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Abstract This study investigated a data augmentation method for plant disease classification and early diagnosis based on a generative adversarial neural network (GAN). In the development of classification models using deep learning, data imbalance is a primary factor that reduces classification performance. To address this issue, tomato disease images from the public dataset PlantVillage were used to evaluate the performance of the GauGAN algorithm. The images generated by the proposed GauGAN model were used to train a MobileNet‐based classification model and compared with methods trained with conventional data augmentation techniques and cut‐mix and mix‐up algorithms. The experimental results demonstrate that based on F1‐scores, GauGAN‐based data augmentation outperformed conventional methods by more than 10%. In addition, after the model was retrained on data collected in the field, it efficiently generated various disease images. The evaluation results from those images also revealed a data augmentation effect of about 10% compared with traditional augmentation techniques.

Abstract Human action understanding (HAU) is a broad topic that involves specific tasks, such as action localisation, recognition, and assessment. However, most popular HAU datasets are bound to one task based on particular actions. Combining different but relevant HAU tasks to establish a unified action understanding system is challenging due to the disparate actions across datasets. A large‐scale and comprehensive benchmark, namely SkatingVerse is constructed for action recognition, segmentation, proposal, and assessment. SkatingVerse focus on fine‐grained sport action, hence figure skating is chosen as the task object, which eliminates the biases of the object, scene, and space that exist in most previous datasets. In addition, skating actions have inherent complexity and similarity, which is an enormous challenge for current algorithms. A total of 1687 official figure skating competition videos was collected with a total of 184.4 h, exceeding four times over other datasets with a similar topic. SkatingVerse enables to formulate a unified task to output fine‐grained human action classification and assessment results from a raw figure skating competition video. In addition, SkatingVerse can facilitate the study of HAU foundation model due to its large scale and abundant categories. Moreover, image modality is incorporated for human pose estimation task into SkatingVerse. Extensive experimental results show that (1) SkatingVerse significantly helps the training and evaluation of HAU methods, (2) the performance of existing HAU methods has much room to improve, and SkatingVerse helps to reduce such gaps, and (3) unifying relevant tasks in HAU through a uniform dataset can facilitate more practical applications. SkatingVerse will be publicly available to facilitate further studies on relevant problems.

ABSTRACT The research proposes a hybrid algorithm model that combines model‐driven and data‐driven approaches for the direct application of bridge health monitoring technology in bridge management. This comprehensive study encompasses a series of analytical techniques and methodologies to build a multi‐objective optimization model for bridge performance assessment and prediction. It focuses on the processing of multi‐source heterogeneous data, selection of key sub‐parameters using Principal Component Analysis (PCA), enhanced K‐means clustering analysis, determination of structural component target thresholds, time‐dependent survival probability analysis, regression fitting, and timing prediction of the bridge system for both the components of double‐layer truss arch bridge and the bridge system. The initial phase of the study concentrates on the diversification and decentralization of monitored data from various sources, integrating and cleaning data obtained from different sources to ensure data quality and consistency. PCA technique is applied to identify key sub‐parameters that have significant impacts on the performance of structural components. Enhanced K‐means clustering analysis is carried out to effectively group and classify the identified key sub‐parameters. Numerical simulations, including structural nonlinear analysis, are conducted to determine the target thresholds of bridge structure, providing important benchmarks for performance evaluation. Finally, a multi‐parameter regression model is used to evaluate and update the performance of the bridge structure, taking into account survival probability (using the Kaplan–Meier method), maintenance history, and material deterioration to estimate the most critical time for the bridge system. A case study is conducted to validate the suggested comprehensive algorithms for a double‐layer truss arch combination bridge, which contributes to enhancing performance evaluation and predicting the most critical time for structural components and bridge system in the bridge management and maintenance practices. It should not be ignored that, the accuracy and reasonability of bridge structure system performance evaluation and prediction depend largely on the selection of target thresholds.

The lack of a sufficient and efficient way to simultaneously perceive general underwater mechanical stimuli, physical contact, and fluidic flow has been a bottleneck for many aquatic applications. To address this challenge, dynamics‐oriented underwater mechanoreceptor interface (DOUMI), a bioinspired mechanoreception system that realizes simultaneous contact and flow perception using a single receptor, is introduced. This receptor, response‐elevated‐and‐expanded hair‐like tactile mechanoreceptor (REEM), is inspired by the mechanoreceptive mechanism of aquatic arthropods. REEM combines structural features from different mechanoreceptive sensilla, enabling it to capture a wide range of stimulus dynamics. Under different stimuli, REEM encodes stimuli dynamics as its oscillations with distinct spectral attributes. Those oscillations are efficiently transferred through mechanical processes and imaging, enabling vision‐based extraction and further analysis. Therefore, by evaluating the oscillation dynamics with tailored wavelet‐based indices, DOUMI can distinguish between contact‐ and flow‐induced oscillations at each receptor unit with 90.5% accuracy. Furthermore, DOUMI provides comprehensive 2D mechanoreception with a scalable array of REEMs, delivering capabilities like stimuli spatiotemporal visualization, flow trend detection, and scenario classification with an accuracy of 99.5%. With its robustness and operational efficiency in underwater environments, DOUMI can be easily adapted to existing applications using common materials and hardware, establishing a new, streamlined paradigm for underwater general mechanoreception.

Abstract The endometrium, the inner lining of the uterus, assumes a crucial role in the female reproductive system. Disorders and injuries impacting the endometrium can lead to profound consequences, including infertility and compromised women's overall health. Recent advancements in stem cell research have opened new possibilities for the treatment and repair of endometrial issues. In the present study, we constructed a degradable hydrogel by loading adipose‐derived stem cells (ADSCs) and melanin nanoparticles (MNP). In vitro cell experiments validated the biocompatibility of the prepared hydrogels and their adeptness in encapsulating ADSCs. Subsequently, we explored the impact of hydrogel@ADSC@MNP constructs in the healing process of uterine injury in mice. The results indicated that hydrogel@ADSC@MNP could augment endometrial thickness and ameliorate endometrial interstitial fibrosis. The injured tissue adjacent to hydrogel@ADSC@MNP constructs exhibited higher levels of bFGF, IGF‐1, and VEGFA compared with the corresponding tissue in mice receiving hydrogel constructs alone or in the model group. Furthermore, the hydrogel@ADSC@MNP system enhanced the proliferative capabilities of uterine endometrial cells, facilitated microvasculature regeneration, and reinstated the endometrium's capacity to receive the embryos. Our findings strongly suggest that the hydrogel@ADSC@MNP system holds significant promise for repairing and regenerating damaged endometrium.

Abstract Taking a rear‐wheel drive pure electric vehicle as the research object, considering the safety during braking and improving energy recovery rate, a study was conducted on the distribution strategy of front and rear axle braking force. During the braking process, the feedback braking force of the motor and the hydraulic braking force with an electronic stability controller (ESC) were coordinated and controlled, to ensure that the total required braking force was met. A fuzzy logic controller has been designed, with three variables of battery state of charge, vehicle speed, and braking intensity as inputs, and a modified motor braking ratio as output variable to prevent wheel lockup. Using Cruise software, a co‐simulation model was established with Amesim and Simulink, and simulation validation was conducted on the braking process and cycling conditions. The simulation results showed that the brake recovery strategy based on fuzzy control can effectively improve the vehicle's control performance and energy recovery rate compared to the Economic Commission of Europe regulation. The NEDC (New European Driving Cycle) working condition improved by 10.41% and the CLTC‐P (China Light‐duty Vehicle Test Cycle‐passenger) working condition improved by 10.57%. Effectively improving power consumption per 100 km, NEDC decreased by 1.81% and CLTC‐P decreased by 2.62%.

Abstract The Yunnan‐Guizhou Plateau (YGP) is characterized by the distinctive isolated habitat of the limestone Karst Islands and features the Wumeng Mountains, which divide the YGP into the two Plateaus of Yunnan and Guizhou. This study aimed to assess the effects of geographic isolation and past climate fluctuation on the distribution of flora in the YGP. To achieve this, we carried out the phylogeographical pattern and genetic structure based on chloroplast and nuclear ribosomal DNA sequence in relation to past (Last Glacial Maximum) and present distributions based on ecological niche modeling for Morella nana, an important wild plant resource and endemic to the YGP once considered a vulnerable species. The results suggest that the genetic and chlorotype network structures of M. nana are divided into at least two groups: cpDNA chlorotype H2 (or dominant nrDNA haplotypes h1 and h2), distributed primarily to the east of the Wumeng Mountains, and cpDNA chlorotypes H1 and H3–H10 (or dominant nrDNA haplotype h2 and h3), distributed to the west of the Wumeng Mountains. A deep genetic split was noted within the two groups to reach 25 steps, especially for the cpDNA fragment variation. This east–west divergence reveals the existence of a natural geographical isolation boundary in the form of the Wumeng Mountains, and supports the existence of at least two glacial refuges during the Quaternary glacial period, along with two genetic diversity center, and at least two large geographic protection units for the important species of M. nana. This study indicates that the phylogeographical pattern of M. nana can be attributed to geographic/environmental isolation caused by the Wumeng Mountains and climate fluctuation during the last glacial maximum, and proposes an effective strategy to protecting this important plant resource.

Abstract Targeting ferroptosis has attracted exponential attention to eradicate cancer cells with high iron‐dependent growth. Increasing the level of intracellular labile iron pool via small molecules and iron‐containing nanomaterials is an effective approach to induce ferroptosis but often faces insufficient efficacy due to the fast drug metabolism and toxicity issues on normal tissues. Therefore, developing a long‐acting and selective approach to regulate ferroptosis is highly demanded in cancer treatment. Herein, a lysosome‐targeted magnetic nanotorquer (T7‐MNT) is proposed as the mechanical tool to dynamically induce the endogenous Fe2+ pool outbreak for ferroptosis of breast cancer. T7‐MNTs target lysosomes via the transferrin receptor‐mediated endocytosis in breast cancer cells. Under the programmed rotating magnetic field, T7‐MNTs generate torques to trigger endogenous Fe2+ release by disrupting the lysosomal membrane. This magneto‐mechanical manipulation can induce oxidative damage and antioxidant defense imbalance to boost frequency‐ and time‐dependent lipid peroxidization. Importantly, in vivo studies show that T7‐MNTs can efficiently trigger ferroptosis under the magnetic field and play as a long‐acting physical inducer to boost ferrotherapy efficacy in combination with RSL3. It is anticipated that this dynamic targeted strategy can be coupled with current ferroptosis inducers to achieve enhanced efficacy and inspire the design of mechanical‐based ferroptosis inducers for cancer treatment.

Introduction. To evaluate the changes of lens antidilatation, antiedema, and antienzymolysis ability after different concentrations of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysuccinimide (EDC-NHS)-induced collagen cross-linking. Methods. Corneal stromal lenticules (n = 100) obtained from small incision lenticule extraction (SMILE) procedures were divided into 5 groups: no treatment (control); EDC/NHS (5%/2.5%); EDC/NHS(5%/5%); EDC/NHS (10%/5%); riboflavin and ultraviolet-A light (UVA). Collagen crosslinking was induced using EDC-NHS and UVA. Biomechanical assessments including inflation test, enzymatic degradation resistance, and light transmittance were evaluated posttreatment. Results. (1) Lenticule apex displacement ranked: control Group > UVA Group > Group (5%/5%) > Group (5%/2.5%) > Group (10%/5%) (Friedman test, p

Abstract Although the incidence and death rates of gastric cancer (GC) are decreasing, approximately one million new cases and 800,000 GC‐related deaths were reported worldwide in 2018. Currently, the oncogenesis of GC remains unclear, and the demand for novel treatment options are unmet. Here, we explored the role of aldo‐keto reductase family 1 member B (AKR1B1) in the progression of GC. The proliferation, migration, and invasion of GC cells were evaluated by CCK‐8 assay, wound healing assay, and transwell assay, respectively. The interaction between EBF transcription factor 1 (EBF1) and the promoter region of AKR1B1 was determined by luciferase reporter assay and chromatin immunoprecipitation (ChIP). Gene expression levels were measured by quantitative real‐time polymerase chain reaction (qRT‐PCR) and Western blotting assay. The expression of AKR1B1 was elevated in GC cells, resulting in increased cell proliferation, migration, and invasion. Meanwhile, EBF1 was a negative regulator of AKR1B1; its overexpression suppressed AKR1B1 expression and GC progression. Furthermore, knockdown of ZNF521 induced EBF1 expression, thus suppressing AKR1B1 expression and resulting in attenuated GC growth and invasiveness. Notably, knockdown of ZNF521 attenuated GC progression and was rescued by overexpression of AKR1B1. Our current study revealed a novel ZNF521/EBF1/AKR1B1 axis in GC and elaborated its important role in promoting GC progression, providing potential therapeutic targets for anti‐GC treatments.

Abstract The conformal integration of the electronic skin on the non‐developable surface is in great demand for the comprehensive tactile sensing of robotics and prosthetics. However, the current techniques still encounter obstacles in achieving conformal integration of film‐like electronic skin on non‐developable surfaces with substantial curvatures for contact pressure detection and tactile mapping. In this paper, by utilizing the 3D printing technology to prepare the 3D electrode array in the structural component following its surface curvature, and covering it with a molded functional shell to form the pressure sensitive iontronic interface, a device is proposed to achieve high‐sensitive pressure detection and high‐fidelity tactile mapping on a complicated non‐developable surface, called structural electronic skin (SES). The SES is prepared in a 3D printed fingertip with 46 tactile sensing units distributed on its curved surface, achieving the integration of both structural and tactile functions in a single component. By integrating the smart fingertip into a dexterous hand, a series of demonstrations are presented to show the dead‐zone free pressure detection and tactile mapping with high sensitivity, for instance, 2D pulse wave monitoring and robotic injection in a medical robot, object recognition and compliant control in a smart prosthesis.

Abstract “Land radiative management” (LRM)—intentionally increasing land surface albedo to reduce regional temperatures—has been proposed as a form of geoengineering. Its effects on local precipitation and soil moisture over long timescales are not well understood. We use idealized cloud‐permitting simulations and a conceptual model to understand the response of precipitation and soil moisture to a mesoscale albedo anomaly at equilibrium. Initially, differential heating between a high‐albedo anomaly and the lower‐albedo surrounding environment drives mesoscale circulations, increasing precipitation and soil moisture in the surrounding environment. However, over time, increasing soil moisture reduces the differential heating, eliminating the mesoscale circulations. At equilibrium, the fractional increase in simulated soil moisture is up to 1.3 times the fractional increase in co‐albedo (one minus albedo). Thus, LRM may increase precipitation and soil moisture in surrounding regions, enhancing evaporative cooling and spreading the benefits of LRM over a wider region than previously recognized.

Abstract Deforestation, urbanization and construction of wind farms can change the land surface roughness, which can further influence surface heat fluxes and thus weather and climate. Land surface roughness anomalies can dynamically trigger convergence through changing mean wind speed. Here, we report a new mechanism, in which roughness anomalies cause thermally direct mesoscale circulations and anomalous precipitation. To study this mechanism, we conduct cloud‐permitting simulations over an idealized land surface with prescribed surface roughness anomalies. Anomalously high roughness increases turbulent mixing near the surface, which decreases land surface temperature and outgoing longwave radiation. The additional surface net radiation partly goes into greater sensible heat flux, which triggers mesoscale circulations driven by differential heating. As a result, precipitation over the high‐roughness anomaly is generally larger than that over the low‐roughness background. This new mechanism, not present in climate models, may be relevant to storm formation over wind farms, cities and forests.

Abstract Substantial progress has been made in the understanding of gas‐involving electrochemical reactions recently for the sake of clean, renewable, and efficient energy technologies. However, the specific influence mechanism of the microenvironment at the reaction interface on the electrocatalytic performance (activity, selectivity, and durability) remains unclear. Here, we provide a comprehensive understanding of the interfacial microenvironment of gas‐involving electrocatalysis, including carbon dioxide reduction reaction and nitrogen reduction reaction, and classify the factors affecting the reaction thermodynamics and kinetics into gas diffusion, proton supply, and electron transfer. This categorization allows a systematic survey of the literature focusing on electrolyzer‐level (optimization of the device, control of the experimental condition, and design of the working electrode), electrolyte‐level (increase of gas solubility, regulation of proton supply, and substitution of anodic reaction), and electrocatalyst‐level strategies (promotion of gas affinity, adjustment of hydrophobicity, and enhancement of conductivity), aiming to retrieve the correlations between the microenvironment and electrochemical performance. Finally, priorities for future studies are suggested to support the comprehensive improvement of next‐generation gas‐involving electrochemical reactions.

Abstract To obtain high accuracy and efficiency in the simulations, an optimum time step should be taken in finite‐difference time‐domain (FDTD) methods. The authors investigated how time steps impact on numerical dispersion of two FDTD methods including the FDTD(2,2) method and the FDTD(2,4) method. Through rigorously analytical and numerical analysis, it is found that small time steps of the FDTD methods do not always have small numerical errors. Our findings reveal that these two FDTD methods present different behaviours with respect to time steps: (1) for the FDTD(2,2) method, smaller time steps limited by the Courant‐Friedrichs‐Lewy condition increase numerical dispersion and lead to larger simulation errors and (2) for the FDTD(2,4) method, as the time step increases, numerical dispersion errors first decrease and then increase. Our findings are also comprehensively validated from one‐ to three‐dimensional cases through several numerical examples including wave propagation, resonant frequencies of cavities and a practical engineering problem.

Abstract Electrohydrodynamic (EHD) printing has great potential to be used in the field of electronic industry, precision optics and biological engineering. However, it is still a challenge to achieve a high scaling ratio for line patterns production by EHD jet printing technique, which can effectively prevent the needles to be blocked. In this paper, the influence of the key process parameters on the line width of EHD jet printing was investigated. The printing needle with the inner diameter of 890 μm was used, and the line with width of 3.02 μm was printed by optimizing the parameters. The scaling ratio between the needle inner diameter and the printed line width was up to 295 times. At the same time, the function model between the flow rate and printed line width of PVP/PEO composite was deduced. The error was found to be less than 1% by the verification of experiments. By utilizing this model, the printed line width can be predicted by controlling the flow rate, which will greatly improve the work efficiency. By controlling the flow rate, the goal of printing on demand can be realized. The proposed method and model can provide support for the fabrication of micro‐nano scale structure.

Abstract Osteoarthritis (OA) is a degenerative disease that involves excess reactive oxygen species (ROS) and osteochondral defects. Although multiple approaches have been developed for osteochondral regeneration, how to balance the biochemical and physical microenvironment in OA remains a big challenge. In this study, a bioceramic scaffold by 3D printed akermanite (AKT) integrated with hair‐derived antioxidative nanoparticles (HNPs)/microparticles (HMPs) for ROS scavenging and osteochondral regeneration has been developed. The prepared bioscaffold with multi‐mimetic enzyme effects, which can scavenge a broad spectrum of free radicals in OA, can protect chondrocytes under the ROS microenvironment. Importantly, the bioscaffold can distinctly stimulate the proliferation and maturation of chondrocytes due to the stimulation of the glucose transporter pathway (GLUT) via HNPs/HMPs. Furthermore, it significantly accelerated osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). In vivo results showed that the bioscaffold can effectively enhance the osteochondral regeneration compared to the unmodified scaffold. The work shows that integration of antioxidant and mechanical properties via the bioscaffold is a promising strategy for osteochondral regeneration in OA treatment.

Background. Assays of transposase accessible chromatin sequencing (ATAC-seq) is an efficient assay to investigate chromatin accessibility, which depends on the activity of a robust Tn5 transposase to fragment the genome while cutting in the sequencing adapters. Methods. We propose reliable approaches for purifying hyperactive Tn5 transposase by chitin magnetic bead sorting. Double-stranded DNA of J76 cells and 293T cells were digested and subjected to tagmentation as test samples with Tn5 transposase, and libraries were established and sequenced. Sequencing data was then analyzed for peak calling, GO enrichment, and motif analysis. Results. We report a set of rapid, efficient, and low-cost methods for ATAC-seq library construction and data analysis, through large-scale and rapid sequencing. These methods can provide a reference for the study of epigenetic regulation of gene expression.

Abstract Objective The paper characterizes outpatient communication in a major cancer hospital in southern China with regard to the structure, style and focus of doctor–patient communication. Method Fifty‐one encounters between doctors and patients were recorded in the outpatient department of the cancer hospital and analysed inductively to identify patterns of doctor–patient outpatient communication. Results Outpatient communication in the cancer hospital is characterized by structuralized conversation, doctor domination of the conversation and a focus on technology during communication. These characteristics suggest an extreme inequality of power between Chinese doctors and patients at the individual level. They are also shaped by the institutional environment of Chinese hospitals. Discussion Measures should be taken at both the interpersonal and institutional level to improve doctor–patient communication. At the micro‐interpersonal level, public education and professional skills training are needed to improve communication and promote mutual understanding between patients and doctors. At the macro‐institutional level, changes are needed in terms of transforming the structural factors that shape doctor–patient communication. Conclusions Structuralized conversation, doctor domination of the conversation and a focus on technology during outpatient encounters present challenges to effective doctor–patient communication. These patterns are shaped by the institutional environment of Chinese hospitals and suggest the extreme power imbalance between Chinese doctors and patients.

Abstract Objective This study aims to investigate the burden of family caregivers of patients with schizophrenia, and its influencing factors Methods A total of 105 patients with schizophrenia and their caregivers were investigated using the positive and negative symptom scale (PANSS) and family burden scale of disease (FBS) Results There was a strong correlation between the patient's recovery and family burden, especially between positive and negative symptoms and family financial burden, family daily activities, family recreational activities, and family relationship Conclusion There is a strong correlation between the patient's recovery and family burden, and this is especially correlated to family economic burden, family daily activities, family recreational activities, and family relationship. Medical staff should pay attention to the psychological characteristics of patients and fully understand and avoid the adverse effects of family burden on the rehabilitation of patients.

Universal distinct element code (UDEC) is a simulation software based on the discrete element method, widely used in geotechnical mining. However, in the UDEC, when simulating large-scale excavation, the subsidence of the fractured zone is almost equal to the mining height, which makes the deformation value calculated in the study of gob-side entry retention too large. To solve this problem, in this paper, the double-yield constitutive model is applied to the whole caving zone to analyze the deformation and failure characteristics of surrounding rock along gob-side entry retaining by roof cutting. The results of the simulation are in good agreement with the result of drilling peeking (drilling observation by borehole televiewer) and field condition (observation and measurement in the field). Finally, by using this numerical method, the effects of roadway width, temporary support, and coal side support on the failure of the roof and the arc coal side are studied.

Abstract Reactive oxygen species (ROS), a group of oxygen derived radicals and derivatives, can induce cancer cell death via elevated oxidative stress. A spatiotemporal approach with safe and deep‐tissue penetration capabilities to elevate the intracellular ROS level is highly desirable for precise cancer treatment. Here, a mechanical‐thermal induction therapy (MTIT) strategy is developed for a programmable increase of ROS levels in cancer cells via assembly of magnetic nanocubes integrated with alternating magnetic fields. The magneto‐based mechanical and thermal stimuli can disrupt the lysosomes, which sequentially induce the dysfunction of mitochondria. Importantly, intracellular ROS concentrations are responsive to the magneto‐triggers and play a key role for synergistic cancer treatment. In vivo experiments reveal the effectiveness of MTIT for efficient eradication of glioma and breast cancer. By remote control of the force and heat using magnetic nanocubes, MTIT is a promising physical approach to trigger the biochemical responses for precise cancer treatment.

The nutrient compositions and in vitro antioxidant activities of water-soluble extract from Lactobacillus plantarum DY-1 fermented wheat germ and its effect on the lipid oxidation and texture properties of emulsified sausages were investigated. The optimal hydroxyl radical scavenging capacity of 72.8 ± 2.9% was demonstrated for fermented wheat germ extract (FWGE) by terms of the fermentation conditions as follows: fermentation time of 26 h, fermentation temperature of 35°C, initial pH of 3.0, solid to liquid ratio of 1/10, and inoculum amount of 0.48 g. The enhancement in FWGE content could improve the oxidation stability of emulsified sausages by retarding the formation of thiobarbituric acid-reactive substances (TBARSs) during 7 days of storage at 4°C. However, a higher FWGE content (2.14%) resulted in 78% of increase in cooking loss (p

Principal component analysis (PCA) was used to cluster the possible amino acid compositions of antioxidant peptides in potato protein hydrolysate (PPH). The antioxidant peptides exhibiting high ABTS+• scavenging capacity were isolated with the procedure of ultrafiltration, gel filtration, and preparative RP-HPLC and identified by UPLC-MS/MS. Phe, Tyr, and His were shown to group together with ABTS+• scavenging capacity in component matrix plot. Three prominent peptides, namely, Phe-Tyr, Tyr-Phe-Glu, and Pro-Pro-His-Tyr-Phe, which matched the sequence of patatin and were made up of Phe and Tyr, were identified. The peptide Tyr-Phe-Glu demonstrated antioxidant activity against Caco-2 cell oxidation induced by H2O2. The results suggested that multivariate analysis could be used to predict the amino acid compositions of antioxidant peptides.

Background. Progressive β-cell dysfunction, a major characteristic of type 2 diabetes (T2D), is closely related to the infiltration of inflammatory macrophages within islets. Mesenchymal stem cells (MSCs) have been identified to alleviate β-cell dysfunction by modulating macrophage phenotype in T2D, but the restoration of β-cells by a single MSC infusion is relatively transient. Decitabine (DAC) has been reported to polarize macrophages towards the anti-inflammatory phenotype at low doses. We therefore investigated whether low-dose decitabine could enhance the antidiabetic effect of MSCs and further promote the restoration of β-cell function. Methods. We induced a T2D mice model by high-fat diets and streptozotocin (STZ) injection. Mice were divided into five groups: the normal group, the T2D group, the DAC group, the MSC group, and the MSC plus DAC group (MD group). We examined the blood glucose and serum insulin levels of mice 1, 2, and 4 weeks after MSC and/or DAC treatment. Dynamic changes in islets and the phenotype of intraislet macrophages were detected via immunofluorescence. In vitro, we explored the effect of MSCs and DAC on macrophage polarization. Results. The blood glucose and serum insulin levels revealed that DAC prolonged the antidiabetic effect of MSCs to 4 weeks in T2D mice. Immunofluorescence staining demonstrated more sustainable morphological and structural amelioration in islets of the MD group than in the MSC group. Interestingly, further analysis showed more alternatively activated macrophages (M2, anti-inflammatory) and fewer classically activated macrophages (M1, proinflammatory) in islets of the MD group 4 weeks after treatment. An in vitro study demonstrated that DAC together with MSCs further polarized macrophages from the M1 to M2 phenotype via the PI3K/AKT pathway. Conclusion. These data unveiled that DAC prolonged the antidiabetic effect of MSCs and promoted sustainable β-cell restoration, possibly by modulating the macrophage phenotype. Our results offer a preferable therapeutic strategy for T2D.

Nonalcoholic fatty liver disease (NAFLD) is increasingly common among patients with type 2 diabetes mellitus (T2DM). The two conditions can act synergistically to produce adverse outcomes. However, the therapeutic options for patients with NAFLD and T2DM are currently limited. Human umbilical cord-derived mesenchymal stem cells (UC-MSCs) have shown therapeutic potential for diabetes and hepatic disorders such as liver cirrhosis and fulminant hepatic failure. The present study is aimed at investigating the effect of human UC-MSCs on a mouse model of NAFLD and T2DM, characterized by obesity-induced hyperglycaemia, dyslipidaemia, hepatic steatosis, and liver dysfunction. Thirty-week-old male C57BL/6 db/db mice were infused with human UC-MSCs or phosphate-buffered saline (PBS) via the tail vein once a week for six weeks. Age-matched male C57BL/6 wild-type db/+ mice were used as controls. Body weight and random blood glucose were measured every week. One week after the sixth infusion, intraperitoneal glucose tolerance tests and insulin tolerance tests were performed and the blood and liver were harvested for biochemical and histopathological examinations. Quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR), immunofluorescence staining, and western blot were performed to monitor the expression of the lipid metabolism- and regulatory pathway-related genes. UC-MSC infusions significantly ameliorated hyperglycaemia, attenuated the elevation of hepatic transaminases, and decreased lipid contents, including triglyceride, total cholesterol, and low-density lipoprotein cholesterol. Moreover, histological lesions in the liver diminished markedly, as evidenced by reduced lipid accumulation and attenuated hepatic steatosis. Mechanistically, UC-MSCs were found to regulate lipid metabolism by increasing the expression of fatty acid oxidation-related genes and inhibiting the expression of lipogenesis-related genes, which were associated with the upregulation of the HNF4α-CES2 pathway. Our results demonstrate that human UC-MSCs can ameliorate NAFLD and reverse metabolic syndrome in db/db mice. Thus, UC-MSCs may serve as a novel therapeutic agent for T2DM patients with NAFLD.

This paper proposes a tension-compression damage model for concrete materials, formulated within the framework of thermodynamics of irreversible processes. The aim of this work is to solve the following problems: the premature divergence of numerical solutions under general loading conditions due to the conflict of tensile and compressive damage bounding surfaces, which is a result of the application of the spectral decomposition method to distinguish tension and compression, and the unsatisfactory reproduction of distinct tension-compression behaviors of concrete by strain-driven damage models. The former is solved by the sign of the volumetric deformation, while the latter is solved via two separated dissipation mechanisms. Moreover, of specific interest is an improved solution to the problem of mesh-size dependency using consistent crack bandwidths, which takes into account situations with irregular meshes and arbitrary crack directions in the context of the crack band approach. The performance of the model is validated by the well-documented experimental data. The simplicity and the explicit integration of the constitutive equations render the model well suitable for large-scale computations.

Quasi-linear autoregressive with exogenous inputs (Quasi-ARX) models have received considerable attention for their usefulness in nonlinear system identification and control. In this paper, identification methods of quasi-ARX type models are reviewed and categorized in three main groups, and a two-step learning approach is proposed as an extension of the parameter-classified methods to identify the quasi-ARX radial basis function network (RBFN) model. Firstly, a clustering method is utilized to provide statistical properties of the dataset for determining the parameters nonlinear to the model, which are interpreted meaningfully in the sense of interpolation parameters of a local linear model. Secondly, support vector regression is used to estimate the parameters linear to the model; meanwhile, an explicit kernel mapping is given in terms of the nonlinear parameter identification procedure, in which the model is transformed from the nonlinear-in-nature to the linear-in-parameter. Numerical and real cases are carried out finally to demonstrate the effectiveness and generalization ability of the proposed method.