of the modulation. These results implicate biological sensing mechanisms for specific EMR in animals.

Evaluation of ecotourism suitability based on AHP-GIS: Taking Xiaoxiangling area of the Giant Panda National Park and the surrounding communities as an example.

The primary goal of national parks is to protect ecological environment, but also with the functions of scientific research, education, and recreation. Aiming for the realization of universal sharing, we used the analytic hierarchy process (AHP) to construct an ecotourism suitability evaluation system by selecting four factors, including landscape resources, ecological environment carrying capacity, recreation utilization capacity and social condition, taking Xiaoxiangling area of Giant Panda National Park and the surrounding communities as an example. We evaluated the ecotourism suitability based on GIS, and conducted a questionnaire survey of tourists, to propose suggestions on the functional zoning in terms of ecotourism suitability and subjective choice preferences of tourists. The results showed that the ecotourism suitability of the evaluation area could be classified into five levels. The most suitable areas were located nearby the natural landscape resources and far away from the core conservation area, and the least suitable areas distributed at the edge of the core conservation area. According to the results of suitability analysis, the evaluation area was divided into suitable development area, moderate development area, and restricted development area. Combined with the tourist preferences, we divided the recreational activities in the evaluation area into seven activities, namely, ecotourism, eco-camping, science education, leisure vacation, agricultural and animal husbandry culture experience, eco-education, and mountain adventure. These findings could help provide suitable services for different tourists and offer reference for the ecotourism developmental planning of the Xiaoxiangling area of the Giant Panda National Park.

Therapeutic robots for post-stroke rehabilitation.

Stroke is a prevalent, severe, and disabling health-care issue on a global scale, inevitably leading to motor and cognitive deficits. It has become one of the most significant challenges in China, resulting in substantial social and economic burdens. In addition to the medication and surgical interventions during the acute phase, rehabilitation treatment plays a crucial role in stroke care. Robotic technology takes distinct advantages over traditional physical therapy, occupational therapy, and speech therapy, and is increasingly gaining popularity in post-stroke rehabilitation. The use of rehabilitation robots not only alleviates the workload of healthcare professionals but also enhances the prognosis for specific stroke patients. This review presents a concise overview of the application of therapeutic robots in post-stroke rehabilitation, with particular emphasis on the recovery of motor and cognitive function.

Interactions between electromagnetic radiation and biological systems.

Even though the bioeffects of electromagnetic radiation (EMR) have been extensively investigated during the past several decades, our understandings of the bioeffects of EMR and the mechanisms of the interactions between the biological systems and the EMRs are still far from satisfactory. In this article, we introduce and summarize the consensus, controversy, limitations, and unsolved issues. The published works have investigated the EMR effects on different biological systems including humans, animals, cells, and biochemical reactions. Alternative methodologies also include dielectric spectroscopy, detection of bioelectromagnetic emissions, and theoretical predictions. In many studies, the thermal effects of the EMR are not properly controlled or considered. The frequency of the EMR investigated is limited to the commonly used bands, particularly the frequencies of the power line and the wireless communications; far fewer studies were performed for other EMR frequencies. In addition, the bioeffects of the complex EM environment were rarely discussed. In summary, our understanding of the bioeffects of the EMR is quite restrictive and further investigations are needed to answer the unsolved questions.

Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset.

Accelerated brain aging (ABA) intricately links with age-associated neurodegenerative and neuropsychiatric diseases, emphasizing the critical need for a nuanced exploration of heterogeneous ABA patterns. This investigation leveraged data from the UK Biobank (UKB) for a comprehensive analysis, utilizing structural magnetic resonance imaging (sMRI), diffusion magnetic resonance imaging (dMRI), and resting-state functional magnetic resonance imaging (rsfMRI) from 31,621 participants. Pre-processing employed tools from the FMRIB Software Library (FSL, version 5.0.10), FreeSurfer, DTIFIT, and MELODIC, seamlessly integrated into the UKB imaging processing pipeline. The Lasso algorithm was employed for brain-age prediction, utilizing derived phenotypes obtained from brain imaging data. Subpopulations of accelerated brain aging (ABA) and resilient brain aging (RBA) were delineated based on the error between actual age and predicted brain age. The ABA subgroup comprised 1949 subjects (experimental group), while the RBA subgroup comprised 3203 subjects (control group). Semi-supervised heterogeneity through discriminant analysis (HYDRA) refined and characterized the ABA subgroups based on distinctive neuroimaging features. HYDRA systematically stratified ABA subjects into three subtypes: SubGroup 2 exhibited extensive gray-matter atrophy, distinctive white-matter patterns, and unique connectivity features, displaying lower cognitive performance; SubGroup 3 demonstrated minimal atrophy, superior cognitive performance, and higher physical activity; and SubGroup 1 occupied an intermediate position. This investigation underscores pronounced structural and functional heterogeneity in ABA, revealing three subtypes and paving the way for personalized neuroprotective treatments for age-related neurological, neuropsychiatric, and neurodegenerative diseases.

A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis.

Alzheimer's disease (AD) is a complex form of dementia and due to its high phenotypic variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial role in AD diagnosis and monitoring, but interpreting these biomarkers can be problematic due to their spatial and temporal heterogeneity. Therefore, researchers are increasingly turning to imaging-based biomarkers that employ data-driven computational approaches to examine the heterogeneity of AD. In this comprehensive review article, we aim to provide health professionals with a comprehensive view of past applications of data-driven computational approaches in studying AD heterogeneity and planning future research directions. We first define and offer basic insights into different categories of heterogeneity analysis, including spatial heterogeneity, temporal heterogeneity, and spatial-temporal heterogeneity. Then, we scrutinize 22 articles relating to spatial heterogeneity, 14 articles relating to temporal heterogeneity, and five articles relating to spatial-temporal heterogeneity, highlighting the strengths and limitations of these strategies. Furthermore, we discuss the importance of understanding spatial heterogeneity in AD subtypes and their clinical manifestations, biomarkers for abnormal orderings and AD stages, the recent advancements in spatial-temporal heterogeneity analysis for AD, and the emerging role of omics data integration in advancing personalized diagnosis and treatment for AD patients. By emphasizing the significance of understanding AD heterogeneity, we hope to stimulate further research in this field to facilitate the development of personalized interventions for AD patients.

Biotransformation of anabolic androgenic steroids in human skin cells.

In comparison to well-known drug-metabolizing organs such as the liver, the metabolic capacity of human skin is still not well elucidated despite the widespread use of topical drug application. To gain a comprehensive insight into anabolic steroid metabolism in the skin, six structurally related anabolic androgenic steroids, testosterone, metandienone, methyltestosterone, clostebol, dehydrochloromethyltestosterone, and methylclostebol, were applied to human keratinocytes and fibroblasts derived from the juvenile foreskin. Phase I metabolites obtained from incubation media were analyzed by gas chromatography-mass spectrometry. The 5α-reductase activity was predominant in the metabolic pathways as supported by the detection of 5α-reduced metabolites after incubation of testosterone, methyltestosterone, clostebol, and methylclostebol. Additionally, the stereochemistry structures of fully reduced metabolites (4α,5α-isomers) of clostebol and methylclostebol were newly confirmed in this study by the help of inhouse synthesized reference materials. The results provide insights into the steroid metabolism in human skin cells with respect to the characteristics of the chemical structures.

Effects of Different Proportions of Amaranthus hypochondriacus Stem and Leaf Powder Inclusions on Growth Performance, Carcass Traits, and Blood Biochemical Parameters of Broilers.

This experiment aimed to study the effects of different proportions of Amaranthus hypochondriacus stem and leaf powder (AHSL) on the growth performance, apparent nutrient digestibility, carcass traits, meat quality, and blood biochemical parameters of broilers from day 1 to day 42. The experiment utilized a single-factor experimental design, with a total of 216 one-day-old male broilers (Ross 308) randomly assigned to three dietary treatment groups (eight replicate cages of nine birds per cage). The dietary treatments included a control diet, a 3% AHSL diet and a 6% AHSL diet for days 0-21. Then, the 3% and 6% AHSL diets were changed to 5% and 10% AHSL for days 22-42. The results showed that the inclusion levels of AHSL did not affect growth performance, carcass traits, or meat quality on days 21 and 42 (p > 0.05). However, the inclusion levels of AHSL decreased the apparent nutrient digestibility (AND) of dry matter (DM) (p ˂ 0.001) and neutral detergent fiber (NDF) (p ˂ 0.001) and increased the serum concentration of phosphorus (p ˂ 0.001) on day 21. On day 42, the inclusion levels of AHSL decreased the AND of DM (p = 0.025) and NDF content (p ˂ 0.001), but increased the AND of crude protein (CP) (p = 0.004). In particular, the diet containing 10% AHSL significantly increased the serum enzyme activity of alkaline phosphatase (ALP) (p = 0.046) and the serum concentration of total protein (TP) (p ˂ 0.001) on day 42. Overall, AHSL can be used as a new and effective feed ingredient in broiler diets. It can replace part of the corn-soybean meal diet without any adverse effects, which is beneficial for conserving feed resources. Additionally, AHSL can be included at a level of up to 10% during the broiler growth period.

MET fusions and splicing variants is a strong adverse prognostic factor in astrocytoma, isocitrate dehydrogenase mutant.

Liu et al. describe the adverse prognostic role of MET fusions and splicing variants in astrocytoma, isocitrate dehydrogenase mutant. On this basis, MET fusions and splicing variants was suggested to be a biomarker for the diagnosis of high-grade astrocytoma, isocitrate dehydrogenase mutant.

The value of multimodality MR in T staging evaluation after neoadjuvant therapy for rectal cancer.

BACKGROUND: Surgery is the preferred treatment for rectal cancer, but surgical treatment alone sometimes does not achieve satisfactory results. OBJECTIVE: To explore the value of multimodal Magnetic Resonance (MR) images in evaluating T staging of rectal cancer after neoadjuvant therapy and to compare and analyze with pathological results. METHODS: This study retrospectively analyzed 232 patients with stage T3, T4 rectal cancer between January 1, 2017 and October 31, 2022. MR examination was performed within 3 days before surgery. Different MR sequences were used for mrT staging of rectal cancer after neoadjuvant therapy and compared with pathological pT staging. The accuracy of different MR sequences in evaluating T staging of rectal cancer was calculated, and the consistency between the two was analyzed by kappa test. The sensitivity, specificity, negative predictive value and positive predictive value of different MR sequences in evaluating rectal cancer invading mesorectal fascia after neoadjuvant therapy were calculated. RESULTS: A total of 232 patients with rectal cancer were included in the study. The accuracy of high-resolution T2 WI in evaluating T staging of rectal cancer after neoadjuvant therapy was 49.57%, and the Kappa value was 0.261. The accuracy of high-resolution T2WI combined with diffusion weighted imaging (DWI) in evaluating T staging of rectal cancer after neoadjuvant therapy was 61.64%, and the Kappa value was 0.411. The accuracy of high-resolution combined with DCE-MR images in evaluating T staging of rectal cancer after neoadjuvant therapy was 80.60%, and the Kappa value was 0.706. The sensitivity and specificity of high-resolution t2-weighted imaging (HR-T2WI) combined with dynamic contrast-enhancement magnetic resonance (DCE-MR) in evaluating the invasion of mesorectal fascia were 83.46% and 95.33%, respectively. CONCLUSION: Compared with HR-T2WI combined with DWI images for mrT staging of rectal cancer after neoadjuvant chemoradiotherapy (N-CRT), HR-T2WI combined with DCE-M has the highest accuracy in evaluating mrT staging of rectal cancer after neoadjuvant therapy (80.60%), and has a high consistency with pathological pT staging. It is the best sequence for T staging of rectal cancer after neoadjuvant therapy. At the same time, the sequence has high sensitivity and specificity in evaluating mesorectal fascia invasion, which can provide accurate perioperative information for the formulation of surgical plan.

Expression and Activity of the Transcription Factor CCAAT/Enhancer-Binding Protein ß (C/EBPß) Is Regulated by Specific Pulse-Modulated Radio Frequencies in Oligodendroglial Cells.

The rapid growth of wireless electronic devices has raised concerns about the harmful effects of leaked electromagnetic radiation (EMR) on human health. Even though numerous studies have been carried out to explore the biological effects of EMR, no clear conclusions have been drawn about the effect of radio frequency (RF) EMR on oligodendrocytes. To this end, we exposed oligodendroglia and three other types of brain cells to 2.4 GHz EMR for 6 or 48 h at an average input power of 1 W in either a continuous wave (CW-RF) or a pulse-modulated wave (PW-RF, 50 Hz pulse frequency, 1/3 duty cycle) pattern. RNA sequencing, RT-qPCR, and Western blot were used to examine the expression of C/EBPß and its related genes. Multiple reaction monitoring (MRM) was used to examine the levels of expression of C/EBPß-interacting proteins. Our results showed that PW-RF EMR significantly increased the mRNA level of C/EBPß in oligodendroglia but not in other types of cells. In addition, the expression of three isoforms and several interacting proteins and targeted genes of C/EBPß were markedly changed after 6-h PW-RF but not CW-RF. Our results indicated that RF EMR regulated the expression and functions of C/EBPß in a waveform- and cell-type-dependent manner.

An alternative extension of telomeres related prognostic model to predict survival in lower grade glioma.

OBJECTIVE: The alternative extension of the telomeres (ALT) mechanism is activated in lower grade glioma (LGG), but the role of the ALT mechanism has not been well discussed. The primary purpose was to demonstrate the significance of the ALT mechanism in prognosis estimation for LGG patients. METHOD: Gene expression and clinical data of LGG patients were collected from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohort, respectively. ALT-related genes obtained from the TelNet database and potential prognostic genes related to ALT were selected by LASSO regression to calculate an ALT-related risk score. Multivariate Cox regression analysis was performed to construct a prognosis signature, and a nomogram was used to represent this signature. Possible pathways of the ALT-related risk score are explored by enrichment analysis. RESULT: The ALT-related risk score was calculated based on the LASSO regression coefficients of 22 genes and then divided into high-risk and low-risk groups according to the median. The ALT-related risk score is an independent predictor of LGG (HR and 95% CI in CGGA cohort: 5.70 (3.79, 8.58); in TCGA cohort: 1.96 (1.09, 3.54)). ROC analysis indicated that the model contained ALT-related risk score was superior to conventional clinical features (AUC: 0.818 vs 0.729) in CGGA cohorts. The results in the TCGA cohort also shown a powerful ability of ALT-related risk score (AUC: 0.766 vs 0.691). The predicted probability and actual probability of the nomogram are consistent. Enrichment analysis demonstrated that the ALT mechanism was involved in the cell cycle, DNA repair, immune processes, and others. CONCLUSION: ALT-related risk score based on the 22-gene is an important factor in predicting the prognosis of LGG patients.

Network Pharmacology, Molecular Docking and Molecular Dynamics to Explore the Potential Immunomodulatory Mechanisms of Deer Antler.

The use of deer antlers dates back thousands of years in Chinese history. Deer antlers have antitumor, anti-inflammatory, and immunomodulatory properties and can be used in treating neurological diseases. However, only a few studies have reported the immunomodulatory mechanism of deer antler active compounds. Using network pharmacology, molecular docking, and molecular dynamics simulation techniques, we analyzed the underlying mechanism by which deer antlers regulate the immune response. We identified 4 substances and 130 core targets that may play immunomodulatory roles, and the beneficial and non-beneficial effects in the process of immune regulation were analyzed. The targets were enriched in pathways related to cancer, human cytomegalovirus infection, the PI3K-Akt signaling pathway, human T cell leukemia virus 1 infection, and lipids and atherosclerosis. Molecular docking showed that AKT1, MAPK3, and SRC have good binding activity with 17 beta estradiol and estrone. Additionally, the molecular dynamics simulation of the molecular docking result using GROMACS software (version: 2021.2) was performed and we found that the AKT1-estrone complex, 17 beta estradiol-AKT1 complex, estrone-MAPK3 complex, and 17 beta estradiol-MAPK3 complex had relatively good binding stability. Our research sheds light on the immunomodulatory mechanism of deer antlers and provides a theoretical foundation for further exploration of their active compounds.

Subject-independent EEG classification based on a hybrid neural network.

A brain-computer interface (BCI) based on the electroencephalograph (EEG) signal is a novel technology that provides a direct pathway between human brain and outside world. For a traditional subject-dependent BCI system, a calibration procedure is required to collect sufficient data to build a subject-specific adaptation model, which can be a huge challenge for stroke patients. In contrast, subject-independent BCI which can shorten or even eliminate the pre-calibration is more time-saving and meets the requirements of new users for quick access to the BCI. In this paper, we design a novel fusion neural network EEG classification framework that uses a specially designed generative adversarial network (GAN), called a filter bank GAN (FBGAN), to acquire high-quality EEG data for augmentation and a proposed discriminative feature network for motor imagery (MI) task recognition. Specifically, multiple sub-bands of MI EEG are first filtered using a filter bank approach, then sparse common spatial pattern (CSP) features are extracted from multiple bands of filtered EEG data, which constrains the GAN to maintain more spatial features of the EEG signal, and finally we design a convolutional recurrent network classification method with discriminative features (CRNN-DF) to recognize MI tasks based on the idea of feature enhancement. The hybrid neural network proposed in this study achieves an average classification accuracy of 72.74 ± 10.44% (mean ± std) in four-class tasks of BCI IV-2a, which is 4.77% higher than the state-of-the-art subject-independent classification method. A promising approach is provided to facilitate the practical application of BCI.

MSATNet: multi-scale adaptive transformer network for motor imagery classification.

Motor imagery brain-computer interface (MI-BCI) can parse user motor imagery to achieve wheelchair control or motion control for smart prostheses. However, problems of poor feature extraction and low cross-subject performance exist in the model for motor imagery classification tasks. To address these problems, we propose a multi-scale adaptive transformer network (MSATNet) for motor imagery classification. Therein, we design a multi-scale feature extraction (MSFE) module to extract multi-band highly-discriminative features. Through the adaptive temporal transformer (ATT) module, the temporal decoder and multi-head attention unit are used to adaptively extract temporal dependencies. Efficient transfer learning is achieved by fine-tuning target subject data through the subject adapter (SA) module. Within-subject and cross-subject experiments are performed to evaluate the classification performance of the model on the BCI Competition IV 2a and 2b datasets. The MSATNet outperforms benchmark models in classification performance, reaching 81.75 and 89.34% accuracies for the within-subject experiments and 81.33 and 86.23% accuracies for the cross-subject experiments. The experimental results demonstrate that the proposed method can help build a more accurate MI-BCI system.

A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI.

Introduction: Brain-computer interfaces (BCIs) have the potential in providing neurofeedback for stroke patients to improve motor rehabilitation. However, current BCIs often only detect general motor intentions and lack the precise information needed for complex movement execution, mainly due to insufficient movement execution features in EEG signals. Methods: This paper presents a sequential learning model incorporating a Graph Isomorphic Network (GIN) that processes a sequence of graph-structured data derived from EEG and EMG signals. Movement data are divided into sub-actions and predicted separately by the model, generating a sequential motor encoding that reflects the sequential features of the movements. Through time-based ensemble learning, the proposed method achieves more accurate prediction results and execution quality scores for each movement. Results: A classification accuracy of 88.89% is achieved on an EEG-EMG synchronized dataset for push and pull movements, significantly outperforming the benchmark method's performance of 73.23%. Discussion: This approach can be used to develop a hybrid EEG-EMG brain-computer interface to provide patients with more accurate neural feedback to aid their recovery.

Analysis of electromagnetic response of cells and lipid membranes using a model-free method.

Electromagnetic radiation (EMR) is omnipresent on earth and may interact with the biological systems in diverse manners. But the scope and nature of such interactions remain poorly understood. In this study, we have measured the permittivity of cells and lipid membranes over the EMR frequency range of 20 Hz to 4.35 × 1010 Hz. To identify EMR frequencies that display physically intuitive permittivity features, we have developed a model-free method that relies on a potassium chloride reference solution of direct-current (DC) conductivity equal to that of the target sample. The dielectric constant, which reflects the capacity to store energy, displays a characteristic peak at 105-106 Hz. The dielectric loss factor, which represents EMR absorption, is markedly enhanced at 107-109 Hz. The fine characteristic features are influenced by the size and composition of these membraned structures. Mechanical disruption results in abrogation of these characteristic features. Enhanced energy storage at 105-106 Hz and energy absorption at 107-109 Hz may affect certain membrane activity relevant to cellular function.