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Abstract The transplantation of CD34+ hematopoietic stem-progenitor cells (HSPCs) derived from cord blood serves as the standard treatment for selected hematological, oncological, metabolic, and immunodeficiency disorders, of which the dose is pivotal to the clinical outcome. Based on numerous maternal and neonatal parameters, we evaluated the predictive power of mathematical pipelines to the proportion of CD34+ cells in the final cryopreserved cord blood product adopting both parametric and non-parametric algorithms. Twenty-four predictor variables associated with the cord blood processing of 802 processed cord blood units randomly sampled in 2020–2022 were retrieved and analyzed. Prediction models were developed by adopting the parametric (multivariate linear regression) and non-parametric (random forest and back propagation neural network) statistical models to investigate the data patterns for determining the single outcome (i.e., the proportion of CD34+ cells). The multivariate linear regression model produced the lowest root-mean-square deviation (0.0982). However, the model created by the back propagation neural network produced the highest median absolute deviation (0.0689) and predictive power (56.99%) in comparison to the random forest and multivariate linear regression. The predictive model depending on a combination of continuous and discrete maternal with neonatal parameters associated with cord blood processing can predict the CD34+ dose in the final product for clinical utilization. The back propagation neural network algorithm produces a model with the highest predictive power which can be widely applied to assisting cell banks for optimal cord blood unit selection to ensure the highest chance of transplantation success.

With standard T6 heat treatments, precipitate-hardened alloys such as Al7075 and Al6061 fabricated using Additive Friction Stir Deposition (AFSD) method restore to noticeablely different peak mechanical properties. Previous research observed similar results but did not provide a viable solution. This study proposes a new processing strategy, namely enhanced plastic deformation by subjecting the Al7075 feedstock to annealed softening treatments. Specifically, by annealing the standard T651-Al7075 feedstock and deposition substrate (179 HV), their Microhardness were first degraded to its lowest state (80 HV), which is called a Soft-to-Soft system. For the Soft-to-Soft system subjected to AFSD, after undergoing appropriate T6 heat treatment, the microhardness of the AFSD 7075 alloy was restored to its peak value (183.1 ± 1.8 HV). The results indicate that this softening strategy can effectively reduce the non-strengthening phase in the AFSD matrix, thereby increasing the strengthening phase (η′ phase). This addresses the issue of traditional AFSD-prepared aluminum alloys being unable to achieve peak performance through T6 heat treatment.

Mesenchymal stem cells (MSCs), as a stem cell type with multiple differentiation potentials and immune regulatory abilities, have shown broad prospects in the treatment of ischemic stroke in recent years. The main characteristics of MSCs include their self-renewal ability, differentiation potential for different types of cells, and the ability to secrete various bioactive factors such as cytokines, chemokines, and growth factors, which play a key role in tissue repair and regeneration. In the treatment of ischemic stroke, MSCs exert therapeutic effects through various mechanisms, including promoting vascular regeneration of damaged brain tissue, reducing inflammatory responses, and protecting neurons from damage caused by apoptosis. Research have shown that MSCs can promote the repair of ischemic areas by releasing neurotrophic factors and angiogenic factors, while inhibiting immune responses triggered by ischemia, thereby improving neurological function. With the in-depth study of its biological mechanism, MSCs have gradually shown good safety and effectiveness in clinical applications. Therefore, fully exploring and utilizing the potential of MSCs in the treatment of ischemic stroke may provide new ideas and solutions for future neural repair and regenerative medicine.

Hydrogen evolution reactions (HERs) and oxygen evolution reactions (OERs) are crucial for renewable energy production. Developing stable, cost-effective, and highly catalytic HER and OER electrocatalysts is paramount. In this study, a combination of hydrothermal synthesis and annealing was used to fabricate nickel sulfide (Ni3S2) particle–embedded nanotubes supported on nickel (Ni) foam (Ni3S2 PN/NF). The Ni3S2 PN/NF structures featured a highly branched morphology with a large specific surface area, surpassing that of conventional Ni metal nanotubes. This design increased the number of reactive sites and enhanced the charge-transfer process. The Ni foam substrate expanded the contact area of Ni3S2, thereby improving conductivity and facilitating the adsorption/desorption of intermediates on the Ni3S2 surface. Density functional theory calculations showed that the electronic structure of Ni3S2 provides excellent conductivity. Moreover, the multi-branched structure and inherent conductivity of the NiS nanomaterials enhanced the Ni3S2 PN/NF performance in 1M KOH, with overpotentials of 87 and 210 mV with iR compensation at 10 mA cm−2 for the HER and OER, respectively. The synthesized Ni3S2 PN/NF also exhibited robust durability for 20 h. These results demonstrate that Ni3S2 PN/NF is an excellent catalyst for both HER and OER.

Sleep staging plays an important role in the diagnosis and treatment of clinical sleep disorders. The sleep staging standard defines every 30 seconds as a sleep period, which may mean that there exist similar brain activity patterns during the same sleep period. Thus, in this work, we propose a novel time-related synchronization analysis framework named time-related multimodal sleep scoring model (TRMSC) to explore the potential time-related patterns of sleeping. In the proposed TRMSC, the time-related synchronization analysis is first conducted on the single channel electrophysiological signal, i.e., Electroencephalogram (EEG) and Electrooculogram (EOG), to explore the time-related patterns, and the spectral activation features are also extracted by spectrum analysis to obtain the multimodal features. With the extracted multimodal features, the feature fusion and selection strategy is utilized to obtain the optimal feature set and achieve robust sleep staging. To verify the effectiveness of the proposed TRMSC, sleep staging experiments were conducted on the Sleep-EDF dataset, and the experimental results indicate that the proposed TRMSC has achieved better performance than other existing strategies, which proves that the time-related synchronization features can make up for the shortcomings of traditional spectrum-based strategies and achieve a higher classification accuracy. The proposed TRMSC model may be helpful for portable sleep analyzers and provide a new analytical method for clinical sleeping research.

The occupant behavior has a significant impact on the building performance. This review offers researchers and practitioners a clear understanding of the evolution of the occupant behavior model and its involvement in building optimization design, providing guidance for future research. Studies are selected if they are peer-reviewed conference proceedings and journal papers published from 2005 to 2023. By analyzing 203 core papers from the Web of Science, a bibliometric study is conducted using CiteSpace. The findings indicate that research on occupant behavior has advanced significantly since 2005, with China being the most active country. The interaction between occupant and building performance, development of occupant behavior model, building optimization framework, and optimized strategies in buildings are the four fundamental topics. Finally, the current challenges and future opportunities are discussed. Future research should focus on conducting real-case quantitative studies, expanding performance simulation, developing comprehensive techniques, improving user-system interaction, and exploring feasible social practices. However, limitations arise due to deficiencies in the thoroughness and depth of analyses resulting from sample constraints. To obtain more reliable results, a broader and more systematic approach to collecting publications is needed.

Disulfidptosis, a regulated form of cell death, has been recently reported in cancers characterized by high SLC7A11 expression, including invasive breast carcinoma, lung adenocarcinoma, and hepatocellular carcinoma. However, its role in colon adenocarcinoma (COAD) has been infrequently discussed. In this study, we developed and validated a prognostic model based on 20 disulfidptosis-related genes (DRGs) using LASSO and Cox regression analyses. The robustness and practicality of this model were assessed via a nomogram. Subsequent correlation and enrichment analysis revealed a relationship between the risk score, several critical cancer-related biological processes, immune cell infiltration, and the expression of oncogenes and cell senescence-related genes. POU4F1, a significant component of our model, might function as an oncogene due to its upregulation in COAD tumors and its positive correlation with oncogene expression. In vitro assays demonstrated that POU4F1 knockdown noticeably decreased cell proliferation and migration but increased cell senescence in COAD cells. We further investigated the regulatory role of the DRG in disulfidptosis by culturing cells in a glucose-deprived medium. In summary, our research revealed and confirmed a DRG-based risk prediction model for COAD patients and verified the role of POU4F1 in promoting cell proliferation, migration, and disulfidptosis.

Earth-cover landfills are one of the primary means of treating urban garbage. However, the organic matter in the garbage generates a large amount of gas upon degradation. The internal gas pressure will be substantially high if the gas generation rate is considerably high or if the gas drainage is not smooth, resulting in the deformation and destruction of the soil cover, thus affecting the stability of the landfill. Accordingly, a plane model test of gas pressure-induced failure of unsaturated soil was performed using a self-designed test device, and the deformation and failure mechanisms of soil under different soil thicknesses and gas pressures were comparably studied through numerical simulation. The results revealed that the process of soil damage induced by gas pressure can be divided into four stages—water and gas migration, local micro crack generation, main crack penetration, and internal cavity formation; Soil damage mainly occurs in the inverted triangle area between the top of the inflatable hole and the surface layer. The soil failure modes can be divided into two types—splitting and burst failure—depending on whether there was a previous gas-pressure effect. The failure pressure of soil increases in an approximately linear fashion with an increase in the thickness of the overlying soil. Accordingly, the concept of failure stress ratio was proposed, and it was observed that the failure stress ratio of each soil layer thickness can be approximately regarded as a constant, which has a certain importance for monitoring the landfill overburden in practical engineering. Additionally, the test results revealed that appropriate gas pressure is conducive to increasing the stability of soil mass; the soil mass will gradually become unstable if gas pressure exceeds a certain value, based on which the concept of critical stable gas pressure was proposed. Furthermore, the proposed numerical simulation method was used to establish a corresponding two-dimensional numerical model with reference to the model test. The numerical results, including the fracture propagation pattern and failure pressure results, were consistent with the model test results. On this basis, the seepage variation law within the soil mass was deeply studied. It was observed that the gas pressure increases the pore pressure inside the soil while driving the water to diffuse around, causing changes in the saturation of the surrounding soil. Finally, the simulation results revealed that regional change of effective stress increment may be the cause of critical stable gas pressure, providing a reference for practical engineering.

Background and objective In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. Methods A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. Results MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P

Abstract Background Inflammatory myofibroblastic tumor (IMT) is a distinctive tumor composed of spindle cells accompanied by mixed inflammatory cells, and immunohistochemical positivity for ALK (anaplastic lymphoma kinase protein) can be detected in half of IMTs. The diagnosis of ALK-negative IMT could be a challenge. Recently, the fusions of some kinase genes, such as RET, NTRK1, ROS1, etc., are revealed in ALK-negative IMT. Case presentation A 19-year-old woman presented with swelling of the left upper arm. Magnetic resonance imaging (MRI) scan revealed a tumor in the left postbrachium extended to the left axillary, serratus anterior muscle, and latissimus dorsi muscle. Histopathologically, the irregular-circumscribed tumor was composed of dense spindle-shaped cells with eosinophilic abundant cytoplasm and hyalinized mesenchyme in an inflammatory background. Immunohistochemically (IHC), tumor cells were positive for SMA, MDM2, and p16; the cells were negative for desmin, MyoD1, Myogenin, pan-cytokeratin, S100, SOX10, HMB45, Malen-A, CD34, CD31, CD99, and ALK. By RNA-based NGS, a novel fusion between TPD52L2 3’ end of exon 1–4 and ROS1 5’ end of exon 36–43 was revealed. ROS1 IHC staining was negative. The final diagnosis of IMT with TPD52L2-ROS1 fusion was made. Subsequently, the patient experienced a good clinical response to Crizotinib, and clinical follow-up showed stable disease after 9 months. Conclusion This report expands the spectrum of ROS1 gene rearrangements in the IMT and highlights the importance of molecular analysis of IMT for getting a diagnostic clue and determining potential therapeutic strategies.

Electrophysiological monitoring is a commonly used medical procedure designed to capture the electrical signals generated by the body and promptly identify any abnormal health conditions. Wearable sensors are of great significance in signal acquisition for electrophysiological monitoring. Traditional electrophysiological monitoring devices are often bulky and have many complex accessories and thus, are only suitable for limited application scenarios. Hydrogels optimized based on nanomaterials are lightweight with excellent stretchable and electrical properties, solving the problem of high-quality signal acquisition for wearable sensors. Therefore, the development of hydrogels based on nanomaterials brings tremendous potential for wearable physiological signal monitoring sensors. This review first introduces the latest advancement of hydrogels made from different nanomaterials, such as nanocarbon materials, nanometal materials, and two-dimensional transition metal compounds, in physiological signal monitoring sensors. Second, the versatile properties of these stretchable composite hydrogel sensors are reviewed. Then, their applications in various electrophysiological signal monitoring, such as electrocardiogram monitoring, electromyographic signal analysis, and electroencephalogram monitoring, are discussed. Finally, the current application status and future development prospects of nanomaterial-optimized hydrogels in wearable physiological signal monitoring sensors are summarized. We hope this review will inspire future development of wearable electrophysiological signal monitoring sensors using nanomaterial-based hydrogels.

As the global energy landscape transitions towards a more sustainable future, hydrogen has emerged as a promising energy carrier due to its potential to decarbonize various sectors. However, the economic competitiveness of hydrogen production by water electrolysis strongly depends on renewable energy source (RES) availability. Thus, it is necessary to overcome the challenges related to the intermittent nature of RESs. This paper presents a comprehensive techno-economic analysis of complementing green hydrogen production with grid electricity. An evaluation model for the levelized cost of hydrogen (LCOH) is proposed, considering both CO2 emissions and the influence of RES fluctuations on electrolyzers. A minimum load restriction is required to avoid crossover gas. Moreover, a new operation strategy is developed for hydrogen production plants to determine optimal bidding in the grid electricity market to minimize the LCOH. We evaluate the feasibility of the proposed approach with a case study based on data from the Kyushu area in Japan. The results show that the proposed method can reduce the LCOH by 11% to 33%, and increase hydrogen productivity by 86% to 140%, without significantly increasing CO2 emission levels.

To enable the widespread adoption of residential energy storage, sustainable, low-cost, long-life, and energy-dense battery technologies are required. Sodium-ion offers many of these characteristics, however often the system is tailored for energy rather than cycle life. In this work, the effect of synthesis conditions upon the primary and agglomerated secondary particle size and shape of the sodium-ion cathode material NaNi1/3Fe1/3Mn1/3O2 was investigated for optimization of energy and cycle life. A two-level full factorial experimental design was utilized to examine how the synthesis parameters (pH, molar ratio of ammonia/metal precursor salt, and stirring speed) affect the physical and electrochemical properties. This approach enabled a comprehensive investigation of the main effects and interactions of these parameters. The data from multiple synthesis runs were analyzed using statistical methods and regression analysis. This experimental design provided valuable insights into the relationship between synthesis parameters and material properties. Statistical analysis indicates that both physical and electrochemical properties are mainly controlled through pH and NH4OH, while the effects of stirring speed are less pronounced. The optimal synthetic conditions producing the highest cycling performance were extrapolated from the statistical analysis. A validation experiment showed that particles synthesized with optimum parameters displayed a threefold increase in cycling performance together with uniformly distributed particle size and a high tap density.

Aims: We aim to evaluate the expression of GNA13 in germinal center (GC)-derived B cell lymphomas to evaluate its potential use as marker for diagnosis. Methods and Results: In this study, GNA13 expression was detected by immunohistochemistry in 129 cases of B-cell non-Hodgkin lymphomas (B-NHLs) and 8 cases of angioimmunoblastic T-cell lymphoma (AITL). Furthermore, mutations in the GNA13 gene in 114 cases of B-NHLs were detected by exome sequencing. In 50 cases of diffuse large B-cell lymphoma (DLBCL), 11 cases were positive for GNA13, and all GNA13-positive cases were of the germinal center B-cell-like (GCB) subtype. In 42 cases of follicular lymphoma (FL), the GNA13-positive rate was 100% in FL grade 1, 100% in FL grade 2, 80.0% in FL grade 3 A, and 63.2% in FL grade 3B. In 6 cases of Burkitt lymphoma, 3 cases were positive for GNA13. However, in small lymphocytic lymphoma, mantle cell lymphoma and marginal zone lymphoma, GNA13 was negative or only expressed in the GC. In addition, the GNA13-positive rate was 100% in AITL. The mutation of the GNA13 gene was 27.8% (5/18) in GCB-DLBCL and 10.3% (3/29) in FL, respectively, and mutation of GNA13 occurred in cases with weak positive or negative expression of the GNA13 protein. Conclusion: GNA13 may be a reliable new marker for GC cells applied in the diagnosis of GC-derived B-cell lymphomas. Its deficiency or low expression may be related to the degree of invasion of GC-derived B-cell lymphomas, and may result from genetic mutations.

With the rapid development of artificial intelligence, human‐machine interfaces (HMI) are continuing to affect human lifestyles. Artificial skin is a new type of HMI sensor that enables a seamless connection between human and electronic devices. Currently, artificial skin is mostly prepared from rigid materials, which lack flexibility and scalability, thus impeding the development of HMI. Hydrogel, consisting of 3D polymer network and water is similar to human tissues and is therefore an excellent candidate for artificial skin in HMI. The conventional HMI of hydrogel‐based artificial skin includes touch pad and machine control based on capacitive or resistive sensors. However, the energy supply of HMI depends on battery which requires frequent recharging and replacement. Therefore, hydrogel‐based self‐powered artificial skin is expected to become primary interaction medium for the forthcoming generation of HMI. This article reviews the development of hydrogel‐based self‐powered artificial skin for HMI. Various power supply mechanisms of hydrogel‐based artificial skin are discussed. The materials for self‐powered artificial skin are introduced, including ionic hydrogel, ionic‐liquid hydrogel, metal‐based hydrogel, carbon‐based and MXene‐based hydrogel, and conductive polymer‐based hydrogel. The application of the hydrogel‐based self‐powered artificial skin in HMI is also reviewed. Finally, the challenges and development trends in HMI are outlined.

Abstract Microgrid clusters (MGC) can improve the consumption of renewable energy and the system reliability. The control of microgrid cluster with large‐scale microgrids is the focus of microgrid cluster research. In order to better realize the coordination control and energy scheduling among microgrids, this paper proposes a distributed optimal strategy for complex MGC based on model predictive control (MPC) and block‐wised alternating direction multiplier method (BADMM). Firstly, an optimization model is established based on a honeycomb active distribution network (HADN); then the network is decomposed into several regions according to BADMM. The global optimization goal of the cluster is achieved by iterating the optimization results of each region in a time domain. Finally, the case study results verify the effectiveness and convergence of the proposed distributed optimization strategy, and provide a reference for energy management of MGC.

Abstract Background The aging process in the tobacco production, as in other food industries, is an important process for improving the quality of raw materials. In the spontaneous aging, the complex components in flue-cured tobacco (FT) improve flavor or reduce harmful compounds through chemical reactions, microbial metabolism, and enzymatic catalysis. Some believed that tobacco-microbe played a significant part in this process. However, little information is available on how microbes mediate chemical composition to improve the quality of FT, which will lay the foundation for the time-consuming spontaneous aging to seek ways to shorten the aging cycle. Results Comparing aged and unaged FT, volatile and non-volatile differential compounds (DCs) were multi-dimensionally analyzed with the non-targeted metabolomes based on UPLC-QTOP-MS (the ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry), GC–MS (gas chromatography-mass spectrometer) assisted derivatization and HP-SPME-GC/MS (headspace solid-phase micro-extraction assisted GC–MS). Products associated with the degradation pathways of terpenoids or higher fatty acids were one of the most important factors in improving FT quality. With the microbiome, the diversity and functions of microbial flora were analyzed. The high relative abundance function categories were in coincidence with DCs-related metabolic pathways. According to the correlation analysis, Acinetobacter, Sphingomonas and Aspergillus were presumed to be the important contributor, in which Aspergillus was associated with the highest number of degradation products of terpenoids and higher fatty acids. At last, the screened Aspergillus nidulans strain F4 could promote the degradation of terpenoids and higher fatty acids to enhance tobacco flavor by secreting highly active lipoxygenase and peroxidase, which verified the effect of tobacco-microbes on FT quality. Conclusions By integrating the microbiome and metabolome, tobacco-microbe can mediate flavor-related substances to improve the quality of FT after aging, which provided a basis for identifying functional microorganisms for reforming the traditional spontaneous aging.

As part of the ocean winch, the traction winch mainly plays the role of attenuating the load tension. It generally uses simple speed control. For the ship-based collection and release system, complex sea conditions make the cable tension constantly changes. The traditional control method will make the cable in the traction winch too slack or too tight. Meanwhile, it can result in the wrong rope, bite rope and slippage, and other phenomena. Eventually, it is leading to cable damage or breakage and equipment loss. Moreover, with the introduction of expensive photoelectric composite cables, there is a greater need for a good control algorithm to extend the life of the cable and ensure the safety of retrieval and release. Therefore, this paper focuses on the constant tension control of the traction winch cable. In this paper, the NARX neural network-based cable tension compensation value prediction model is established as the feedforward part based on historical ship heave displacement data and cable tension compensation data as training data. On this basis, the simulation model of cable constant tension winch based on common PID control, fuzzy PID control, and BP fuzzy neural network PID control are established. By comparing the tension of the cable with the above controller, the results show that the tension control of the cable based on the NARX neural network predicted tension compensation value plus BP fuzzy neural network PID control has high accuracy, fast dynamic response, smooth system, and no overshoot.

BackgroundPercutaneous nephrolithotripsy (PCNL) is the main method for urinary calculi. An anesthesia method with little effect on the blood circulation and which does not affect the postoperative activity of a patient is lacking.ObjectiveTo compare the effects of paravertebral nerve block (PNB) and epidural block (EPB) on quadriceps femoris muscle (QFM) strength in patients after PCNL.Methods163 patients were separated into two groups: EPB (81) and PNB (82). Primary outcome parameters were QFM strength and range of motion (RoM) of the knee 1 h, 2 h, 3 h, and 24 h after anesthesia induction (AI). Secondary outcome parameters were: time from AI beginning to first ambulation; time of sensory-plane recovery; amount of additional analgesics given during and after surgery; prevalence of nausea and vomiting; duration of hospital stay (DoHS); mean arterial pressure (MAP), heart rate (HR), and oxygen saturation (SpO2) before, 0.5 h, and 1 h after AI; visual analog scale (VAS) score 0.5 h, 1 h, 2 h, 3 h and 24 h after AI.ResultsThere was no significant difference in QFM strength or knee RoM before or 24 h after AI between the two groups (P > 0.05). The time from AI to first ambulation was shorter (P 0.05). VAS scores were higher in the PNB group than in the EPB group 0.5 after AI (P 0.05).ConclusionsFor patients undergoing PCNL, PNB can meet the need for surgical analgesia while having little effect on QFM strength.Trial registrationhttp://www.chictr.org.cn/, identifier ChiCTR2200060606.

Abstract Smart Internet of Vehicles (IoV) as a promising application in Internet of Things emerges with the development of the fifth generation mobile communication (5G). Nevertheless, the heterogeneous requirements of sufficient battery capacity, powerful computing ability and energy efficiency for electric vehicles face great challenges due to the explosive data growth in 5G and the sixth generation of mobile communication (6G) networks. In order to alleviate the deficiencies mentioned above, this paper proposes a mobile edge computing (MEC) enabled IoV system, in which electric vehicle nodes upload and download data through an anchor node which is integrated with a MEC server. Meanwhile, the anchor node transmitters radio signal to electric vehicles with simultaneous wireless information and power transfer technology so as to compensate the battery limitation of eletric vehicles. Moreover, the spectrum efficiency is further improved by multi-input and multi-output and full-duplex technologies which is equipped at the anchor node. In consideration of the issues above, we maximize the average energy efficiency of electric vehicles by jointly optimize the CPU frequency, vehicle transmitting power, computing tasks and uplink rate. Since the problem is nonconvex, we propose a novel alternate interior-point iterative scheme (AIIS) under the constraints of computing tasks, energy consumption and time latency. Results and discussion section verifies the effectiveness of the proposed AIIS scheme comparing with the benchmark schemes.

The network-assisted full-duplex (NAFD) system realizes flexible duplex in the spatial domain within the same time-frequency resource. With the explosive growth of the number of users and remote antenna units (RAUs) under 6G scenario, the resource utilization of the system is lower. When the resource of users is selected by the RAUs to send or receive, collisions or congestion may occur due to mechanisms such as grant-free. Aiming at making better use of system resources, a load-aware dynamic mode selection scheme with NAFD scheme is proposed to improve the access efficiency and resource utility of the system. This paper first propose a centralized Q-learning algorithm which determines a clever strategy to approach the ultimate goal by itself and excels in environment dynamics. However, the size of the Q-table used in the centralized Q-learning algorithm for storage is huge. Further, a distributed multi-agent Q-learning algorithm is proposed which has a smaller size of Q-table and lower complexity to suit for actual scenarios. The simulation results showed that the proposed load-aware dynamic mode selection scheme can significantly improve resource utility and throughput performance than other traditional schemes.

Flue-cured tobacco (FCT) is an economical raw material whose quality affects the quality and cost of the derived product. However, the time-consuming and inefficient spontaneous aging is the primary process for improving the FCT quality in the industry. In this study, a function-driven co-culture with functional microorganisms was built in response to the quality-driven need for less irritation and more aroma in FCT. The previous study has found that Bacillus kochii SC could degrade starch and protein to reduce tobacco irritation and off-flavors. The Filobasidium magnum F7 with high lipoxygenase activity was screened out for degrading higher fatty acid esters and terpenoids to promote the aroma and flavor of FCT. Co-cultivation with strain SC and F7 obtained better quality improvement than mono-culture at an initial inoculation ratio of 1:3 for 2 days, representing a significant breakthrough in efficiency and a reduction in production costs compared to the more than 2 years required for the spontaneous aging process. Through the analysis of microbial diversity, predicted flora functions, enzyme activities and volatile compositions within the mono- and co-cultivation, our study showed the formation of a function-driven co-culture between two strains through functional division of labor and nutritional feeding. Herein, the function-driven co-culture via bioaugmentation will become an increasingly implemented approach for the tobacco industry.

Background: Tobacco alcoholization is an important step in increasing the quality of tobacco leaf, which may convert a portion of low-grade tobacco leaves into useable product, however this may take to 2–3 years. The addition of exogenous microorganisms to tobacco leaves and treating them by biological fermentation can shorten the maturation time of tobacco leaves, and improve the quality and applicability of low-grade tobacco leavesMethods: Several strains were screened from low-grade tobacco by flow cytometry, including the bacteria Bacillus amyloliticus, with starch degradation ability and Bacillus kochii, with protein degradation ability, and the fungus Filobasidium magnum with lipid oxidase ability, and were inoculated onto tobacco leaves, both individually and in combination, for solid-state fermentationResults: The greatest improvement in tobacco quality was observed when strains 4# and 3# were applied at a ratio of 3:1. The Maillard reaction products, such as 2-amyl furan, 1-(2-furanmethyl) -1 h-pyrrole, furfural and 2, 5-dimethylpyrazine, were significantly increased, by up to more than 2 times. When strains F7# and 3# were mixed at a ratio of 3:1, the improvement of sensory evaluation index was better than that of pure cultures. The increase of 3-(3, 4-dihydro-2h-pyrro-5-yl) pyridine, β -damasone and benzyl alcohol was more than 1 times. The increase of 2-amyl-furan was particularly significant, up to 20 timesConclusion: The functional strains screened from tobacco leaves were utilized for the biological fermentation of tobacco leaves, resulting in the reduction of irritation and an improvement in quality of final product, showing a good potential for application.

BackgroundParaneoplastic peripheral neuropathy (PPN) caused by olfactory neuroblastoma (ONB) has not yet been reported.Case reportWe present a rare case of an adult who hospitalized repeatedly over the past 9 months for persistent pain and numbness in the limbs. This patient was initially diagnosed with chronic inflammatory demyelinating polyneuropathy (CIDP) and treated accordingly, but neurological symptoms did not improve significantly. After this admission, FDG-PET/CT showed focal hypermetabolism of a soft-tissue mass in the nasal cavity, and further lesion biopsy suggested ONB. Combined with positive serum anti-Hu antibody, the diagnosis of PPN associated with ONB was eventually made. Furthermore, the patient's neurological symptoms were relieved after removal of the primary tumor, confirming the accuracy of the diagnosis.ConclusionOur case not only expanded the clinical characteristics of ONB but also highlighted the importance of early and comprehensive tumor screening for the diagnosis of PPN.

Abstract In the micro electro mechanical system (MEMS) area, micro metal devices fabricating by the electroplating process were used widely in biology, medicine and optics field. However, due to the oxide layer of the metal substrate surface, the electroplating layer suffers from the poor adhesion. In order to reduce the oxide layer of the metal substrate surface, effects of the ultrasonic assisted electrochemical potential activation method have been investigated originally. The electrochemical test was processed by an electrochemical station. The oxide content of the substrate surface was measured by the X‐ray photoelectron spectroscopy (XPS) method. The experimental results show that, comparing with the ultrasound free one, the ultrasonic assisted electrochemical potential activation method can improve the hydrogen evolution reaction and reduce the metal ion nucleation rate. Then the Cu substrate surface oxide content has been restored. Results of this paper can provide a new ultrasonic electrochemical potential activation method to activate the oxide layer of the substrate surface, as well as to improve the adhesion.

Abstract In the present study, we aimed to find the target of Tanshinone IIA (Tan-IIA) in Cholangiocarcinoma by network pharmacology-based prediction and investigate the possible mechanism through experimental verification. In this study, we combined Tan-IIA-specific and Cholangiocarcinoma-specific targets with protein–protein interactions (PPI) to construct a Tan-IIA targets-Cholangiocarcinoma network, and network pharmacology approach was applied to identify potential targets and mechanisms of Tan-IIA in the treatment of Cholangiocarcinoma. The anti-cancer effects of Tan-IIA were investigated by using subcutaneous tumorigenic model in nude mice and in the human Cholangiocarcinoma cell lines in vitro. Our results showed that Tan-IIA treatment considerably suppressed the proliferation and migration of Cholangiocarcinoma cells while inducing apoptosis of Cholangiocarcinoma cells. Western blot results demonstrated that the expression of PI3K, p-Akt, p-mTOR, and mTOR were inhibited by Tan-IIA. Meanwhile, After treatment with Tan-IIA, the level of Bcl2 was downregulated and cleaved caspase-3 expression increased. Further studies revealed that the anticancer effects of Tan-IIA were severely mitigated by pretreatment with a PI3K agonist. Our research provides a new anticancer strategy and strengthens support for the use of Tan-IIA as an anticancer drug for the treatment of CCA.

The development of next-generation electrodes is key for advancing performance parameters of lithium-ion batteries and achieving the target of net-zero emissions in the near future. Electrode architecture and design can greatly affect electrode properties and the effects are sometimes complicated. The architecture of current electrodes is designed mainly based on empirical studies by making trade-offs between battery performance parameters. Thus, a holistic understanding of the relationships between electrode architecture-property-performance is urgently needed. Additionally, the implementation of next-generation electrodes with optimised architectures also relies on manufacturing capability. Various manufacturing processes have been proposed to produce electrodes with characteristic architectures. Nevertheless, the merits and limitations of the manufacturing processes are not well understood and selecting appropriate manufacturing processes is challenging. Herein, ten manufacturing processes are illustrated, which have been classified into four categories of slurry casting, templating, additive manufacturing, laser ablation. The overall performance of all the manufacturing processes is first qualitatively compared from five different aspects of architectural controllability, scalability, sustainability, simplicity and cost, followed by a quantitative comparison using a Weighted Manufacturing Score method. This work provides a guideline for future electrode architectural design illustrating the limitations and potential advantages of different methodologies to stimulate the development of the next-generation LIB electrodes.

With the enhancement of carbon sink capacity and the intensification of biodiversity change in coastal wetlands, previous studies have well studied the relationship between species diversity and litter decomposition, a vital process of carbon cycling. However, previous studies ignored the importance of genetic diversity, which restricted our comprehensive understanding of the effects of biodiversity loss on ecosystem functions. Here, we manipulated different richness levels with litters of eight common species of coastal wetland plants and eight different genotypes of common reed (Phragmites australis) to explore the effects of species and genetic diversity on litter decomposition. We found the litter mass loss of mixtures was significantly lower than the average mass loss of single litters (ANOVA, p

Vertical line source irrigation (VLSI) is an underground irrigation method suitable for deep-rooted plants. Understanding the characteristics of the soil wetting body of the VLSI was the key to designing this irrigation system. On the basis of experimental verification of the reliability of the HYDRUS simulation results of VLSI under the conditions of soil texture (ST), initial water content (θi), line source buried depth (B), line source diameter (D) and line source length (L), numerical studies of the migration law of the wetting front of VLSI and the distribution characteristics of soil moisture were performed. The wetting front migration (WFM) was mainly influenced by ST, θi, D and L (P < 0.05), while B had little effect on WFM (P > 0.05). The shape of the soil wetting body changed little under different influencing factors. The water content contour was approximately ‘ellipsoidal’ around the line source. The soil moisture near the line source was close to the saturated moisture content. The moisture content around the line source gradually decreased outward, and the contour lines gradually became dense. According to the simulation results, a prediction model of multiple factors influencing the migration process of the VLSI wetting front was established. The predicted value was in good agreement with the measured value. The results of this research could provide a theoretical basis for further optimizing the combination of VLSI and irrigation elements. HIGHLIGHTS Based on HYDRUS-2D, a multi-factor prediction model was established for the wet front migration process in vertical source irrigation.; The validity of the model was verified by experimental data, and the prediction effect was good.; Numerical studies of the migration law of the wetting front of the vertical line source irrigation and the distribution characteristics of soil moisture were performed.; The wetting front migration was mainly influenced by soil texture, initial water content, line source diameter and line source length (P < 0.05), while line source buried depth had little effect on it (P > 0.05).; The shapes of the contours of soil moisture content were slightly different, and were all approximate 'ellipsoids' with the axis of the line source.;

Soil microorganisms play vital roles in regulating biogeochemical processes. The composition and function of soil microbial community have been well studied, but little is known about the responses of bacterial and fungal communities to different habitats of the same plant, especially the inter-kingdom co-occurrence pattern including bacteria and fungi. Herein, we used high-throughput sequencing to investigate the bacterial and fungal communities of five Phragmites australis habitats in the Yellow River Delta and constructed their inter-kingdom interaction network by network analysis. The results showed that richness did not differ significantly among habitats for either the bacterial or fungal communities. The distribution of soil bacterial community was significantly affected by soil physicochemical properties, whereas that of the fungal community was not. The main functions of the bacterial and fungal communities were to participate in the degradation of organic matter and element cycling, both of which were significantly affected by soil physicochemical properties. Network analysis revealed that bacteria and fungi participated in the formation of networks through positive interactions; the role of intra-kingdom interactions were more important than inter-kingdom interactions. In addition, rare species acted as keystones played a critical role in maintaining the network structure, while NO3−−N likely played an important role in maintaining the network topological properties. Our findings provided insights into the inter-kingdom microbial co-occurrence network and response of the soil microbial community composition and function to different P. australis habitats in coastal wetlands, which will deepen our insights into microbial community assembly in coastal wetlands.

Crosstalk is the primary source of noise in quantum computing equipment. The parallel execution of multiple instructions in quantum computation causes crosstalk, which causes coupling between signal lines and mutual inductance and capacitance between signal lines, destroying the quantum state and causing the program to fail to execute correctly. Overcoming crosstalk is a critical prerequisite for quantum error correction and large-scale fault-tolerant quantum computing. This paper provides an approach for suppressing crosstalk in quantum computers based on multiple instruction exchange rules and duration. Firstly, for the majority of the quantum gates that can be executed on quantum computing devices, a multiple instruction exchange rule is proposed. The multiple instruction exchange rule reorders quantum gates in quantum circuits and separates double quantum gates with high crosstalk on quantum circuits. Then, time stakes are inserted based on the duration of different quantum gates, and quantum gates with high crosstalk are carefully separated in the process of quantum circuit execution by quantum computing equipment to reduce the influence of crosstalk on circuit fidelity. Several benchmark experiments verify the proposed method’s effectiveness. In comparison to previous techniques, the proposed method improves fidelity by 15.97% on average.

Epidermal electronics offer an important platform for various on-skin applications including electrophysiological signals monitoring and human–machine interactions (HMI), due to their unique advantages of intrinsic softness and conformal interfaces with skin. The widely used nondegradable synthetic materials may produce massive electronic waste to the ecosystem and bring safety issues to human skin. However, biomaterials extracted from nature are promising to act as a substitute material for the construction of epidermal electronics, owing to their diverse characteristics of biocompatibility, biodegradability, sustainability, low cost and natural abundance. Therefore, the development of natural biomaterials holds great prospects for advancement of high-performance sustainable epidermal electronics. Here, we review the recent development on different types of biomaterials including proteins and polysaccharides for multifunctional epidermal electronics. Subsequently, the applications of biomaterials-based epidermal electronics in electrophysiological monitoring and HMI are discussed, respectively. Finally, the development situation and future prospects of biomaterials-based epidermal electronics are summarized. We expect that this review can provide some inspirations for the development of future, sustainable, biomaterials-based epidermal electronics.

With the explosive growth of mobile communication technology, the number of access terminals has increased dramatically, which will make the pilot contamination caused by pilot reuse extremely worse due to limited pilot resources. It is difficult to apply a traditional pilot assignment algorithm to serve the numerous access terminals simultaneously in real time with low complexity, so there is necessity to design a scalable pilot assignment scheme in the case of massive access. In this paper, we propose a scalable deep learning-based pilot assignment algorithm to maximize the sum spectral efficiency (SE) of cell-free large-scale distributed multiple-input multiple-output (MIMO) systems with massive access. The mapping between user locations and pilot assignment schemes is learned by a deep neural network (DNN). The training samples of the DNN are generated by a min-max algorithm, which minimizes the maximum interference to alleviate pilot contamination. The output of the pretrained DNN is used as the initial value of the min-max algorithm to achieve better pilot assignment schemes and reduce the algorithm complexity. The simulation results show that the proposed algorithm has better convergence with massive access and achieves a higher sum SE in near real time.

In recent years, quantum computing has received extensive attention for its superior efficiency and application potential. For some physical architecture, one qubit can only interact with its adjacent qubits, SWAP gates are inserted to make a quantum circuit nearest neighbor compliant. The initial qubit placement algorithm in a 2D grid structure is proposed based on the constructed interaction cost metric model, and the method of dynamic grid decision is given. In order to obtain a better way of inserting SWAP gates, the gate level and circuit level interaction routing policies are put forward, and a heuristic pruning of interaction routing records is employed so as to reduce the runtime and additional quantum cost. Experimental results show that our proposed methods can achieve better performance than existing methods, and the average optimization rate of quantum cost is 21.76% and 17.23% respectively.

Estimations of bulk hardness from nanoindentation are frequently subject to considerable uncertainties due to indentation size effects (ISE), pileup effects, and potential influence of surface quality or test methods. This study examined materials science principles of nanoindentation test methods to enable accurate prediction of bulk hardness for a series of high purity Fe and Fe-(3–25 wt%) Cr alloys. These materials were tested in as-annealed and thermally aged (100–900 h at 475 ℃ to produce Cr-rich α’ precipitates) conditions. Nanoindentation with a Berkovich indenter at constant strain rate (0.05–0.5 /s) and constant loading rate conditions provided comparable bulk equivalent hardness (H0) extracted by Nix-Gao model, indicating a weak strain rate sensitivity at room temperature. Results from electropolished and fine mechanically polished samples gave comparable measured hardness. Pileup corrections produced a 5–14% correction to H0 which agreed with the experimental bulk Vickers hardness within ∼10% for most tested materials. The microstructural model-predicted and measured strength values agreed for aged samples. A derived analytic expression demonstrates that an ISE error, associated with inappropriate methods such as hardness ratios or changes at a reference depth, would be as large as 60% in estimated bulk hardness for the investigated Fe-Cr alloys.

Ionic hydrogels outperform existing rigid and bulky electronics with many remarkable advantages including great flexibility, high conductivity, exceptional biocompatibility, and transparency, making them ideal materials for wearable human–machine interfaces (HMIs). However, traditional HMIs typically rely on external power sources, which impose limitations in terms of device size and weight, thereby compromising the user experience in HMIs. The advent of triboelectric nanogenerators (TENGs) employing ionic hydrogels has introduced a sustainable energy solution for self-powered HMIs. These TENGs can harvest the electrical energy resulting from the migration of ions induced by mechanical motion, thereby offering a sustainable energy solution for applications in wearable HMIs. Hence, the development of ionic hydrogels-based TENGs holds immense potential for the advancement of self-powered HMIs. This review first introduces the latest achievements in the fabrication of ionic hydrogel-based TENGs using diverse materials, including synthetic polymers, natural polymers, and low-dimensional materials. Then different working principles and modes of the ionic hydrogel-based TENGs are elucidated. Subsequently, the applications of these TENGs in self-powered HMIs are discussed, such as robot control, medical applications, electronic device control, and other applications. Finally, the current status and future prospects of ionic hydrogel-based TENGs in self-powered HMIs are summarized. We hope that this review will provide inspiration for the future development of self-powered human–machine interfaces utilizing ionic hydrogels-based TENGs.

Under $\textit {ergodic}$ per-user quality-of-service and per-remote antenna unit (RAU) transmit power constraints, we investigate the problem of maximizing energy efficiency (EE) of distributed massive MIMO systems, which is known to be non-convex. To solve this challenging problem efficiently, we first derive closed-form expressions for the spectral efficiency and the power control parameters (related to per-RAU transmit power constraint) with zero-forcing (ZF) and maximum ratio transmission (MRT) beamforming, and then develop a computationally feasible power allocation algorithm using the tools of fractional programming and sequential convex approximation. The derived closed-form expressions are functions of only slowly changing large-scale fading which enables us to solve the optimization problem over a longer time interval. The proposed power allocation algorithm is guaranteed to converge to the Karush–Kuhn–Tucker points of the original non-convex EE maximization problem. The simulation results demonstrate the accuracy of the derived expressions and the effectiveness of the proposed algorithm. Moreover, some insightful conclusions are arrived at from the EE comparisons between different beamforming schemes (ZF and MRT) and different antenna deployments (distributed and co-located).

Recently, a novel network architecture for a distributed antenna system with interlaced clustering has been proposed to mitigate the cell-edge problem. Under this network architecture, we propose a more practical implementation for ultradensely deployed remote antenna units (RAUs) with large numbers of users. Furthermore, we focus on the user selection (USC) and sparse beamforming technologies to optimize the weighted sum rate (WSR) with both backhaul and power constraints. First, we divide each cluster pattern (CP) into several adaptive cells, where RAUs are connected to a central processor via finite-capacity backhaul links. Aiming at reducing the computational complexity for large numbers of users and RAUs, we solve the original problem with two steps. In the first stage, we propose an efficient USC algorithm to find the largest user subset that satisfies the quality of service requirement. In the second stage, we adopt a CP-based weighted sum minimum mean square error algorithm to optimize the WSR problem for the selected users in the previous stage. Moreover, two decomposition algorithms, named primal decomposition and dual decomposition, are exploited to further reduce the computational complexity. Furthermore, based on the adaptive cells, we provide a low-complexity alternating optimization method for sparse beamforming. Finally, simulation results show that the proposed algorithms can achieve a significant performance gain on edge-user rates without losing much performance gain. At the same time, the backhaul information exchange is largely reduced, and approximately 90% of the RAUs consumes less than 66.7% of backhaul for each RAU.

In this paper, we consider a green communication design in a multiple-input-multiple-output orthogonal frequency-division multiplexing-based downlink cloud radio access network system with per-user quality of service constraints and remote antenna units (RAUs) power constraints. Two problems are solved in this paper: a total transmits power minimization problem and a total network consumption minimization problem. The first problem is to minimize the total transmit power of RAUs by designing beamforming. While the other is to minimize the total network consumption by beamforming and switching off unnecessary RAUs, which is a joint design of sparse beamforming and RAU selection. It is a mixed integer nonlinear programming problem and hard to deal with. Approximations are made to convert the problems into convex ones by using the difference of convex programming and a mixed ℓ1/ℓ2-norm. Then, the iterative algorithms are proposed to solve the problems. The simulation results show that by using proposed algorithms, the transmit power consumption and the network power consumption can be significantly reduced. Meanwhile, the number of active RAUs can be effectively decreased.

This paper addresses the performance of downlink beamforming in fog radio access networks (F-RANs) with distributed antennas. The wireless channel is modeled as Rician fading. We analyze the asymptotic behavior of the signal-to-interference-plus-noise ratio (SINR) and the data rate of maximum ratio transmission (MRT) and regularized zero-forcing (RZF) beamformers in the large system limit, where the numbers of antennas and users go to infinity while keeping a fixed ratio. In some practical F-RAN environment, it is difficult to perform centralized processing and share channel state information (CSI) globally, so distributed beamforming schemes are of interest. Therefore, we propose the local zero-forcing (ZF) beamformer that relies only on local CSI. The simulation results show that the asymptotic results of MRT and RZF are accurate for finite system size, and the local ZF beamformer provides a tradeoff between MRT and RZF in terms of CSI sharing complexity and interference control ability.

With the advent of the 5G era, the number of user terminals has increased dramatically. However, the limitation of pilot resources results in pilot reuse among user terminals, which makes the performance of massive multiple-input-multiple-output (MIMO) systems constrained by pilot contamination. In this paper, we propose a pilot allocation algorithm based on coalitional game theory to minimize the error of channel estimation in distributed MIMO systems. The simulation results show that the performance of the algorithm is very close to the exhaustive method with low complexity and far better than the random pilot reuse.

Objective: The objective of this study is to investigate the effects of laparoscopic and open operation on serum and peritoneal inflammatory mediators in patients with right colon carcinoma. Patients and Methods: A total of 100 patients were randomly divided into laparoscopic group (n = 50) and open group (n = 50). The age, sex, operation time, operation blood loss, post-operative Dukes stage, time to first passage of flatus and post-operative hospital stay were recorded. The levels of hypersensitive C reactive protein (hsCRP) and tumour necrosis factor-α (TNF-α) in serum and abdominal exudate were measured by ELISA at the time of pre-operative 2 h and post-operative 6 h and 24 h. Results: There was no significant difference in age, sex, Dukes stage and pre-operative inflammatory mediators between the two groups (P > 0.05). The operation time, intraoperative blood loss, time to first passage of flatus and post-operative hospital stay were significantly better in laparoscopic group than those in open operation group. At 6 h and 24 h after operation, the levels of hsCRP and TNF-α in serum and abdominal exudate in laparoscopic group were significantly lower than those in open operation group. Conclusions: Laparoscopic surgery for the treatment of right colon carcinoma has the advantages of fewer traumas, less systemic and local inflammatory response, rapider post-operative recovery and shorter hospital stay. It is worthy of clinical application.

Type 2 diabetes, a global health concern has been considered as major risk factor for cardiovascular diseases. Hinokinin, an emerging bioactive lignin, is reported to show wide range of pharmacological activities. However, the protective role and mechanisms of Hinokinin against type 2 diabetes-mediated cardiotoxicity are still remains unknown. An experimental type 2 diabetic mice model was created by treating animals with high fat diet for four weeks and intraperitoneal injection of streptozotocin (35 mg/kg body weight). Post-type 2 diabetic induction, animals orally treated with Hinokinin (20 or 40 mg/kg body weight) for six weeks. The type 2 diabetic mice exhibited a rise in blood glucose level as well as glycated hemoglobin (HbA1c %), decrease in weekly body weights, decrease in food intake, reduction in absolute heart weight, fall in serum insulin level with altered lipid profile and cardiac functional damage. Diabetic mice treated with Hinokinin attenuated hyperglycemia, dyslipidemia and cardiac dysfunction. In addition, Hinokinin ameliorated histological alterations, fibrosis and glycated proteins in HFD/STZ-induced mice. Type 2 diabetic condition in mice exacerbated oxidative stress, inflammatory status and apoptosis. Hinokinin treatment significantly assuaged oxidative stress, inflammation and apoptosis and elevated antioxidant defenses in diabetic heart. The underlying mechanisms for such mitigation involved the modulation of Nrf2/Keap1/ARE pathway, MAPKs (JNK, p38 and ERK 1/2) and TLR4/MyD88/NF-κB mediated inflammatory pathways and mitochondrial-dependent (intrinsic) apoptosis pathway. In conclusion, the results of this study provided clear evidence that Hinokinin protects against HFD/STZ (type 2 diabetes)-induced cardiac injury by alleviating oxidative stress, inflammation and apoptosis.

Cutting-edge technologies of stretchable, skin-mountable, and wearable electronics have attracted tremendous attention recently due to their very wide applications and promising performances. One direction of particular interest is to investigate novel properties in stretchable electronics by exploring multifunctional materials. Here, we report an integrated strain sensing system that is highly stretchable, rehealable, fully recyclable, and reconfigurable. This system consists of dynamic covalent thermoset polyimine as the moldable substrate and encapsulation, eutectic liquid metal alloy as the strain sensing unit and interconnects, and off-the-shelf chip components for measuring and magnifying functions. The device can be attached on different parts of the human body for accurately monitoring joint motion and respiration. Such a strain sensing system provides a reliable, economical, and ecofriendly solution to wearable technologies, with wide applications in health care, prosthetics, robotics, and biomedical devices.

Abstract Background Studies have reported the impact of chronic childhood and adolescent tic disorder (TD) on families. However, few researches focused on the relationship between family environment and diagnosis of TD. We aim to assess the influence of couple relationship and family structure on the onset of TD. Methods A total of 660 parents of patients with TD (aged 6–12 years) and 641 parents of controls completed questionnaires. Couple relationship and family structure were selected by regression of binary logistic analysis as the risk factors. Couple relationship was divided into the harmonious, common, hostile, and divorced. Family structure included unconventional family, nuclear family, and unite family. Multivariate correspondence analysis was designed to explore relationships among categorical variables of couple relationship and family structure. Results There were significant associations between TD and couple relationship (Exp B = 1.310, p = .006, 95% CI = 1.080–1.590), family structure (Exp B = 0.668, p = .001, 95% CI = 0.526 ~ 0.847), gender (Exp B = 0.194, p

In recent years, Internet of things (IoT) devices are playing an important role in business, education, medical as well as in other fields. Devices connected to the Internet is much more than the number of world population. However, it may face all kinds of attacks from the Internet easily for its accessibility. As we all know, most attacks against IoT devices are based on Web applications. So protecting the security of Web services can effectively improve the situation of IoT ecosystem. Conventional Web attack detection methods highly rely on samples, and artificial intelligence detection results are uninterpretable. Hence, this article introduced a supervised detection algorithm based on benign samples. Seq2Seq algorithm is been chosen and applied to detect malicious web requests. Meanwhile, the attention mechanism is introduced to label the attack payload and highlight labeling abnormal characters. The results of experiments show that on the premise of training a benign sample, the precision of proposed model is 97.02%, and the recall is 97.60%. It explains that the model can detect Web attack requests effectively. Simultaneously, the model can label attack payload visually and make the model “interpretable.”

Abstract Overcoming multidrug resistance has always been a major challenge in cancer treatment. Recent evidence suggested epithelial-mesenchymal transition plays a role in MDR, but the mechanism behind this link remains unclear. We found that the expression of multiple ABC transporters was elevated in concordance with an increased drug efflux in cancer cells during EMT. The metastasis-related angiopoietin-like 4 (ANGPTL4) elevates cellular ATP to transcriptionally upregulate ABC transporters expression via the Myc and NF-κB signaling pathways. ANGPTL4 deficiency reduced IC50 of anti-tumor drugs and enhanced apoptosis of cancer cells. In vivo suppression of ANGPTL4 led to higher accumulation of cisplatin-DNA adducts in primary and metastasized tumors, and a reduced metastatic tumor load. ANGPTL4 empowered cancer cells metabolic flexibility during EMT, securing ample cellular energy that fuels multiple ABC transporters to confer EMT-mediated chemoresistance. It suggests that metabolic strategies aimed at suppressing ABC transporters along with energy deprivation of EMT cancer cells may overcome drug resistance.