Targeted metabolomics combined with machine learning to identify and validate new biomarkers for early SLE diagnosis and disease activity.

BACKGROUND: The early diagnosis of systemic lupus erythematosus (SLE) and the assessment of disease activity progression remain a great challenge. Targeted metabolomics has great potential to identify new biomarkers of SLE. METHODS: Serum from 44 healthy participants and 89 SLE patients were analyzed using HM400 high-throughput targeted metabolomics. Machine learning (ML) with seven learning models and trained the model several times iteratively selected the two best prediction model in a competitive way, which were independent validated by enzyme-linked immunosorbent (ELISA) with 90 SLE patients. RESULTS: In this study, 146 differential metabolites, most of them organic acids, amino acids, and bile acids, were detected between patients with initial SLE and healthy participants, and 8 potential biomarkers were found by intersection of ML and statistics (area under the curve [AUC] > 0.95) showing a significant positive correlation with clinical indicators. In addition, we identified and validated 2 potential biomarkers for SLE classification (P < 0.05, AUC > 0.775; N-Methyl-L-glutamic acid, L-2-aminobutyric acid) showing a significant correlation with the SLE Disease Activity Index. These differential metabolites were mainly involved in metabolic pathways, amino acid biosynthesis, 2-oxocarboxylic acid metabolism and other pathways. CONCLUSION: This study indicated that the tricarboxylic acid cycle might be associated with SLE drug therapy. We identified 8 diagnostic models biomarkers and 2 biomarkers that could be used to identify initial SLE and distinguish different activity degree, which will promote the development of new tools for the diagnosis and evaluation of SLE.

Effectiveness of fecal DNA syndecan-2 methylation testing for detection of colorectal cancer in a high-risk Chinese population.

BACKGROUND: Colorectal cancer (CRC) is among the most prevalent and life-threatening malignancies worldwide. Syndecan-2 methylation (mSDC2) testing has emerged as a widely used biomarker for early detection of CRC in stool and serum samples. Cancer (CRC) is among the most prevalent and life-threatening malignancies worldwide. mSDC2 testing has emerged as a widely used biomarker for early detection of CRC in stool and serum samples. AIM: To validate the effectiveness of fecal DNA mSDC2 testing in the detection of CRC among a high-risk Chinese population to provide evidence-based data for the development of diagnostic and/or screening guidelines for CRC in China. METHODS: A high-risk Chinese cohort consisting of 1130 individuals aged 40-79 years was selected for evaluation via fecal mSDC2 testing. Sensitivity and specificity for CRC, advanced adenoma (AA) and advanced colorectal neoplasia (ACN) were determined. High-risk factors for the incidence of colorectal lesions were determined and a logistic regression model was constructed to reflect the efficacy of the test. RESULTS: A total of 1035 high-risk individuals were included in this study according to established criteria. Among them, 16 suffered from CRC (1.55%), 65 from AA (6.28%) and 189 from non-AAs (18.26%); 150 patients were diagnosed with polyps (14.49%). Diagnoses were established based upon colonoscopic and pathological examinations. Sensitivities of the mSDC2 test for CRC and AA were 87.50% and 40.00%, respectively; specificities were 95.61% for other groups. Positive predictive values of the mSDC2 test for CRC, AA and ACN were 16.09%, 29.89% and 45.98%, respectively; the negative predictive value for CRC was 99.79%. After adjusting for other high-risk covariates, mSDC2 test positivity was found to be a significant risk factor for the occurrence of ACN (P < 0.001). CONCLUSION: Our findings confirmed that offering fecal mSDC2 testing and colonoscopy in combination for CRC screening is effective for earlier detection of malignant colorectal lesions in a high-risk Chinese population.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer.

BACKGROUND: The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored. METHODS: BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents. RESULTS: Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib. CONCLUSIONS: In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

Research progress of the netrins and their receptors in cancer.

Netrins, a family of secreted and membrane-associated proteins, can regulate axonal guidance, morphogenesis, angiogenesis, cell migration, cell survival, and tumorigenesis. Four secreted netrins (netrin 1, 3, 4 and 5) and two glycosylphosphatidylinositols-anchored membrane proteins, netrin-G1 and G2, have been identified in mammals. Netrins and their receptors can serve as a biomarker and molecular therapeutic target for pathological differentiation, diagnosis and prognosis of malignant cancers. We review here the potential roles of the netrins family and their receptors in cancer.

Identification and validation of a novel glycolysis-related ceRNA network for sepsis-induced cardiomyopathy.

Purpose: Sepsis-induced cardiomyopathy (SIC) is a major life-threatening condition in critically infected patients. Early diagnosis and intervention are important to improve patient prognosis. Recognizing the pivotal involvement of the glycolytic pathway in SIC, this study aims to establish a glycolysis-related ceRNA network and explore novel diagnostic avenues. Materials and methods: SIC-related datasets were carefully filtered from the GEO database. CytoHubba was used to identify differentially expressed genes (DEGs) associated with glycolysis. A predictive method was then used to construct an lncRNA-miRNA-mRNA network. Dual-luciferase reporter assays validated gene interactions, and the specificity of this ceRNA network was confirmed in peripheral blood mononuclear cells (PBMCs) from SIC patients. Logistic analysis was used to examine the correlation between the ceRNA network and SIC. Diagnostic potential was assessed using receiver operating characteristic (ROC) curves, and correlation analysis investigated any associations between gene expression and clinical indicators. Results: IER3 was identified as glycolysis-related DEG in SIC, and a ceRNA network (SNHG17/miR-214-3p/IER3) was established by prediction. Dual luciferase reporter gene assay confirmed the presence of mutual binding between IER3, miR-214-3p and SNHG17. RT-qPCR verified the specific expression of this ceRNA network in SIC patients. Multivariate logistic analysis established the correlation between the ceRNA network and SIC. ROC analysis demonstrated its high diagnostic specificity (AUC > 0.8). Correlation analysis revealed a negative association between IER3 expression and oxygenation index in SIC patients (p < 0.05). Furthermore, miR-214-3p expression showed a negative correlation with NT-proBNP (p < 0.05). Conclusion: In this study, we identified and validated a ceRNA network associated with glycolysis in SIC: SNHG17/miR-214-3p/IER3. This ceRNA network may play a critical role in the onset and development of SIC. This finding is important to further our understanding of the pathophysiological mechanisms underlying SIC and to explore potential diagnostic and therapeutic targets for SIC.

Non-coding RNAs are involved in tumor cell death and affect tumorigenesis, progression, and treatment: a systematic review.

Cell death is ubiquitous during development and throughout life and is a genetically determined active and ordered process that plays a crucial role in regulating homeostasis. Cell death includes regulated cell death and non-programmed cell death, and the common types of regulatory cell death are necrosis, apoptosis, necroptosis, autophagy, ferroptosis, and pyroptosis. Apoptosis, Necrosis and necroptosis are more common than autophagy, ferroptosis and pyroptosis among cell death. Non-coding RNAs are regulatory RNA molecules that do not encode proteins and include mainly microRNAs, long non-coding RNAs, and circular RNAs. Non-coding RNAs can act as oncogenes and tumor suppressor genes, with significant effects on tumor occurrence and development, and they can also regulate tumor cell autophagy, ferroptosis, and pyroptosis at the transcriptional or post-transcriptional level. This paper reviews the recent research progress on the effects of the non-coding RNAs involved in autophagy, ferroptosis, and pyroptosis on tumorigenesis, tumor development, and treatment, and looks forward to the future direction of this field, which will help to elucidate the molecular mechanisms of tumorigenesis and tumor development, as well as provide a new vision for the treatment of tumors.

PLA inhibits TNF-α-induced PANoptosis of prostate cancer cells through metabolic reprogramming.

Previous studies have shown that phenyllactic acid (alpha-Hydroxyhydrocinnamic acid, 2-Hydroxy-3-phenylpropionic acid, PLA), a type of organic acid metabolite, has excellent diagnostic efficacy when used to differentiate between prostate cancer, benign prostatic hyperplasia, and prostatitis. This research aims to explore the molecular mechanism by which PLA influences the PANoptosis of prostate cancer (PCa) cell lines. First, we found that PLA was detected in all prostate cancer cell lines (PC-3, PC-3 M, DU145, LNCAP). Further experiments showed that the addition of PLA to prostate cancer cells could promote ATP generation, enhance cysteine desulfurase (NFS1) expression, and reduce tumor necrosis factor alpha (TNF-α) levels, thereby inhibiting apoptosis in prostate cancer cells. Notably, overexpression of NFS1 can inhibit the binding of TNF-α to serpin mRNA binding protein 1 (SERBP1), suggesting that NFS1 competes with TNF-α for binding to SERBP1. Knockdown of SERBP1 significantly reduced the level of small ubiquity-related modifier (SUMO) modification of TNF-α. This suggests that NFS1 reduces the SUMO modification of TNF-α by competing with SERBP1, thereby reducing the expression and stability of TNF-α and ultimately inhibiting apoptosis in prostate cancer cell lines. In conclusion, PLA inhibits TNF-α induced panapoptosis of prostate cancer cells through metabolic reprogramming, providing a new idea for targeted treatment of prostate cancer.

A novel approach to deriving the fine-scale daily NO2 dataset during 2005-2020 in China: Improving spatial resolution and temporal coverage to advance exposure assessment.

Surface NO2 pollution can result in serious health consequences such as cardiovascular disease, asthma, and premature mortality. Due to the extensive spatial variation in surface NO2, the spatial resolution of a NO2 dataset has a significant impact on the exposure and health impact assessment. There is currently no long-term, high-resolution, and publicly available NO2 dataset for China. To fill this gap, this study generated a NO2 dataset named RBE-DS-NO2 for China during 2005-2020 at 1 km and daily resolution. We employed the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and utilized an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an R2 of 0.72 and RMSE of 10.7 µg/m3, while cross-validation across China during 2013-2020 showed an R2 of 0.73 and RMSE of 9.6 µg/m3. RBE-DS-NO2 better captured spatiotemporal variation of surface NO2 in China compared to the existing publicly available datasets. Exposure assessment using RBE-DS-NO2 show that the population living in non-attainment areas (NO2 ≥ 30 µg/m3) grew from 376 million in 2005 to 612 million in 2012, then declined to 404 million by 2020. Unlike this national trend, exposure levels in several major cities (e.g., Shanghai and Chengdu) continued to increase during 2012-2020, driven by population growth and urban migration. Furthermore, this study revealed that low-resolution dataset (i.e., the 10 km intermediate dataset before the downscaling) overestimated NO2 levels, due to the limited specificity of the low-resolution model in simulating the relationship between NO2 and the predictor variables. Such limited specificity likely biased previous long-term NO2 exposure and health impact studies employing low-resolution datasets. The RBE-DS-NO2 dataset enables robust long-term assessments of NO2 exposure and health impacts in China.

Identifying clinical risk factors correlated with addictive features of non-suicidal self-injury among a consecutive psychiatric outpatient sample of adolescents and young adults.

Non-suicidal self-injury (NSSI) is an issue primarily of concern in adolescents and young adults. Recent literature suggests that persistent, repetitive, and uncontrollable NSSI can be conceptualized as a behavioral addiction. The study aimed to examine the prevalence of NSSI with addictive features and the association of this prevalence with demographic and clinical variables using a cross-sectional and case-control design. A total of 548 outpatients (12 to 22 years old) meeting the criteria for NSSI disorder of DSM-5 were enrolled and completed clinical interviews by 4 psychiatrists. NSSI with addictive features were determined by using a single-factor structure of addictive features items in the Ottawa self-injury inventory (OSI). Current suicidality, psychiatric diagnosis, the OSI, the revised Chinese Internet Addiction Scale, the Childhood Trauma Questionnaire, and the 20-item Toronto Alexithymia Scale were collected. Binary logistic regression analyses were used to explore associations between risk factors and NSSI with addictive features. This study was conducted from April 2021 to May 2022. The mean age of participants was 15.93 (SD = 2.56) years with 418 females (76.3%), and the prevalence of addictive NSSI was 57.5% (n = 315). Subjects with addictive NSSI had a higher lifetime prevalence of nicotine and alcohol use, a higher prevalence of current internet addiction, suicidality, and alexithymia, and were more likely to have physical abuse/neglect, emotional abuse, and sexual abuse than NSSI subjects without addictive features. Among participants with NSSI, the strongest predictors of addictive features of NSSI were female (OR = 2.405, 95% CI 1.512-3.824, p < 0.0001), alcohol use (OR = 2.179, 95% CI 1.378-3.446, p = 0.001), current suicidality (OR = 3.790, 95% CI 2.351-6.109, p < 0.0001), and psysical abuse in childhood (OR = 2.470, 95% CI 1.653-3.690, p < 0.0001). Nearly 3 out of 5 patients (12-22 years old) with NSSI met the criteria of NSSI with addictive features in this psychiatric outpatients sample. Our study demonstrated the importance of the necessity to regularly assess suicide risk, and alcohol use, as well as focus more on females and subjects who had physical abuse in childhood to prevent addictive NSSI.

Comprehensive analysis of the role of Netrin G1 (NTNG1) in hepatocellular carcinoma cells.

Netrin G1 (NTNG1) is a member of the Netrin family and plays a crucial role in various human cancers. However, the molecular functions of NTNG1 in HCC and the underlying mechanisms remain unclear. HCC expression data was obtained from the GEO database and analyzed using various bioinformatics tools. The expression of NTNG1 in HCC tissues and liver cancer cells was evaluated through RT-qPCR and western blotting. Cells with stable NTNG1 overexpression and knockdown were established, and CCK-8, colony formation, and flow cytometry assays were conducted in vitro. The xenograft model was utilized to verify the tumorigenesis capacity of NTNG1 in vivo. IHC was employed to analyze the expression of NTNG1 and CD163 proteins. HCC-specific genes were screened, followed by functional enrichment and immune cell infiltration analysis. Finally, the Co-IP was used to detect the interaction between NTNG1 and N-cadherin. NTNG1 was highly expressed in HCC tissues and liver cancer cells, and associated with significantly poorer OS rates. In addition, NTNG1 overexpression in liver cancer cells significantly increased their proliferation, colony growth, invasion, migration, and EMT, while inhibiting apoptosis. Bioinformatics analyses indicated that NTNG1 was closely related to EMT and tumor infiltration. IHC staining revealed a positive correlation between NTNG1 expression and CD163 in HCC tissues. Additionally, an EMT inhibitor attenuated the expression levels of EMT-related markers and counteracted the effects of NTNG1 overexpression in liver cancer cells. This study is the first to identify NTNG1 as a potential therapeutic target in HCC, promoting tumor development and progression by regulating EMT.

circMSH3 is a potential biomarker for the diagnosis of colorectal cancer and affects the distant metastasis of colorectal cancer.

Objectives: To identify the most significantly differentially expressed circular RNAs (circRNAs) in colorectal cancer (CRC) tissues in terms of their expression levels and circularity, and to analyze the relationship between their expression levels and the clinical characteristics of patients. Methods: circRNA RNA-seq technology was used to screen differentially expressed circRNAs in CRC. Sanger sequencing was used to identify circRNA back-splice junction sites. The relative expression levels of hsa_circ_0003761 (circMSH3) in CRC tissues and cell lines were detected by quantitative real-time fluorescence PCR technology. An RNA-protein pull-down assay was used to detect protein binding to circRNAs. Dual-luciferase reporter gene vectors were constructed to verify that circRNAs bind to microRNAs. Results: Four hundred twenty circRNAs were found to be upregulated, and 616 circRNAs were downregulated. circMSH3 was derived from the MutS homolog 3 (MSH3) gene and was formed by a loop of exons 9, 10, 11, and 12. In 110 pairs of CRC and adjacent tissues, circMSH3 expression was 4.487-fold higher in CRC tissues. circMSH3 was also highly expressed in the HT-29 and LOVO CRC cell lines. The expression level of circMSH3 was associated with distant metastasis in CRC patients (P = 0.043); the area under the curve (AUC) of circMSH3 for CRC diagnosis was 0.75, with a sensitivity and specificity of 70.9% and 66.4%, respectively. circMSH3 could bind to a variety of proteins, mainly those involved in RNA transcription, splicing, cell cycle, and cell junctions. Furthermore, circMSH3 could bind to miR-1276, miR-942-5p, and miR-409-3p. Conclusion: circMSH3 is a potential biomarker for the diagnosis of CRC and affects the distant metastasis of CRC. Multiple RNA-binding protein binds to circMSH3, and circMSH3 binds to miR-1276, miR-942-5p, and miR-409-3p, thereby affecting the expression of circMSH3.

Progress in research on tumor microenvironment-based spatial omics technologies.

Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information. It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results. Spatial omics technologies include spatial transcriptomics, spatial proteomics, spatial metabolomics, and other technologies, the most widely used of which are spatial transcriptomics and spatial proteomics. The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist, including the surrounding blood vessels, immune cells, fibroblasts, bone marrow-derived inflammatory cells, various signaling molecules, and extracellular matrix. A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment, which can reveal problems that conventional research techniques cannot, potentially leading to the development of novel therapeutic agents for cancer. This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.

Network pharmacology and bioinformatics were used to construct a prognostic model and immunoassay of core target genes in the combination of quercetin and kaempferol in the treatment of colorectal cancer.

Purpose: CRC is a malignant tumor seriously threatening human health. Quercetin and kaempferol are representative components of traditional Chinese medicine (TCM). Previous studies have shown that both quercetin and kaempferol have antitumor pharmacological effects, nevertheless, the underlying mechanism of action remains unclear. To explore the synergy and mechanism of quercetin and kaempferol in colorectal cancer. Methods: In this study, network pharmacology, and bioinformatics are used to obtain the intersection of drug targets and disease genes. Training gene sets were acquired from the TCGA database, acquired prognostic-related genes by univariate Cox, multivariate Cox, and Lasso-Cox regression models, and validated in the GEO dataset. We also made predictions of the immune function of the samples and used molecular docking to map a model for binding two components to prognostic genes. Results: Through Lasso-Cox regression analysis, we obtained three models of drug target genes. This model predicts the combined role of quercetin and kaempferol in the treatment and prognosis of CRC. Prognostic genes are correlated with immune checkpoints and immune infiltration and play an adjuvant role in the immunotherapy of CRC. Conclusion: Core genes are regulated by quercetin and kaempferol to improve the patient's immune system and thus assist in the treatment of CRC.

Integration of molecular docking, molecular dynamics and network pharmacology to explore the multi-target pharmacology of fenugreek against diabetes.

Fenugreek is an ancient herb that has been used for centuries to treat diabetes. However, how the fenugreek-derived chemical compounds work in treating diabetes remains unclarified. Herein, we integrate molecular docking and network pharmacology to elucidate the active constituents and potential mechanisms of fenugreek against diabetes. First, 19 active compounds from fenugreek and 71 key diabetes-related targets were identified through network pharmacology analysis. Then, molecular docking and simulations results suggest diosgenin, luteolin and quercetin against diabetes via regulation of the genes ESR1, CAV1, VEGFA, TP53, CAT, AKT1, IL6 and IL1. These compounds and genes may be key factors of fenugreek in treating diabetes. Cells results demonstrate that fenugreek has good biological safety and can effectively improve the glucose consumption of IR-HepG2 cells. Pathway enrichment analysis revealed that the anti-diabetic effect of fenugreek was regulated by the AGE-RAGE and NF-κB signalling pathways. It is mainly associated with anti-oxidative stress, anti-inflammatory response and ß-cell protection. Our study identified the active constituents and potential signalling pathways involved in the anti-diabetic effect of fenugreek. These findings provide a theoretical basis for understanding the mechanism of the anti-diabetic effect of fenugreek. Finally, this study may help for developing anti-diabetic dietary supplements or drugs based on fenugreek.

circSPECC1 Promotes Proliferation and Migration of LNCaP Prostate Cancer Cells by Affecting Their Epithelial-Mesenchymal Transition.

Objective: To determine the effects of circSPECC1 (hsa_circ_0000745) on the proliferation and migration of LNCaP prostate cancer cells and to explore the potential molecular mechanism. Methods: Stable circSPECC1 shRNA-expressing and circSPECC1-overexpressing LNCaP cell lines were constructed, and relative gene expression levels were determined by RT-PCR. MTT and clonogenic assays were used to assess proliferative ability while a scratch test was used to analyze cell migration. Western blotting was used to determine protein expression levels. The effects of circSPECC1 on the proliferation of LNCaP prostate cancer cells were observed in vivo. Results: circSPECC1 was found to be derived from the SPECC1 (sperm antigen with calponin homology and coiled-coil domains 1) parent gene and to form a loop. Overexpression of circSPECC1 promoted the proliferation and migration of the LNCaP cells, whereas decreased expression of circSPECC1 inhibited these properties. Overexpression of circSPECC1 promoted the expression of MMP-2, MMP-9, VEGF, vimentin, and N-cad but downregulated the expression of E-cad. Decreased expression of circSPECC1 inhibited the expression of MMP-2, MMP-9, VEGF, vimentin, and N-cad but increased the expression of E-cad. Conclusion: circSPECC1 promotes cell proliferation and migration by affecting the epithelial-mesenchymal transition of LNCaP prostate cancer cells.

Image-guided Thermal Ablation as a Promising Approach to Both Nontoxic and Toxic Autonomously Functioning Thyroid Nodules.

RATIONALE AND OBJECTIVES: Although thermal ablation has been recommended as an alternative therapy option for autonomously functioning thyroid nodules (AFTN), current clinical evidence mainly focuses on toxic AFTN. This study aims to evaluate and compare the efficacy and safety of thermal ablation (percutaneous radiofrequency ablation or microwave ablation) in treating nontoxic and toxic AFTN. MATERIALS AND METHODS: AFTN patients who received a single session of thermal ablation with a follow-up period ≥12 months were recruited. Changes in nodule volume and thyroid function, and complications were evaluated. Technical efficacy was defined as the maintenance or restoration of euthyroidism with a volume reduction rate (VRR) ≥80% at the last follow-up. RESULTS: In total, 51 AFTN patients (age: 43.8±13.9 years, female: 88.2%) with a median follow-up period of 18.0 (12.0-24.0) months were included, where 31 were nontoxic (nontoxic group), and 20 were toxic (toxic group) before ablation. The median VRR was 96.3% (80.1%-98.5%) and 88.3% (78.3%-96.2%) in the nontoxic and toxic groups, respectively, and the respective euthyroidism rates were 93.5% (29/31, 2 evolved to toxic) and 75.0% (15/20, 5 remained toxic). The corresponding technical efficacy was 77.4% (24/31) and 55.0% (11/20, p=0.126). Except for one case of stress-induced cardiomyopathy in the toxic group, no permanent hypothyroidism or other major complications occurred in both groups. CONCLUSION: Image-guided thermal ablation is efficacious and safe in treating AFTN, both nontoxic and toxic. Recognition of nontoxic AFTN would be helpful for treatment, efficacy evaluation, and follow-up.

Progress in the application of body fluid and tissue level mRNAs-non-coding RNAs for the early diagnosis and prognostic evaluation of systemic lupus erythematosus.

The diagnosis and differential classification of systemic lupus erythematosus (SLE) is difficult, especially in patients with early-onset SLE who are susceptible to systemic multi-organ damage and serious complications and have difficulties in individualized treatment. At present, diagnosis is based mainly on clinical manifestations and the detection of serological antinuclear antibodies. The pathogenesis of SLE involves multiple factors, is clinically heterogeneous, and lacks specific biomarkers. Therefore, it is necessary to identify new biomarkers for the diagnosis and subtype classification of SLE. Non-coding RNAs (ncRNAs) are composed of microRNAs, long non-coding RNAs, small nucleolar RNAs, circular RNAs, and transfer RNAs. They play an important role in the occurrence and development of diseases and are used widely in the early diagnosis and prognosis of autoimmune diseases. In this review, we focus on the research progress in the diagnosis and prognostic assessment of SLE using humoral to tissue level ncRNAs.

Multifunctional tunable visible light metalens based on double-layer barium titanate.

A tunable metalens plays an indispensable role in the development of integrated optics, multi-imaging systems, etc. We propose a multifunctional tunable metalens that combines a double-layer barium titanate (BTO) structure and geometric phase in the visible light band. The refractive indices of the upper and lower layer BTO nanorods can be tuned continuously and independently by applying external voltage (0-60 V), and the lower layer can be converted between a full-wave plate and normal scattering unit, while the scatterers of the upper layer can be switched between a half-wave plate and full-wave plate. The voltages of the upper and lower layers can be adjusted to achieve different functions such as optical switches, conversion between monofocal and bifocal metalenses, adjustment of bifocal intensity, and broadband focusing (585-690 nm). Simulation results show that the multifunctional tunable metalens has a good focusing effect. A metalens with high focusing efficiency, dynamic reconfigurability, and a switching function has tremendous application potential in the fields of multifunctional devices, biomedicine, optical communication, imaging, and so on.

Design of a vortex metalens with high focusing efficiency using propagation phase.

Three vortex-focused beams are produced with linearly polarized light along the x or y axis at a wavelength of 1550 nm. First, a polarization-independent vortex metalens with a topological charge of three and focal length of 3000 nm is designed by selecting cylindrical-shaped elements. This design has a focusing efficiency of 83%. Second, vortex beams with different focal lengths and topological charges are achieved by combining various shapes of structures. Both designs have a focusing efficiency of greater than 92%. The designed metasurface is of great significance to optical communication and radar detection.