Formononetin attenuates psoriasiform inflammation by regulating interferon signaling pathway.

BACKGROUND: Psoriasis is a long-lasting, inflammatory, continuous illness caused through T cells and characterized mainly by abnormal growth and division of keratinocytes. Currently, corticosteroids are the preferred option. However, prolonged use of traditional topical medication can lead to adverse reactions and relapse, presenting a significant therapeutic obstacle. Improved alternative treatment options are urgently required. Formononetin (FMN) is a representative component of isoflavones in Huangqi (HQ) [Astragalus membranaceus (Fisch.) Bge.]. It possesses properties that reduce inflammation, combat oxidation, inhibit tumor growth, and mimic estrogen. Although FMN has been shown to ameliorate skin barrier devastation via regulating keratinocyte apoptosis and proliferation, there are no reports of its effectiveness in treating psoriasis. OBJECTIVE: Through transcriptomics clues and experimental investigation, we aimed to elucidate the fundamental mechanisms underlying FMN's action on psoriasis. MATERIALS AND METHODS: Cell viability was examined using CCK8 assay in this study. The results of analysis of differentially expressed genes (DEGs) between FMN-treated HaCaT cells and normal HaCaT cells using RNA-sequencing (RNA-seq) were presented on volcano plots and heatmap. Enrichment analysis was conducted on DEGs using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), and results were validated through RT-qPCR verification. After 12 days of FMN treatment in psoriasis mouse model, we gauged the PASI score and epidermis thickness. A variety of techniques were used to assess FMN's effectiveness on inhibiting inflammation and proliferation related to psoriasis, including RT-qPCR, HE staining, western blot, and immunohistochemistry (IHC). RESULTS: The findings indicated that FMN could suppress the growth of HaCaT cells using CCK8 assay (with IC50 = 40.64 uM) and 20 uM FMN could reduce the level of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) to the greatest extent. FMN-treated HaCaT cells exhibited 985 up-regulated and 855 down-regulated DEGs compared to normal HaCaT cells. GO analysis revealed that DEGs were linked to interferon (IFN) signaling pathway. Furthermore, FMN improved pathological features, which encompassed decreased erythema, scale, and thickness scores of skin lesions in psoriasis mouse model. In vivo experiments confirmed that FMN down-regulated expression of IFN-α, IFN-ß, IFN-γ, decreased secretion of TNF-α and IL-17 inflammatory factors, inhibited expression of IFN-related chemokines included Cxcl9, Cxcl10, Cxcl11 and Cxcr3 and reduced expression of transcription factors p-STAT1, p-STAT3 and IFN regulatory factor 1 (IRF1) in the imiquimod (IMQ) group. CONCLUSIONS: In summary, these results suggested that FMN played an anti-inflammatory and anti-proliferative role in alleviating psoriasis by inhibiting IFN signaling pathway, and FMN could be used as a potential therapeutic agent.

Semiconducting polymer dots for multifunctional integrated nanomedicine carriers.

The expansion applications of semiconducting polymer dots (Pdots) among optical nanomaterial field have long posed a challenge for researchers, promoting their intelligent application in multifunctional nano-imaging systems and integrated nanomedicine carriers for diagnosis and treatment. Despite notable progress, several inadequacies still persist in the field of Pdots, including the development of simplified near-infrared (NIR) optical nanoprobes, elucidation of their inherent biological behavior, and integration of information processing and nanotechnology into biomedical applications. This review aims to comprehensively elucidate the current status of Pdots as a classical nanophotonic material by discussing its advantages and limitations in terms of biocompatibility, adaptability to microenvironments in vivo, etc. Multifunctional integration and surface chemistry play crucial roles in realizing the intelligent application of Pdots. Information visualization based on their optical and physicochemical properties is pivotal for achieving detection, sensing, and labeling probes. Therefore, we have refined the underlying mechanisms and constructed multiple comprehensive original mechanism summaries to establish a benchmark. Additionally, we have explored the cross-linking interactions between Pdots and nanomedicine, potential yet complete biological metabolic pathways, future research directions, and innovative solutions for integrating diagnosis and treatment strategies. This review presents the possible expectations and valuable insights for advancing Pdots, specifically from chemical, medical, and photophysical practitioners' standpoints.

Processable Pickering emulsion for composite cryogel with cellulose nanofibrils and nanochitin.

Cryogels that are constructed with cellulose nanofibrils (CNF) are important as green materials for a wide range of applications. However, their utilization is limited by inherent hydrophilicity and insufficient mechanical properties. Herein, a processable CNF/nanochitin (NCh)-stabilized Pickering emulsion that contains polylactide (PLA) in the oil phase is developed to directly produce ternary composite cryogels via freeze-drying. The complexation of CNF with NCh promotes CNF adsorption at the surface of PLA droplets, resulting in formation of uniform Pickering PLA droplets. The CNF/NCh complex-stabilized PLA droplets are easy to be translated to the internal structure of the cryogels, exhibiting lightweight nature and possessing highly porous structure. The interconnected network and lamellar structure formed by the CNF/NCh complexes, associating with inclusion of PLA particles, improve the cryogel structure integrity upon post-processing and endow hydrophilic cryogel with water resistance. This study offers a straightforward and eco-friendly Pickering emulsion template on fabrication of the CNF-based composite cryogel with controllable microstructure and mechanical performance, broadening construction of nanocellulose-based composites.

Distributed cyber attack detection and physical fault diagnosis for a class of interconnected large-scale systems.

In this paper we focus on the distributed cyber attack detection and physical fault diagnosis problem for a class of interconnected large-scale systems (ILSSs). In the proposed scheme, apart from node measurement, edge measurement is also used to construct distributed Kalman filter to estimate the state of each subsystem. The gain matrices of Kalman filter are determined by minimizing the covariance of estimation error in the attack-free and fault-free case, which reduces the false alarm rate of cyber attack detection and physical fault diagnosis. Based on this filter, a bank of adjacent residual generators is constructed to characterize the influence of cyber attack on the edge measurement, and the Chi-square test is used to detect whether the received edge measurements are attacked. At the same time, a local residual generator is constructed for each subsystem to characterize the influence of physical faults on it, and the residual signal is evaluated by variance and directional residual, so as to make distributed fault detection and isolation of each subsystem. It is worth noting that at each step, each subsystem first performs attack detection on the received edge measurements, and then estimates its own state using the attack-free edge measurements and node measurement, which further improves the accuracy of fault detection and isolation. In addition, a sufficient condition that ensuring the mean square exponential boundedness of the estimation error is given. Finally, the proposed scheme is verified by an illustrative example.

A transcribed ultraconserved noncoding RNA, uc.285+, promotes colorectal cancer proliferation through dual targeting of CDC42 by directly binding mRNA and protein.

The transcribed ultraconserved region (T-UCR) belongs to a new type of lncRNAs that are conserved in homologous regions of the rat, mouse and human genomes. A lot of research has reported that differential expression of T-UCRs can influence the development of various cancers, revealing the ability of T-UCRs as new therapeutic targets or potential cancer biomarkers. Most studies on the molecular mechanisms of T-UCRs in cancer have focused on ceRNA regulatory networks and interactions with target proteins, but the present study reveals an innovative dual-targeted regulatory approach in which T-UCRs bind directly to mRNAs and directly to proteins. We screened T-UCRs that may be related to colorectal cancer (CRC) by performing a whole-genome T-UCR gene microarray and further studied the functional mechanism of T-UCR uc.285+ in the development of CRC. Modulation of uc.285+ affected the proliferation of CRC cell lines and influenced the expression of the CDC42 gene. We also found that uc.285+ promoted the proliferation of CRC cells by directly binding to CDC42 mRNA and enhancing its stability while directly binding to CDC42 protein and affecting its stability. In short, our research on the characteristics of cell proliferation found that uc.285+ has a biological function in promoting CRC proliferation. uc.285+ may have considerable potential as a new diagnostic biomarker for CRC.

Succession of microbiota and its influence on the dynamics of volatile compounds in the semi-artificial inoculation fermentation of mulberry wine.

To improve the delightful flavor of mulberry wine through semi-artificial inoculation fermentation with Saccharomyces cerevisiae, we studied the dynamics change of microbiota, along with the physicochemical properties and metabolite profiles and their interaction relationship during the fermentation process. The abundance of lactic acid bacteria (Weissella, Lactobacillus, Fructobacillus, and Pediococcus) increased significantly during fermentation, while yeasts gradually established dominance. The inter-kingdom network of the dominant genera analysis further identified the following as core microbiota: Alternaria, Botrytis, Kazachstania, Acremonium, Mycosphaerella, Pediococcus, Gardnerella, and Schizothecium. Additionally, pH, alcohol, and total acid were significantly affected by microbiota variation. Fourteen of all identified volatile compounds with key different aromas were screened using PCA, OPLS-DA, and rOAV. The network of interconnected core microbiota with key different aromas revealed that Kazachstania and Pediococcus had stronger correlations with 1-butanol, 3-methyl-, propanoic acid, and 2-methyl-ethyl ester.

The Antibiotic Resistome and Its Association with Bacterial Communities in Raw Camel Milk from Altay Xinjiang.

Raw camel milk is generally contaminated with varied microbiota, including antibiotic-resistant bacteria (ARB), that can act as a potential pathway for the spread of antibiotic resistance genes (ARGs). In this study, high-throughput quantitative PCR and 16S rRNA gene-based Illumine sequencing data were used to establish a comprehensive understanding of the antibiotic resistome and its relationship with the bacterial community in Bactrian camel milk from Xinjiang. A total of 136 ARGs and up to 1.33 × 108 total ARG copies per gram were identified, which predominantly encode resistance to ß-lactamas and multidrugs. The ARGs' profiles were mainly explained by interactions between the bacteria community and physicochemical indicators (77.9%). Network analysis suggested that most ARGs exhibited co-occurrence with Corynebacterium, Leuconostoc and MGEs. Overall, raw camel milk serves as a reservoir for ARGs, which may aggravate the spread of ARGs through vertical and horizontal gene transfer in the food chain.

Self-assembly of three-dimensional liver organoids: virtual reconstruction via endocytosed polymer dots for refactoring the fine structure.

In vitro culture of organoids holds considerable promise for the treatment of diseases or the provision of artificial organs. Traditional 2D differentiation from mesenchymal stem cells (MSCs) faces challenges in replicating the development of embryonic organs at the cellular level; conversely, the cultivation of 3D organoids exhibits potential for application. It is crucial for clinicians and technology researchers to acquire insights into organoid tissue differentiation, autonomous morphogenesis, as well as 3D assembly processes in vitro. In this investigation, novel 3D organoids capable of engendering complex liver-like tissues in vitro were cultured, and a class of high-luminance semiconductor polymer dots (Pdots) was employed to monitor the self-assembly process of 3D liver organoid tissues and cellular interaction and migration dynamics. Three-dimensional liver-bud (3D-LB) organoid tissues were derived through the interplay of induced MSCs, Wharton's Jelly, and human umbilical vein endothelial cells (HUVECs), and their structural characteristics were determined during the liver-bud organoid development; ultimately, the co-cultured organoid spatial cellular clusters resembling a truffle were successfully replicated. Utilizing R8-Pdots with remarkable resolution and biocompatibility, the structural elements of functional and vascularized organs derived from liver organoid tissues were adeptly reconstituted, and this investigation shall contribute to a further understanding of human hepato-developmental physiology and liver-disease modeling.

Early identification of lung cancer patients with venous thromboembolism: development and validation of a risk prediction model.

INTRODUCTION: Venous thromboembolism(VTE) is a leading cause of death in patients with lung cancer. Furthermore, hospitalization of patients with advanced lung cancer for VTE treatment represents a major economic burden on the national public health resources. Therefore, we performed this prospective study to identify clinical biomarkers for the early identification of VTE in lung cancer patients. METHODS: This prospective study enrolled 158 patients with confirmed lung cancer, including 27 who were diagnosed with VTE within six months of the follow-up after lung cancer diagnosis. Multivariate logistic regression analysis was used to evaluate the diagnostic performancese of all the relevant clinical features and laboratory indicators in identifying lung cancer patients with a higher risk of VTE. A novel risk prediction model was constructed consisting of five clinical variables with the best diagnostic performances and was validated using the receiver operation characteristic(ROC) curves. The diagnostic performances of the new risk prediction model was also compared with the Khorana risk score (KRS) and the Padua risk score (PRS). RESULTS: The VTE group of lung cancer patients (n = 27) showed significantly higher serum levels of fibrin degradation products (FDP), D-dimer, thrombomodulin (TM), thrombin-antithrombin-complex (TAT), α2-plasmin inhibitor-plasmin Complex (PIC), and tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC) compared to those in the non-VTE group (n = 131). ROC curve analyses showed that the diagnostic efficacy of the new VTE risk prediction model with TM ≥ 9.75 TU/ml, TAT ≥ 2.25ng/ml, t-PAIC ≥ 7.35ng/ml, history of VTE, and ECOG PS score ≥ 2 was superior than the KRS and the PRS in the early identification of lung cancer patients with a higher risk of VTE. CONCLUSIONS: The new risk prediction model showed significantly high diagnostic efficacy in the early identification of lung cancer patients with a high risk of VTE. The diagnostic efficacy of the new risk prediction model was higher than the KRS and the PRS in this cohort of lung cancer patients.

Cerium oxide nanoparticles in diabetic foot ulcer management: Advances, limitations, and future directions.

Diabetic foot ulcer (DFU) is one of the most serious complications of diabetes, potentially resulting in wound infection and amputation under severe circumstances. Oxidative stress and dysbiosis are the primary factors that delay wound healing, posing challenges to effective treatment. Unfortunately, conventional approaches in these aspects have proven satisfactory in achieving curative outcomes. Recent research has increasingly focused on using nanoparticles, leveraging their potential in wound dressing and medication delivery. Their unique physical properties further enhance their therapeutic effectiveness. Among these nanoparticles, cerium oxide nanoparticles (CONPs) have garnered attention due to their notable beneficial effects on oxidative stress and microbial abundance, thus representing a promising therapeutic avenue for DFU. This review comprehensively assesses recent studies on CONPs in treating DFU. Furthermore, we elaborate on the wound healing process, ceria synthesis, and incorporating CONPs with other materials. Crucially, a thorough evaluation of CONPs' toxicity as a novel metallic nanomaterial for therapeutic use must precede their formal clinical application. Additionally, we identify the current challenges CONPs encounter and propose future directions for their development.

Metabolomics-Based Analyses of Dynamic Changes in Flavonoid Profiles in the Black Mulberry Winemaking Process.

To overcome the fruit's perishability, mulberry wine has been developed as a method of preservation. However, dynamic changes in metabolites during mulberry wine fermentation have not been reported yet. In the present investigation, UHPLC-QE-MS/MS coupled with multivariate statistical analyses was employed to scrutinize the metabolic profiles, particularly the flavonoid profiles, throughout the process of vinification. In general, the major differential metabolites encompassed organic heterocyclic compounds, amino acids, phenylpropanoids, aromatic compounds, and carbohydrates. The contents of total sugar and alcohol play a primary role that drove the composition of amino acids, polyphenol, aromatic compound, and organic acid metabolites based on the Mantel test. Importantly, among the flavonoids, abundant in mulberry fruit, luteolin, luteolin-7-O-glucoside, (-)-epiafzelechin, eriodictyol, kaempferol, and quercetin were identified as the differential metabolic markers during blackberry wine fermentation and ripening. Flavonoid, flavone and flavonol biosynthesis were also identified to be the major metabolic pathways of flavonoids in 96 metabolic pathways. These results will provide new information on the dynamic changes in flavonoid profiles during black mulberry winemaking.

CircFAM114A2 inhibits the progression of hepatocellular carcinoma via miR-630/HHIP axis.

BACKGROUND: Many studies have shown that circular RNAs (circRNAs) are abnormally expressed in various tumor tissues and served as a key regulator in the occurrence and development of cancer. However, in hepatocellular carcinoma (HCC), the molecular mechanism of circRNAs in body fluids remains to be further explored. METHODS: The expression levels of genes and proteins were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting, respectively. Cell counting Kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU), wound healing assay, Transwell assays, flow cytometry, and tumor formation models in nude mice were conducted to investigate the effects of circFAM114A2 on HCC cells both in vitro and in vivo. RNA antisense purification (RAP), dual luciferase reporter assays and rescue assays were carried out to verify the interaction between circFAM114A2, miR-630 and HHIP. RESULTS: CircFAM114A2 was significantly downregulated in HCC tissues and was associated with microvascular invasion and lymph node metastasis of HCC patients. We also observed that circFAM114A2 was lowly expressed in HCC plasma, which may serve as an effective biomarker to screen HCC patients from healthy controls (area under curve (AUC)=0.922). In vitro, circFAM114A2 overexpression significantly blunted HCC cell proliferation, migration, invasion, and promoted apoptosis, whereas circFAM114A2 silencing posed opposite effects. In vivo, circFAM114A2 overexpression inhibited the growth of HCC cells. Mechanistically, circFAM114A2 could increase the expression of the tumor suppressor HHIP via acting as a sponge for miR-630. CONCLUSIONS: CircFAM114A2 exerts a tumor suppressor role in HCC through miR-630/HHIP axis, and may be served as a potential diagnostic and therapeutic biomarker for HCC patients.

Glyphosate induces autophagy in hepatic L8824 cell line through NO-mediated activation of RAS/RAF/MEK/ERK signaling pathway and energy metabolism disorders.

Glyphosate is an herbicide commonly used worldwide, and its substantial use causes widespread pollution with runoff. However, research on glyphosate toxicity has mostly remained at the embryonic level and existing studies are limited. In the present study, we investigated whether glyphosate can induce autophagy in hepatic L8824 cells by regulating energy metabolism and rat sarcoma (RAS)/rapidly accelerated fibrosarcoma (RAF)/mitogen-activated extracellular signal-regulated kinase (MEK)/extracellular regulated protein kinases (ERK) signaling by activating nitric oxide (NO). First, we selected 0, 50, 200, and 500 µg/mL as the challenge doses, according to the inhibitory concentration of 50% (IC50) of glyphosate. The results showed that glyphosate exposure increased the enzyme activity of inducible nitric oxide synthase (iNOS), which in turn increased the NO content. The activity and expression of enzymes related to energy metabolism, such as hexokinase (HK)1, HK2, phosphofructokinase (PFK), phosphokinase (PK), succinate dehydrogenase (SDH), and nicotinamide adenine dinucleotide with hydrogen (NADH), were inhibited, and the RAS/RAF/MEK/ERK signaling pathway was activated. This led to the negative expression of mammalian target of rapamycin (mTOR) and P62 in hepatic L8824 cells and the activation of the autophagy marker genes microtubule-associated proteins light chain 3 (LC3) and Beclin1 to induce autophagy. The above results were dependent on glyphosate concentration. To verify whether autophagy can be excited by the RAS/RAF/MEK/ERK signaling pathway, we treated L8824 cells with the ERK inhibitor U0126 and found that the autophagy gene LC3 was reduced due to the inhibition of ERK, thus demonstrating the reliability of the results. In conclusion, our results demonstrate that glyphosate can induce autophagy in hepatic L8824 cells by activating NO, thus regulating energy metabolism and the RAS/RAF/MEK/ERK signaling pathway.

SAA1 identified as a potential prediction biomarker for metastasis of hepatocellular carcinoma via multi-omics approaches.

Background: Metastasis is the major cause of high recurrence and mortality of hepatocellular carcinoma (HCC). Unfortunately, there are few reports on effective biomarkers of HCC metastasis. Previous studies have reported that SAA1 may be a predictor and prognostic biomarker for multiple malignant tumors. However, the role of SAA1 in HCC has not yet been investigated. Methods: We applied RNA sequencing and proteomics analysis to investigate the expression landscape of HCC cell lines and patient serum, respectively. SAA1 is a common key gene and listed as a candidate biomarker of HCC metastasis. It was validated in two cell lines, 107 participants serum, and 63 matched HCC and adjacent non-tumorous liver tissues. Human Protein Atlas (HPA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) datasets were integrated to explore SAA1 expression among various cell types and organs. The diagnostic and prognostic value of SAA1 in HCC were determined through receiver operating characteristic (ROC) and Kaplan-Meier curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network were constructed for SAA1, as well as for its co-expressed genes. We further analyzed the correlation between SAA1 and co-expression genes. Results: We found 7 differentially expressed genes (DEGs) and 14 differentially expressed proteins (DEPs) were related to HCC metastasis. SAA1, a key candidate biomarker, was highly enriched in hepatocytes and liver organ, and it was also highly expressed in HCC cells and the serum and tissues of HCC patients. The results of ROC curve analysis indicated that SAA1 had better predictive values for distinguishing HCC metastasis from non-metastasis. Kaplan-Meier curve analysis revealed that HCC patients with higher SAA1 expression had worse overall survival. Conclusions: Our findings provide new insights into HCC metastasis by identifying candidate gene prediction biomarkers for HCC metastasis.

Distributed control for a class of nonlinear systems based on distributed high-gain observer.

This paper concerns the problem of designing distributed control law for a class nonlinear system in which the measurement outputs of the system are distributed in different subsystems. It leads to a challenge that the states of the original systems cannot be completely reconstructed by any single subsystem. In order to solve this problem, distributed state observers and the distributed observer-based distributed control problem emerges as the times require. However, the distributed observers problem of the nonlinear systems is rarely studied, and the distributed control law formed by distributed nonlinear observers has hardly ever been studied up to now. To this end, this paper develops the distributed high-gain observers for a class of nonlinear systems. Unlike the previous several results, our study has the ability to deal with model uncertainty, and devotes itself to overcoming the problem that the separation principle is not tenable. In addition, based on the state estimate generated by the designed distributed observer, an output feedback control law formed by applying the state estimate is developed. Furthermore, a class of sufficient conditions is proved for guaranteeing the error dynamics of the distributed observer and the state trajectory of the closed-loop system to enter an arbitrary small invariant set around the origin. Finally, the simulation results verify the effectiveness of the proposed method.

Study on the Lower Limits of Physical Parameters for Heavy Oil Reservoirs during the In Situ Combustion Process.

As an effective enhanced oil recovery (EOR) method in the late stage of the steam injection process, in situ combustion (ISC) has been verified by more and more researchers owing to its high recovery efficiency and low operation cost. However, the ISC process is prone to bringing about an unfavorable result with a low sweep efficiency and even an extinction process due to the complexity and uncertainty in oil and water distribution as well as the heterogeneity of the actual reservoir. In this work, combustion tube experiments combined with numerical simulations by CMG-STARS were conducted to study the influence of a reservoir's physical parameters on the stability of ISC. It was found that the sustainability of the combustion process is sensitive to permeability and oil saturation, the lower limits of which are determined as 0.2 µm2 and 0.2, respectively. Then, a formula was preliminarily proposed as 0.25 ≤ So/K ≤ 0.8, which could be used as a reference of screening criteria in designing the ISC process.

Integrative Single-Cell Analysis Reveals Transcriptional and Epigenetic Regulatory Features of Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC. SIGNIFICANCE: A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

Composite Observer-Based Optimal Attitude-Tracking Control With Reinforcement Learning for Hypersonic Vehicles.

This article proposes an observer-based reinforcement learning (RL) control approach to address the optimal attitude-tracking problem and application for hypersonic vehicles in the reentry phase. Due to the unknown uncertainty and nonlinearity caused by parameter perturbation and external disturbance, accurate model information of hypersonic vehicles in the reentry phase is generally unavailable. For this reason, a novel synchronous estimation is proposed to construct a composite observer for hypersonic vehicles, which consists of a neural-network (NN)-based Luenberger-type observer and a synchronous disturbance observer. This solves the identification problem of nonlinear dynamics in the reference control and realizes the estimation of the system state when unknown nonlinear dynamics and unknown disturbance exist at the same time. By synthesizing the information from the composite observer, an RL tracking controller is developed to solve the optimal attitude-tracking control problem. To improve the convergence performance of critic network weights, concurrent learning is employed to replace the traditional persistent excitation condition with a historical experience replay manner. In addition, this article proves that the weight estimation error is bounded when the learning rate satisfies the given sufficient condition. Finally, the numerical simulation demonstrates the effectiveness and superiority of the proposed approaches to attitude-tracking control systems for hypersonic vehicles.

LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA-target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA-target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA-target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA-target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA-target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA-target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA-target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA-target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

The dynamic dysregulated network identifies stage-specific markers during lung adenocarcinoma malignant progression and metastasis.

Brain metastasis occurs in approximately 30% of patients with lung adenocarcinoma (LUAD) and is closely associated with poor prognosis, recurrence, and death. However, dynamic gene regulation and molecular mechanism driving LUAD progression remain poorly understood. In this study, we performed a comprehensive single-cell transcriptome analysis using data from normal, early stage, advanced stage, and brain metastasis LUAD. Our single-cell-level analysis reveals the cellular composition heterogeneity at different stages during LUAD progression. We identified stage-specific risk genes that could contribute to LUAD progression and metastasis by reprogramming immune-related and metabolic-related functions. We constructed an early advanced metastatic dysregulated network and revealed the dynamic changes in gene regulations during LUAD progression. We identified 6 early advanced (HLA-DRB1, HLA-DQB1, SFTPB, SFTPC, PLA2G1B, and FOLR1), 8 advanced metastasis (RPS15, RPS11, RPL13A, RPS24, HLA-DRB5, LYPLA1, KCNJ15, and PSMA3), and 2 common risk genes in different stages (SFTPD and HLA-DRA) as prognostic markers in LUAD. Particularly, decreased expression of HLA-DRA, HLA-DRB1, HLA-DQB1, and HLA-DRB5 refer poor prognosis in LUAD by controlling antigen processing and presentation and T cell activation. Increased expression of PSMA3 and LYPLA1 refer poor prognosis by reprogramming fatty acid metabolism and RNA catabolic process. Our findings will help further understanding the pathobiology of brain metastases in LUAD.