Hyperbaric Lidocaine Aggravates Diabetic Neuropathic Pain by Targeting p38 MAPK/ERK and PINK1/Parkin-Mediated Mitophagy Signaling Pathway.

BACKGROUND: Diabetic neuropathic pain (DNP) is a complication of diabetes mellitus (DM). Hyperbaric lidocaine (HL), a local anesthetics drug, has neurotoxicity. The present study aims to study the effect and molecular mechanisms of HL on spinal nerve injury in DNP. METHODS: The DNP rat model was established through a high-fat-glucose diet in combination with Streptozotocin (STZ) administration. SB203580 and PD98059 were utilized to inhibit p38 mitogen-activated protein kinase (p38 MAPK) and extracellular signal-regulated kinase (ERK). The mechanical paw withdrawal threshold (PWT) and the thermal paw withdrawal latency (PWL) were tested to evaluate rats' mechanical allodynia and thermal hyperalgesia. Hematoxylin-eosin (H&E) and terminal deoxynucleotidyltransferase-mediated dUTP nick-end Labeling (TUNEL) staining were performed to evaluate the pathological changes and neuron apoptosis in spinal cord tissues of L4-5. Western blotting analysis and reverse transcription-polymerase chain reaction (RT-qPCR) assay were used to measure the levels of proteins and mRNAs, respectively. RESULTS: PWT and PWL were decreased in DNP rats with serious spinal nerve injury. HL administration downregulated the PWT and PWL and aggravated spinal nerve injury in DNP rats, but isobaric lidocaine had no effects on these changes. Meanwhile, p38 MAPK/ERK signaling and PTEN-induced kinase 1 (PINK1)-mediated mitophagy were activated in DNP, which was enhanced by HL but not isobaric lidocaine. Blocking p38 MAPK/ERK signaling could effectively attenuate HL-induced spinal nerve injury and inhibit mitophagy. CONCLUSION: In summary, HL can aggravate spinal cord tissue damage in DNP rats by inducing PINK1-mediated mitophagy via activating p38 MAPK/ERK signaling. Our data provide a novel insight that supports the potential role of p38 MAPK/ERK signaling in acting as a therapeutic target for HL-induced neurotoxicity.

Musical protein: Mapping the time sequence of music onto the spatial architecture of proteins.

BACKGROUND AND OBJECTIVE: Music, the ubiquitous language across human cultures, is traditionally considered as a form of art but has been linked to biomolecules in recent years. However, previous efforts have only been addressed on sonification of nucleic acids and proteins to produce so-called life music, the soundscape from the basic building blocks of life. In this study, we attempted to, for the first time, conduct a reverse operation of this process, i.e. conversion of music to protein (CoMtP). METHODS: A novel notion termed musical protein (MP) -- the protein defined by music -- was proposed and, on this basis, we described a computational strategy to map the time sequence of music onto the spatial architecture of proteins, which considered that each note in the stave of a music (target) can be simply characterized by two acoustical quantities and that each residue in the primary sequence of a protein (hit) was represented by amino acid descriptors. RESULTS: A simulated annealing (SA) algorithm was applied to iteratively generate the best matched MP hit for a music target and structural bioinformatics was then used to model spatial advanced structure for the resulting MP. We also demonstrated that some small MPs derived from music segments may have potential biological functions, which, for example, can serve as antimicrobial peptides (AMPs) to inhibit clinical bacterial strains with moderate or high antibacterial potency. CONCLUSIONS: This work may benefit many aspects; for example, it would open a door for the hearing-impaired persons to 'listen' music in a biological vision and could be a mean of exposing students to the concepts of biomolecules at an earlier age through the use of auditory characteristics. The CoMtP would also facilitate the rational design of proteins with biological and medicinal significance.

The association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio with type 2 diabetes mellitus: recent findings from NHANES 2007-2018.

OBJECTIVE: This study aims to assess the relationship between NHHR (non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio) and Type 2 diabetes mellitus (T2DM) in US adults, using National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018. METHODS: This study explored the connection between NHHR and T2DM by analyzing a sample reflecting the adult population of the United States (n = 10,420; NHANES 2007-2018). NHHR was characterized as the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol. T2DM was defined based on clinical guidelines. This research used multivariable logistic models to examine the connection between NHHR and T2DM. Additionally, it included subgroup and interaction analyses to assess variations among different groups. Generalized additive models, smooth curve fitting, and threshold effect analysis were also employed to analyze the data further. RESULTS: The study included 10,420 subjects, with 2160 diagnosed with T2DM and 8260 without. The weighted multivariate logistic regression model indicated an 8% higher probability of T2DM for each unit increase in NHHR (OR: 1.08, 95% CI: 1.01-1.15) after accounting for all covariates. Subgroup analysis outcomes were uniform across various categories, demonstrating a significant positive relationship between NHHR and T2DM. Interaction tests showed that the positive link between NHHR and T2DM remained consistent regardless of age, body mass index, smoking status, moderate recreational activities, hypertension, or stroke history, with all interaction P-values exceeding 0.05. However, participants' sex appeared to affect the magnitude of the connection between NHHR and T2DM (interaction P-value < 0.05). Also, a nonlinear association between NHHR and T2DM was discovered, featuring an inflection point at 1.50. CONCLUSIONS: Our study suggests that an increase in NHHR may be correlated with a heightened likelihood of developing T2DM. Consequently, NHHR could potentially serve as a marker for estimating the probability of T2DM development.

Coping with alpine habitats: genomic insights into the adaptation strategies of Triplostegia glandulifera (Caprifoliaceae).

How plants find a way to thrive in alpine habitats remains largely unknown. Here we present a chromosome-level genome assembly for an alpine medicinal herb, Triplostegia glandulifera (Caprifoliaceae), and 13 transcriptomes from other species of Dipsacales. We detected a whole-genome duplication event in T. glandulifera that occurred prior to the diversification of Dipsacales. Preferential gene retention after whole-genome duplication was found to contribute to increasing cold-related genes in T. glandulifera. A series of genes putatively associated with alpine adaptation (e.g. CBFs, ERF-VIIs, and RAD51C) exhibited higher expression levels in T. glandulifera than in its low-elevation relative, Lonicera japonica. Comparative genomic analysis among five pairs of high- vs low-elevation species, including a comparison of T. glandulifera and L. japonica, indicated that the gene families related to disease resistance experienced a significantly convergent contraction in alpine plants compared with their lowland relatives. The reduction in gene repertory size was largely concentrated in clades of genes for pathogen recognition (e.g. CNLs, prRLPs, and XII RLKs), while the clades for signal transduction and development remained nearly unchanged. This finding reflects an energy-saving strategy for survival in hostile alpine areas, where there is a tradeoff with less challenge from pathogens and limited resources for growth. We also identified candidate genes for alpine adaptation (e.g. RAD1, DMC1, and MSH3) that were under convergent positive selection or that exhibited a convergent acceleration in evolutionary rate in the investigated alpine plants. Overall, our study provides novel insights into the high-elevation adaptation strategies of this and other alpine plants.

Stepwise structural evolution toward robust carboranealkynyl-protected copper nanocluster catalysts for nitrate electroreduction.

Atomically precise metal nanoclusters (NCs) are emerging as idealized model catalysts for imprecise metal nanoparticles to unveil their structure-activity relationship. However, the directional synthesis of robust metal NCs with accessible catalytic active sites remains a great challenge. In this work, we achieved bulky carboranealkynyl-protected copper NCs, the monomer Cu13·3PF6 and nido-carboranealkynyl bridged dimer Cu26·4PF6, with fair stability as well as accessible open metal sites step by step through external ligand shell modification and metal-core evolution. Both Cu13·3PF6 and Cu26·4PF6 demonstrate remarkable catalytic activity and selectivity in electrocatalytic nitrate (NO3-) reduction to NH3 reaction, with the dimer Cu26·4PF6 displaying superior performance. The mechanism of this catalytic reaction was elucidated through theoretical computations in conjunction with in situ FTIR spectra. This study not only provides strategies for accessing desired copper NC catalysts but also establishes a platform to uncover the structure-activity relationship of copper NCs.

Electrocatalytic Nitrate Reduction on Metallic CoNi-Terminated Catalyst with Industrial-Level Current Density in Neutral Medium.

Green ammonia synthesis through electrocatalytic nitrate reduction reaction (eNO3RR) can serve as an effective alternative to the traditional energy-intensive Haber-Bosch process. However, achieving high Faradaic efficiency (FE) at industrially relevant current density in neutral medium poses significant challenges in eNO3RR. Herein, with the guidance of theoretical calculation, a metallic CoNi-terminated catalyst is successfully designed and constructed on copper foam, which achieves an ammonia FE of up to 100% under industrial-level current density and very low overpotential (-0.15 V versus reversible hydrogen electrode) in a neutral medium. Multiple characterization results have confirmed that the maintained metal atom-terminated surface through interaction with copper atoms plays a crucial role in reducing overpotential and achieving high current density. By constructing a homemade gas stripping and absorption device, the complete conversion process for high-purity ammonium nitrate products is demonstrated, displaying the potential for practical application. This work suggests a sustainable and promising process toward directly converting nitrate-containing pollutant solutions into practical nitrogen fertilizers.

Efficacy and safety of dabigatran and rivaroxaban in atrial fibrillation patients with impaired liver function: a multicenter retrospective cohort study.

BACKGROUND: The efficacy and safety of direct oral anticoagulants (DOACs) in atrial fibrillation (AF) patients with impaired liver function (ILF) have not been sufficiently studied. The aim of this study was to evaluate the efficacy and safety of DOACs for stroke prevention in patients with AF and ILF. METHOD: This study was based on data from 15 centers in China, including 4,982 AF patients. The patients were divided into 2 subgroups based on their liver function status: patients with normal liver function (NLF)(n = 4213) and patients with ILF (n = 769). Logistic regression analysis was used to investigate the risk of total bleeding, major bleeding, thromboembolism, and all-cause deaths in AF patients with NLF and ILF after taking dabigatran or rivaroxaban, respectively. RESULTS: Among AF patients treated with dabigatran or rivaroxaban, patients with ILF were associated with significantly higher major bleeding, compared with NLF patients (aOR: 4.797; 95% CI: 2.224-10.256; P < 0.001). In patients with NLF, dabigatran (n = 2011) had considerably lower risk of total bleeding than rivaroxaban (n = 2202) (aOR: 1.23; 95% CI: 1.002-1.513; P = 0.049). In patients with ILF, dabigatran (n = 321) significantly favored lower risks of major bleeding compared with rivaroxaban(n = 448) (aOR: 5.484; 95% CI: 1.508-35.269; P = 0.026). CONCLUSION: After using dabigatran or rivaroxaban, patients with ILF had remarkably increased risk of major bleeding compared with patients with NLF. In AF patients with NLF, dabigatran had the distinct strength of significantly reduced risk of total bleeding compared with rivaroxaban. In patients with AF and ILF, dabigatran use was associated with lower risk for major bleeding compared with rivaroxaban.

Surface protein profiling and subtyping of extracellular vesicles in body fluids reveals non-CSF biomarkers of Alzheimer's disease.

Noninvasive and effortless diagnosis of Alzheimer's disease (AD) remains challenging. Here we report the multiplexed profiling of extracellular vesicle (EV) surface proteins at the single EV level in five types of easily accessible body fluids using a proximity barcoding assay (PBA). A total of 183 surface proteins were detected on the EVs from body fluids collected from APP/PS1 transgenic mice and patients with AD. The AD-associated differentially expressed EV proteins could discriminate between the control and AD/AD model samples with high accuracy. Based on machine learning predictive models, urinary EV proteins exhibited the highest diagnostic potential compared to those on other biofluid EVs, both in mice and humans. Single EV analysis further revealed AD-associated EV subpopulations in the tested body fluids, and a urinary EV subpopulation with the signature proteins PLAU, ITGAX and ANXA1 could diagnose patients with AD in blinded datasets with 88% accuracy. Our results suggest that EVs and their subpopulations from noninvasive body fluids, particularly urine, are potential diagnostic biomarkers for AD.

Imaging predictors of hemorrhagic progression of a contusion after traumatic brain injury: a systematic review and meta-analysis.

The hemorrhagic progression of a contusion (HPC) after Traumatic brain injury (TBI) is one of the important causes of death in trauma patients. The purpose of this meta-analysis was to evaluate the predictive effect of imaging features of Computed tomography (CT) on HPC after TBI. A comprehensive systematic search was performed using PubMed, EMBASE, and WEB OF SCIENCE databases to identify all relevant literature. A total of 8 studies involving 2543 patients were included in this meta-analysis. Meta-analysis showed that subarachnoid hemorrhage (OR 3.28; 95% CI 2.57-4.20), subdural hemorrhage (OR 4.35; 95% CI 3.29-5.75), epidural hemorrhage (OR 1.47;95% CI 1.15-1.89), contrast extravasation (OR 11.81; 95% CI 4.86-28.71) had a predictive effect on the occurrence of HPC. Skull fracture (OR 1.64; 95% CI 0.84-3.19) showed no statistical significance, and midline displacement > 5 mm (OR 4.66; 95% CI 1.87-11.62) showed high heterogeneity. The results of this meta-analysis showed that some imaging features were effective predictors of HPC after TBI. Well-designed prospective studies are needed to more accurately assess the effective predictors of HPC after TBI.

A scenario-based web app to facilitate patient education in lung tumor patients undergoing video-assisted thoracoscopic surgery: Development and usability testing.

Background: Patient education (PE) is essential for improving patients' knowledge, anxiety, and satisfaction, and supporting their postoperative recovery. However, the advantages of video-assisted thoracoscopic surgery (VATS)-smaller incisions and faster recovery-can result in shorter hospital stays, making PE more challenging to implement effectively. Multimedia PE can potentially enhance PE, but its effectiveness for patients undergoing VATS is unclear. Objective: This study developed a scenario-based PE web app for lung tumor patients undergoing VATS (SPE-VATS) to facilitate the PE process and evaluated its usability through a clinical trial. Methods: The SPE-VATS provided the experimental group (EG: 32 participants) with interactive scenario, query guidance, diagnostic analysis, experience sharing, and active reminder, while the control group (CG: 32 participants) used pamphlets and videos. The usability of SPE-VATS in terms of postoperative anxiety reduction and patient satisfaction with the app was evaluated using self-reported questionnaires based on the state-trait anxiety inventory, technology acceptance model, system usability scale, and task load index. Results: There was no statistically significant difference in postoperative anxiety reduction between the EG and CG, possibly because 90% of the participants underwent a low-risk surgical type, and VATS is known to be advantageous in alleviating surgical anxiety. However, females and higher educated EG participants showed a non-significant but favorable reduction than their CG counterparts. Moreover, the EG was highly satisfied with the app (rated 4.2 to 4.4 out of 5.0), with no significant gender and education level difference. They particularly valued the interactive scenario, experience sharing, and diagnostic analysis features of SPE-VATS. Conclusions: The SPE-VATS demonstrated its usability and high patient satisfaction, particularly for female and higher educated patients. Low-risk patient predominance and VATS's advantages may explain non-significant postoperative anxiety reduction, warranting further studies on high-risk patients to evaluate the impact of SPE-VATS on clinical practice.

Prediction Model of Lean Coal Adsorption of Power Plant Flue Gas.

To minimize errors in calculating coal flue gas adsorption capacity due to gas compressibility and to preclude prediction inaccuracies in abandoned mine flue gas storage capacity for power plants, it is imperative to account for the influence of compression factor calculation accuracy while selecting the optimal theoretical adsorption model. In this paper, the flue gas adsorption experiment of a power plant with coal samples gradually pressurized to close to 5 MPa at two different temperatures is carried out, and the temperature and pressure data obtained from the experiment are substituted into five different compression factor calculation methods to calculate different absolute adsorption amounts. The calculated adsorption capacities were fitted into six theoretical adsorption models to establish a predictive model suitable for estimating the coal adsorption capacity in power plant flue gas. Results reveal significant disparities in the absolute adsorption capacity determined by different compression factors, with an error range of 0.001278-7.8262 (cm3/kg). The Redlich-Kwong equation of state emerged as the most suitable for the flue gas of the selected experimental coal sample and the chosen composition ratio among the five compression factors. Among the six theoretical adsorption models, the Brunauer-Emmett-Teller model with three parameters demonstrated the highest suitability for predicting the adsorption capacity of coal samples in power plant smoke, achieving a fitting accuracy as high as 0.9922 at 49.7 °C.

Identification of the HLA-A*11:463 allele in a Chinese patient and his father.

HLA-A*11:463 has one nucleotide change from HLA-A*11:01:01:01 at nucleotide 508 changing Lysine (146) to Glutamine.

Molecular features and clinical outcomes of EGFR-mutated, MET-amplified non-small-cell lung cancer after resistance to dual-targeted therapy.

Background: Some studies of dual-targeted therapy (DTT) targeting epidermal growth factor receptor (EGFR) and mesenchymal-epithelial transition (MET) have shown promising efficacy in non-small-cell lung cancer (NSCLC). Consequently, patient management following DTT resistance has gained significance. However, the underlying resistance mechanisms and clinical outcomes in these patients remain unclear. Objectives: This study aimed to delineate the molecular characteristics and survival outcomes of patients with NSCLC harboring EGFR mutations and acquired MET amplification after developing resistance to DTT. Design: We conducted a retrospective analysis of patients with NSCLC with EGFR mutations and acquired MET amplification who exhibited resistance to EGFR/MET DTT. Methods: Next-generation sequencing (NGS) was performed on patients with available tissue samples before and/or after the development of resistance to DTT. Stratified analyses were carried out based on data sources and subsequent salvage treatments. Univariate/multivariate Cox regression models and survival analyses were employed to explore potential independent prognostic factors. Results: The study included 77 NSCLC patients, with NGS conducted on 19 patients. We observed many resistance mechanisms, including EGFR-dependent pathways (4/19, 21.1%), MET-dependent pathways (2/19, 10.5%), EGFR/MET co-dependent pathways (2/19, 10.5%), and EGFR/MET-independent resistance mechanisms (11/19, 57.9%). Post-progression progression-free survival (pPFS) and post-progression overall survival (pOS) significantly varied among patients who received the best supportive care (BSC), targeted therapy, or chemotherapy (CT), with median pPFS of 1.5, 3.9, and 4.9 months, respectively (p = 0.003). Median pOS were 2.3, 7.7, and 9.2 months, respectively (p < 0.001). The number of treatment lines following DTT resistance and the Eastern Cooperative Oncology Group performance status emerged as the independent prognostic factors. Conclusion: This study revealed a heterogeneous landscape of resistance mechanisms to EGFR/MET DTT, with a similar prevalence of on- and off-target mechanisms. Targeted therapy or CT, as compared to BSC, exhibited the potential to improve survival outcomes for patients with advanced NSCLC following resistance to DTT.

Identification and validation of a metabolism-related gene signature for predicting the prognosis of paediatric medulloblastoma.

Medulloblastoma (MB) is a malignant brain tumour that is highly common in children and has a tendency to spread to the brain and spinal cord. MB is thought to be a metabolically driven brain tumour. Understanding tumour cell metabolic patterns and characteristics can provide a promising foundation for understanding MB pathogenesis and developing treatments. Here, by analysing RNA-seq data of MB samples from the Gene Expression Omnibus (GEO) database, 12 differentially expressed metabolic-related genes (DE-MRGs) were chosen for the construction of a predictive risk score model for MB. This model demonstrated outstanding accuracy in predicting the outcomes of MB patients and served as a standalone predictor. An evaluation of functional enrichment revealed that the risk score showed enrichment in pathways related to cancer promotion and the immune response. In addition, a high risk score was an independent poor prognostic factor for MB in patients with different ages, sexes, metastasis stages and subgroups (SHH and Group 4). Consistently, the metabolic enzyme ornithine decarboxylase (ODC1) was upregulated in MB patients with poor survival time. Inhibition of ODC1 in primary and metastatic MB cell lines decreased cell proliferation, migration and invasion but increased immune infiltration. This study could aid in identifying metabolic targets for MB as well as optimizing risk stratification systems and individual treatment plans for MB patients via the use of a metabolism-related gene prognostic risk score signature.

Identification of pine wood nematode (Bursaphelenchus xylophilus) loading response genes in Japanese pine sawyer (Monochamus alternatus) through comparative genomics and transcriptomics.

BACKGROUND: Pine wood nematode (PWN; Bursaphelenchus xylophilus) is the causative agent of pine wilt disease (PWD), which is considered the most dangerous biohazard to conifer trees globally. The transmission of PWN relies on insect vectors, particularly the Japanese pine sawyer (JPS; Monochamus alternatus). However, the molecular mechanism underlying PWN-JPS assembly remains largely unknown. RESULTS: Here, we found that both geographical and gender could significantly affect the PCA (PWN carrying amount) of JPS; thus, JPS transcriptomes from diverse locations and genders were explored regard to PWN loading. Due to the shortage of genomes, we developed a full-length reference transcriptome for analyzing next-generation sequencing data. A comparative genomic study was performed, and 11 248 potential PWN-carrying associate genes (ß) were nominated in JPS by using the reported genomes of PWN and non-PWN carrier insect species. Then, 151 differentially expressed transcripts (DETs), 28 of them overlapped with ß, correlated with the PCA of JPS were nominated by RNA-Seq, and found that fatty acid ß-oxidation might be the key factor that affected the PCA of JPS. Furthermore, JPS fatty acid ß-oxidation rates were experimentally decreased using the inhibitor Etomoxir, leading to an increased PCA of JPS. Meanwhile, silencing MaCPT1 in JPS by RNA interference led to a decreased fatty acid ß-oxidation rate and increased PCA of JPS. CONCLUSIONS: In conclusion, MaCPT1 was able to decrease the PWN-JPS assembly formation through the fatty acid ß-oxidation of JPS. These results provide new insights for exploring the impact of PWN invasion on JPS. © 2024 Society of Chemical Industry.

Comprehensive phytohormone metabolomic and transcriptomic analysis of tobacco (Nicotiana tabacum) infected by tomato spotted wilt virus (TSWV).

Tomato spotted wilt virus (TSWV) is ranked among the top 10 most destructive viruses globally. It results in abnormal leaf growth, stunting, and even death, significantly affecting crop yield and quality. Phytohormones play a crucial role in regulating plant-virus interactions. However, there is still limited research on the effect of TSWV on phytohormone levels, particularly growth hormones and genes involved in the phytohormone pathway. In our study, we combined phytohormone metabolomics and transcriptomics to examine the impact of TSWV infection on phytohormone content and gene expression profile. Metabolomic results showed that 41 metabolites, including major phytohormones and their precursors and derivatives were significantly altered after 14 days of TSWV inoculation tobacco plants cvK326, with 31 being significantly increased and 10 significantly reduced. Specifically, the levels of abscisic acid (ABA) and jasmonoyl-isoleucine (JA-Ile) were significantly reduced. The levels of indole-3-acetic acid (IAA) have remained unchanged. However, the levels of cytokinin isopentenyladenine (iP) and salicylic acid (SA) significantly increased. The transcriptome analysis revealed 2,746 genes with significant changes in expression. Out of these, 1,072 genes were significantly downregulated, while 1,674 genes were significantly upregulated. Among them, genes involved in ABA synthesis and signaling pathways, such as 9-cis-epoxycarotenoid dioxygenase (NCED), protein phosphatase 2C (PP2C), serine/threonine-protein kinase (SnRK2), and abscisic acid responsive element binding factor (ABF), exhibited significant downregulation. Additionally, expression of the lipoxygenase gene LOX, Jasmonate ZIM domain-containing protein gene JAZ, and transcription factor gene MYC were significantly down-regulated. In the cytokinin pathway, while there were no significant changes in the expression of the cytokinin synthesis genes, a significant downregulation of transcriptionally active factor type-B response regulators (type-B RRs) was observed. In terms of SA synthesis and signaling pathways, the isochorismate synthase gene ICS1 and the pathogenesis-related gene PR1 were significantly upregulated. These results can strengthen the theoretical foundation for understanding the interaction between TSWV and tobacco and provide new insights for the future prevention and control of TSWV.

Non-invasive prediction of the chronic degree of lupus nephropathy based on ultrasound radiomics.

OBJECTIVE: Through machine learning (ML) analysis of the radiomics features of ultrasound extracted from patients with lupus nephritis (LN), this attempt was made to non-invasively predict the chronicity index (CI)of LN. METHODS: A retrospective collection of 136 patients with LN who had renal biopsy was retrospectively collected, and the patients were randomly divided into training set and validation set according to 7:3. Radiomics features are extracted from ultrasound images, independent factors are obtained by using LASSO dimensionality reduction, and then seven ML models were used to establish predictive models. At the same time, a clinical model and an US model were established. The diagnostic efficacy of the model is evaluated by analysis of the receiver operating characteristics (ROC) curve, accuracy, specificity, and sensitivity. The performance of the seven machine learning models was compared with each other and with clinical and US models. RESULTS: A total of 1314 radiomics features are extracted from ultrasound images, and 5 features are finally screened out by LASSO for model construction, and the average ROC of the seven ML is 0.683, among which the Xgboost model performed the best, and the AUC in the test set is 0.826 (95% CI: 0.681-0.936). For the same test set, the AUC of clinical model constructed based on eGFR is 0.560 (95% CI: 0.357-0.761), and the AUC of US model constructed based on Ultrasound parameters is 0.679 (95% CI: 0.489-0.853). The Xgboost model is significantly more efficient than the clinical and US models. CONCLUSION: ML model based on ultrasound radiomics features can accurately predict the chronic degree of LN, which can provide a valuable reference for clinicians in the treatment strategy of LN patients.