ADP-based online compensation hierarchical sliding-mode control for partially unknown switched nonlinear systems with actuator failures.

This article investigates an adaptive dynamic programming-based online compensation hierarchical sliding-mode control problem for a class of partially unknown switched nonlinear systems with actuator failures and uncertain perturbations under an identifier-critic neural networks architecture. Firstly, by introducing a cost function related to hierarchical sliding-mode surfaces for the nominal system, the original control problem is equivalently converted into an optimal control problem. To obtain this optimal control policy, the Hamilton-Jacobi-Bellman equation is solved through an adaptive dynamic programming method. Compared with conventional adaptive dynamic programming methods, the identifier-critic network architecture not only overcomes the limitation on the unknown internal dynamic but also eliminates the approximation error arising from the actor network. The weights in the critic network are tuned via the gradient descent approach and the experience replay technology, such that the persistence of excitation condition can be relaxed. Then, a compensation term containing hierarchical sliding-mode surfaces is used to offset uncertain actuator failures without the fault detection and isolation unit. Based on the Lyapunov stability theory, all states of the closed-loop nonlinear system are stable in the sense of uniformly ultimately boundedness. Finally, numerical and practical examples are given to demonstrate the effectiveness of our presented online compensation control strategy.

A predictive model for stunting among children under the age of three.

Background: In light of the global effort to eradicate stunting in childhood, the objective of this research endeavor was to assess the prevalence of stunting and associated factors, simultaneously construct and validate a risk prediction model for stunting among children under the age of three in Shenzhen, China. Methods: Using the stratified random sampling method, we selected 9,581 children under the age of three for research and analysis. The dataset underwent a random allocation into training and validation sets, adhering to a 8:2 split ratio. Within the training set, a combined approach of LASSO regression analysis and binary logistic regression analysis was implemented to identify and select the predictive variables for the model. Subsequently, model construction was conducted in the training set, encompassing model evaluation, visualization, and internal validation procedures. Finally, to assess the model's generalizability, external validation was performed using the validation set. Results: A total of 684 (7.14%) had phenotypes of stunt. Utilizing a combined approach of LASSO regression and logistic regression, key predictors of stunting among children under three years of age were identified, including sex, age in months, mother's education, father's age, birth order, feeding patterns, delivery mode, average daily parent-child reading time, average time spent in child-parent interactions, and average daily outdoor time. These variables were subsequently employed to develop a comprehensive prediction model for childhood stunting. A nomogram model was constructed based on these factors, demonstrating excellent consistency and accuracy. Calibration curves validated the agreement between the nomogram predictions and actual observations. Furthermore, ROC and DCA analyses indicated the strong predictive performance of the nomograms. Conclusions: The developed model for forecasting stunt risk, which integrates a spectrum of variables. This analytical framework presents actionable intelligence to medical professionals, laying down a foundational framework and a pivot for the conception and execution of preemptive strategies and therapeutic interventions.

Silk protein: A novel antifungal and edible coating for strawberry preservation.

In this study, an antimicrobial component, silk protease inhibitors (SPIs), was extracted from discarded silkworm cocoons, and a suitable degumming method for obtaining regenerated silk fibroin (SF) was screened. An edible antimicrobial coating was prepared by mixing SPIs with SF for evaluation of potential in strawberries preservation. Results demonstrated that SPI could effectively inhibit mycelial growth and spore germination. The alkaline protease method exhibited the highest degumming rate of 24.4 %. The SPI-SF coating exhibited excellent mechanical properties, high water vapor permeability, and easy washability. Within 10 days, seedlings treatment with SPI-SF coating solution showed a germination rate of 94.3 %, and exhibited good biocompatibility with HepG2 cells. Coating with SPI-SF led to increase in the storage period of strawberries to 10-14 days, concurrent with considerable reduction in decay rate at room temperature. Conclusively, this study demonstrates the potential of SPI-SF edible coating in strawberries preservation.

Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.

BACKGROUND: Variations in symptoms and indistinguishable depression episodes of unipolar depression (UD) and bipolar disorder (BD) make the discrimination difficult and time-consuming. For adolescents with high disease prevalence, an efficient diagnostic tool is important for the discrimination and treatment of BU and UD. METHODS: This multi-center cross-sectional study involved 1587 UD and 246 BD adolescents aged 12-18. A combination of standard questionnaires and demographic information was collected for the construction of a full-item list. The unequal patient number was balanced with three data balancing algorithms, and 4 machine learning algorithms were compared for the discrimination ability of UD and BD in three age groups: all ages, 12-15 and 16-18. Random forest (RF) with the highest accuracy were used to rank the importance of features/items and construct the 25-item shortlist. A separate dataset was used for the final performance evaluation with the shortlist, and the discrimination ability for UD and BD was investigated. RESULTS: RF performed the best for UD and BD discrimination in all 3 age groups (AUC 0.88-0.90). The most important features that differentiate UD from BD belong to Parental Bonding Instrument (PBI) and Loneliness Scale of the University of California at Los Angeles (UCLA). With RF and the 25-item shortlist, the diagnostic accuracy can still reach around 80 %, achieving 95 % of the accuracy levels obtained with all features. CONCLUSIONS: Through machine learning algorithms, the most influencing factors for UD and BD classification were recombined and applied for rapid diagnosis. This highly feasible method holds the potential for convenient and accurate diagnosis of young patients in research and clinical practice.

Shiitake mushroom-derived extracellular nanovesicles: Preparation, characterization, and inhibition of Caco-2 cells.

In this study, Shiitake mushroom-derived extracellular nanovesicles (SMDENVs) were isolated from fresh Shiitake mushrooms by ultracentrifugation and sucrose gradient ultracentrifugation. The morphological characteristics of SMDENVs were investigated via Transmission Electron Microscopy and Laser Scanning Confocal Microscopy. SMDENVs were spherical, hollow, and uniform in size, with an average diameter of 177.6 ± 51.4 nm. Based on the analysis of lipidomics and proteomics, 383 lipids species and 1290 proteins were identified in SMDENVs. Compared with the conventional liposomes, SMDENVs demonstrated higher stability in different environmental conditions. Furthermore, we observed that SMDENVs were cytocompatible and inhibited the proliferation of Caco-2 cells. SMDENVs could be phagocytized by Caco-2 cells in a time-dependent manner. Further, SMDENVs also inhibited the proliferation of Caco-2 cells in a dose-dependent manner, and the half-maximal inhibitory concentration (IC50) was 236.2 ± 3.2 µg/mL. Additionally, SMDENVs induced cellular apoptosis by increasing the levels of reactive oxygen species and decreasing the mitochondrial membrane potential.

Unveiling the therapeutic potential and mechanism of inulin in DSS-induced colitis mice.

Inulin has been reported to alleviate colitis. In this study, colitis patients' feces were used to simulate fermentation to demonstrate changes in the microbiota profile in the presence of inulin. We found inulin can reshape the gut microbiota profile of colitis patients, especially by altering the abundance of Faecalibacterium and Blautia. Interestingly, the subsequent co-culture with inulin demonstrated that inulin promoted the growth of these two strains of bacteria. The dextran sodium sulfate (DSS)-induced mouse model was used to examine the effect of inulin and its combination with two probiotics on colitis. Results showed that all three treatments can alleviate the clinical symptoms, including weight-losing, colon-shortening, and the Disease Activity Index (DAI) score. Further investigations showed that the administrations regulate colitis mice's pro- and anti-inflammatory cytokines, such as TNF-α, IL-1ß, IL-6, IL-10, and IL-17. Also, they alter the relative abundance of Faecalibacterium and Blautia, change the short-chain fatty acids (SCFAs) profile in the cecum and colon, and improve the intestinal barrier; specifically, the intervention increased the expressions of Claudin, Occludin, Zonula Occludens (ZO)-1, and Mucin (MUC)-2 in colonic tissues, thus restoring the colonic tissue structure and morphology of colitis mice. Collectively, our results confirm that inulin can alter the colitis patients' characteristic microbial community, and they can ameliorate experimental colitis by inhibiting the TRL4/MyD88/NF-κB signaling pathway-improving the inflammatory response and enhancing the intestinal barrier. In conclusion, we propose that inulin may hold promise as a functional food therapeutic approach for the treatment of colitis.

The Accurate Prediction of Antibody Deamidations by Combining High-Throughput Automated Peptide Mapping and Protein Language Model-Based Deep Learning.

Therapeutic antibodies such as monoclonal antibodies (mAbs), bispecific and multispecific antibodies are pivotal in therapeutic protein development and have transformed disease treatments across various therapeutic areas. The integrity of therapeutic antibodies, however, is compromised by sequence liabilities, notably deamidation, where asparagine (N) and glutamine (Q) residues undergo chemical degradations. Deamidation negatively impacts the efficacy, stability, and safety of diverse classes of antibodies, thus necessitating the critical need for the early and accurate identification of vulnerable sites. In this article, a comprehensive antibody deamidation-specific dataset (n = 2285) of varied modalities was created by using high-throughput automated peptide mapping followed by supervised machine learning to predict the deamidation propensities, as well as the extents, throughout the entire antibody sequences. We propose a novel chimeric deep learning model, integrating protein language model (pLM)-derived embeddings with local sequence information for enhanced deamidation predictions. Remarkably, this model requires only sequence inputs, eliminating the need for laborious feature engineering. Our approach demonstrates state-of-the-art performance, offering a streamlined workflow for high-throughput automated peptide mapping and deamidation prediction, with the potential of broader applicability to other antibody sequence liabilities.

Spatially Separate Center-to-Surround Radiation Structure Induced Tandem Electron Transfer Effect for Stable and Enhanced Photocatalysis.

Spatially separate anchoring redox cocatalysts on the photocatalyst to shunt the charge migration paths is an effective route to regulate the charge flow. Differently, we herein introduce an artificially synthesized Sun-planet-like spatially separated center-to-surround radiation photosensitizer-cocatalyst structure to regulate electron flow in a tandem manner. A single Au sphere acts as the Sun/photosensitizer in the center, and small Pt particles scatter around as the planets/cocatalyst, both of which are fixed inside the MOF crystal. Such a structure can not only simultaneously increase the light harvesting capacity and electron migration kinetics but also optimize the electron transfer pathway to minimize the electron migration distance, so that the hot electrons generated by Au can be quickly transferred to Pt through MOF before annihilation, leading to a significant photoactivity promotion.

Composition and micromorphological determination of blue honeysuckle fruit (Lonicera caerulea L.) cuticular wax and its effects on fruit post-harvest quality.

The chemical composition and structure of the cuticular wax in blue honeysuckle fruit were investigated using gas chromatography-mass spectrometry (GC-MS) and scanning electron microscopy (SEM). The results revealed that the cuticular wax was dense and uniform, taking on a tubular form. A total of 158 wax components were identified, including alkanes, terpenes, ketones, alcohols, fatty acids, and esters. The wax was found to be particularly rich in alkanes. After storage, the wax content decreased, whereas an increase in 1-undecanol. The destruction or reduction of cuticular wax resulted in a more rapid decline in storage quality, loss of nutrients, and a decrease in antioxidant phytochemicals. Meanwhile, wax metabolizing enzyme activity and gene expression increased. This study presents a deeper understanding of blue honeysuckle fruit cuticular wax composition and aids to developing effective measures to delay its postharvest fruit quality deterioration.

The alleviative effects of viable and inactive Lactobacillus paracasei CCFM1120 against alcoholic liver disease via modulation of gut microbiota and the Nrf2/HO-1 and TLR4/MyD88/NF-κB pathways.

Probiotics can alleviate alcoholic liver disease. However, whether inactive counterparts can produce similar outcomes requires further investigation. We investigated the effects of viable (V) and dead (D) Lactobacillus paracasei CCFM1120 on alcohol-induced ALD mice. The results showed that CCFM1120V and D ameliorated the disease symptoms and intestinal injury. Specifically, these interventions strengthened the intestinal barrier, as evidenced by the increased expression of ZO-1 (zonula occludens 1), occludin, and claudin-1 in the colon and the restored ileal microstructure, including the villi and crypts. In addition, they enhanced the antioxidant capacity of the liver by reducing the production of malondialdehyde and increasing the levels of glutathione and superoxide dismutase. The activation of Nrf2 and HO-1 may be responsible for recovering the antioxidant capacity. Interventions can decrease mouse TNF-α, IL-6 and IL-1ß content in serum, probably through the TLR4/MyD88/NF-κB pathway. Furthermore, they possess the ability to restore the quantities of bacteria responsible for producing butyric acid, such as Lactobacillus, Blautia, Bifidobacterium, Ruminococcaceae, Faecalibaculum and Lachnospiraceae. Taken together, CCFM1120V and D apparently can modify the composition of the gut microbiota, foster the gastrointestinal equilibrium, fortify the intestinal barrier, augment the antioxidant capacity of the liver, and effectively shield it from ethanol-induced injury.

Design and Conformation of Separators for High-performance Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries (AZIBs) are considered promising candidates for large-scale energy storage due to their high safety, low cost, and environmental friendliness. As a core component, separator plays a unique yet oftentimes overlooked role in providing electrochemical stability in AZIBs. This concept focuses on the exquisite structure-property relationship of separators, highlighting three forms of these components and their structural design requirements, i.e., traditional membranes, solid-state electrolytes, and electrode coatings. The mechanism by which separators influence the zinc anode and the cathode is discussed. The article also identifies the challenges and potential future directions for functional separators in the development of high-performance AZIBs.

Genomic mutation patterns and prognostic value in de novo and secondary acute myeloid leukemia: A multicenter study from China.

Acute myeloid leukemia (AML) can manifest as de novo AML (dn-AML) or secondary AML (s-AML), with s-AML being associated with inferior survival and distinct genomic characteristics. The underlying reasons for this disparity remain to be elucidated. In this multicenter study, next-generation sequencing (NGS) was employed to investigate the mutational landscape of AML in 721 patients from June 2020 to May 2023.Genetic mutations were observed in 93.34% of the individuals, with complex variations (more than three gene mutations) present in 63.10% of them. TET2, ASXL1, DNMT3A, TP53 and SRSF2 mutations showed a higher prevalence among older individuals, whereas WT1 and KIT mutations were more commonly observed in younger patients. BCOR, BCORL1, ZRSR2, ASXL1 and SRSF2 exhibited higher mutation frequencies in males. Additionally, ASXL1, NRAS, PPMID, SRSF2, TP53 and U2AF1 mutations were more common in patients with s-AML, which PPM1D was more frequently associated with therapy-related AML (t-AML). Advanced age and hyperleukocytosis independently served as adverse prognostic factors for both types of AML; however, s-AML patients demonstrated a greater number of monogenic adverse prognostic factors compared to dn-AML cases (ASXL1, PPM1D, TP53 and U2AF1 in s-AML vs. FLT3, TP53 and U2AF1 in dn-AML). Age and sex-related gene mutations suggest epigenetic changes may be key in AML pathogenesis. The worse prognosis of s-AML compared to dn-AML could be due to the older age of s-AML patients and more poor-prognosis gene mutations. These findings could improve AML diagnosis and treatment by identifying potential therapeutic targets and risk stratification biomarkers.

Event-Triggered Adaptive Finite-Time Control Using a Fuzzy State Observer for Nonlinear Cyber-Physical Systems Under Deception Attacks.

This article presents a new event-triggered adaptive finite-time control strategy using a fuzzy state observer for a class of nonlinear cyber-physical systems (CPSs) under malicious deception attacks with a more general form. Compared with the traditional assumptions on the deception attacks in the existing results, a more general assumption on deception attacks is given in this article. During the design process, real system states are initially estimated by developing an improved state observer, which effectively addresses the problem of state unavailability. Then, a coordinate transformation technology, in which the estimated states of observer are considered, is presented to stabilize the studied system. By constructing the singularity-free finite time virtual controls, the singularity problem in the traditional finite time design algorithms is cleverly avoided. Furthermore, to minimize communication overhead, a final finite-time controller is established by using a relative threshold event-triggered scheme. The developed event-triggered adaptive finite-time control strategy guarantees that all signals in the closed-loop system are semi-globally bounded in finite time without Zeno behavior. Finally, the correctness of the proposed control strategy is validated through two simulation results.

Review of the Interfacial Structure and Properties of Surfactants in Petroleum Production and Geological Storage Systems from a Molecular Scale Perspective.

Surfactants play a crucial role in tertiary oil recovery by reducing the interfacial tension between immiscible phases, altering surface wettability, and improving foam film stability. Oil reservoirs have high temperatures and high pressures, making it difficult and hazardous to conduct lab experiments. In this context, molecular dynamics (MD) simulation is a valuable tool for complementing experiments. It can effectively study the microscopic behaviors (such as diffusion, adsorption, and aggregation) of the surfactant molecules in the pore fluids and predict the thermodynamics and kinetics of these systems with a high degree of accuracy. MD simulation also overcomes the limitations of traditional experiments, which often lack the necessary temporal-spatial resolution. Comparing simulated results with experimental data can provide a comprehensive explanation from a microscopic standpoint. This article reviews the state-of-the-art MD simulations of surfactant adsorption and resulting interfacial properties at gas/oil-water interfaces. Initially, the article discusses interfacial properties and methods for evaluating surfactant-formed monolayers, considering variations in interfacial concentration, molecular structure of the surfactants, and synergistic effect of surfactant mixtures. Then, it covers methods for characterizing microstructure at various interfaces and the evolution process of the monolayers' packing state as a function of interfacial concentration and the surfactants' molecular structure. Next, it examines the interactions between surfactants and the aqueous phase, focusing on headgroup solvation and counterion condensation. Finally, it analyzes the influence of hydrophobic phase molecular composition on interactions between surfactants and the hydrophobic phase. This review deepened our understanding of the micro-level mechanisms of oil displacement by surfactants and is beneficial for screening and designing surfactants for oil field applications.

Radially distributed charging time constants at an electrode-solution interface.

An electrochemically homogeneous electrode-solution interface should be understood as spatially invariant in both terms of intrinsic reactivity for the electrode side and electrical resistance mainly for the solution side. The latter remains presumably assumed in almost all cases. However, by using optical microscopy to spatially resolve the classic redox electrochemistry occurring at the whole surface of a gold macroelectrode, we discover that the electron transfer occurs always significantly sooner (by milliseconds), rather than faster in essence, at the radial coordinates closer to the electrode periphery than the very center. So is the charging process when there is no electron transfer. Based on optical measurements of the interfacial impedance, this spatially unsynchronized electron transfer is attributed to a radially non-uniform distribution of solution resistance. We accordingly manage to eliminate the heterogeneity by engineering the solution resistance distribution. The revealed spatially-dependent charging time 'constant' (to be questioned) would help paint our overall fundamental picture of electrode kinetics.

Study on the mechanism of macrophages activated by phosphoesterified rehmanniae polysaccharide on human gastric cancer cells.

Gastric cancer(GC)is one of the most common gastrointestinal malignant tumors in the world, requiring the development of novel therapeutic agents with reduced toxicity. Rehmannia polysaccharide (RPS) possesses immunomodulatory and anti-tumor properties, yet its efficacy is suboptimal. To enhance its biological activity, we subjected RPS to molecular modifications, resulting in phosphorylated Rehmannia polysaccharides (P-RPS). Using the mixed phosphate method, we synthesized P-RPS and optimized the synthesis conditions through a combination of single-factor and response surface methodologies. In vitro studies on P-RPS's anti-tumor activity showed no direct influence on the viability of GC cells. However, P-RPS induced the transformation of PMA-activated THP-1 cells into the M1 phenotype. We collected conditioned medium (CM) of THP-1 cells to stimulate gastric cancer cells and CM-P-RPS significantly promoted apoptosis of gastric cancer cells and inhibited cell proliferation, and reduced cell migration. Mechanistically, CM-P-RPS inhibits the Wnt/ß-catenin signaling pathway through LGR6, leading to the suppression of tumor growth. Furthermore, P-RPS demonstrated a significant inhibitory effect on tumor growth in vivo, suggesting its potential as a promising therapeutic agent for GC treatment.

Soil moisture alters the responses of alpine ecosystem productivity to environmental factors, especially VPD, on the Qinghai-Tibetan Plateau.

Water availability, which can be represented by soil water content (SWC), plays a crucial role in plant growth and productivity across the cold and arid Qinghai-Tibetan Plateau. However, the indirect effects of SWC are less well understood, and a more comprehensive understanding of its regulating effects may enhance the recognition of its importance, as this factor is pivotal for accurately predicting the future response of alpine ecosystems to climate change. In this study, in situ eddy covariance observation data from typical alpine ecosystems and satellite data covering the Qinghai-Tibetan region were used to comprehensively reveal the effects of SWC on ecosystem productivity. The results indicated that SWC played an important role in regulating the responses of gross primary productivity (GPP) to other environmental factors over both time and space, especially in terms of the responses of GPP to vapor pressure deficit (VPD). The regulating effect can be summarized as follows: there was a specific SWC value (SWC = 0.24 m3 m-3 on the Qinghai-Tibetan Plateau) above which SWC was no longer the primary limiting factor. The responses of GPP to certain environmental factors shifted from negative to positive when the SWC increased above this value. The responses of GPP to VPD exhibited the highest sensitivity to the regulating effects of SWC, with a general response pattern found across different temporal and spatial scales. The findings revealed divergent responses of GPP to environmental factors under different SWC conditions and between arid and humid regions, emphasizing the importance of soil water conditions. These findings suggest that water conditions should be given primary consideration in global change studies.

[Efficacy of Decitabine Combined with Preexcitation Regimen in Treatment of Newly Diagnosed AML Patients Who Did not Respond to Initial Standard Induction Chemotherapy].

OBJECTIVE: To investigate the efficacy of decitabine combined with preexcitation regimen in the treatment of newly diagnosed acute myeloid leukemia (AML) patients who have not been relieved by the first standard induction chemotherapy and its influence on the relative content of regulatory T lymphocytes (Tregs). METHODS: The clinical data of 102 newly diagnosed AML patients (except acute promyelocytic leukemia) who did not relieve after initial standard induction chemotherapy in Shaanxi Provincial People's Hospital from March 2013 to March 2019 were retrospectively analyzed. Fifty-one patients who accepted pre-excitation regimen were divided into regular group, while another 51 patients treated with decitabine combined with pre-excitation regimen were divided into combination group. The efficacy, incidence of toxic and side effects, Core Scale of Quality of Life (QLQ-C30) score before and after treatment, T lymphocyte subsets (CD3+, CD4+, CD4+/CD8+, Tregs) and 3-year overall survival (OS) rate were compared between the two groups. RESULTS: The total effective rate of combination group was 80.39%, which was significantly higher than 62.75% of regular group (P < 0.05). After treatment, the QLQ-C30 score of combination group was 60.27±6.96, which was significantly lower than 65.73±7.96 of regular group (P < 0.001). There was no statistical difference in the incidence of toxic and side effects between the two groups (P >0.05). After treatment, the levels of CD3+, CD4+, CD4+/CD8+ in the combination group were higher than those in the regular group (all P < 0.001), while Treg was lower (P < 0.001). The 3-year OS rate in the combination group was 72.55%, which was significantly higher than 52.94% in the regular group (P < 0.001). CONCLUSION: Decitabine combined with preexcitation regimen has a significant effect on AML patients who have not been alleviated by standard induction chemotherapy in the first course of treatment. It can reduce anti-tumor immune suppression and improve immune function by regulating the relative content of Tregs, thus prolongs survival time and improves life quality of patients without increasing adverse reactions.

Black raspberry-mediated metabolic changes in patients with familial adenomatous polyposis associated with rectal polyp regression.

Familial adenomatous polyposis (FAP) patients face an almost certain 100% risk of developing colorectal cancer, necessitating prophylactic colectomy to prevent disease progression. A crucial goal is to hinder this progression. In a recent clinical trial involving 14 FAP patients, half received 60 g of black raspberry (BRB) powder orally and BRB suppositories at bedtime, while the other half received only BRB suppositories at bedtime over 9 months. This intervention led to a notable reduction in rectal polyps for 11 patients, although 3 showed no response. In this study, we delved into the metabolic changes induced by BRBs in the same patient cohort. Employing mass spectrometry-based non-targeted metabolomics, we analyzed pre- and post-BRB urinary and plasma samples from the 11 responders. The results showed significant alterations in 23 urinary and 6 plasma metabolites, influencing various pathways including polyamine, glutathione metabolism, the tricarboxylic acid cycle, inositol metabolism, and benzoate production. BRBs notably elevated levels of several metabolites associated with these pathways, suggesting a potential mechanism through which BRBs facilitate rectal polyp regression in FAP patients by modulating multiple metabolic pathways. Notably, metabolites derived from BRB polyphenols were significantly increased post-BRB intervention, emphasizing the potential therapeutic value of BRBs in FAP management.