Cholinergic macrophages promote the resolution of peritoneal inflammation.

The non-neural cholinergic system plays a critical role in regulating immune equilibrium and tissue homeostasis. While the expression of choline acetyltransferase (ChAT), the enzyme catalyzing acetylcholine biosynthesis, has been well documented in lymphocytes, its role in the myeloid compartment is less understood. Here, we identify a significant population of macrophages (Mϕs) expressing ChAT and synthesizing acetylcholine in the resolution phase of acute peritonitis. Using Chat-GFP reporter mice, we observed marked upregulation of ChAT in monocyte-derived small peritoneal Mϕs (SmPMs) in response to Toll-like receptor agonists and bacterial infections. These SmPMs, phenotypically and transcriptionally distinct from tissue-resident large peritoneal macrophages, up-regulated ChAT expression through a MyD88-dependent pathway involving MAPK signaling. Notably, this process was attenuated by the TRIF-dependent TLR signaling pathway, and our tests with a range of neurotransmitters and cytokines failed to induce a similar response. Functionally, Chat deficiency in Mϕs led to significantly decreased peritoneal acetylcholine levels, reduced efferocytosis of apoptotic neutrophils, and a delayed resolution of peritonitis, which were reversible with exogenous ACh supplementation. Intriguingly, despite B lymphocytes being a notable ChAT-expressing population within the peritoneal cavity, Chat deletion in B cells did not significantly alter the resolution process. Collectively, these findings underscore the crucial role of Mϕ-derived acetylcholine in the resolution of inflammation and highlight the importance of the non-neuronal cholinergic system in immune regulation.

SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations.

Transcriptome-wide association studies (TWAS) integrate gene expression prediction models and genome-wide association studies (GWAS) to identify gene-trait associations. The power of TWAS is determined by the sample size of GWAS and the accuracy of the expression prediction model. Here, we present a new method, the Summary-level Unified Method for Modeling Integrated Transcriptome using Functional Annotations (SUMMIT-FA), which improves gene expression prediction accuracy by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models in whole blood using SUMMIT-FA with the comprehensive functional database MACIE and eQTL summary-level data from the eQTLGen consortium. We apply these models to GWAS for 24 complex traits and show that SUMMIT-FA identifies significantly more gene-trait associations and improves predictive power for identifying "silver standard" genes compared to several benchmark methods. We further conduct a simulation study to demonstrate the effectiveness of SUMMIT-FA.

Regional analysis to delineate intrasample heterogeneity with RegionalST.

MOTIVATION: Spatial transcriptomics has greatly contributed to our understanding of spatial and intra-sample heterogeneity, which could be crucial for deciphering the molecular basis of human diseases. Intra-tumor heterogeneity, e.g. may be associated with cancer treatment responses. However, the lack of computational tools for exploiting cross-regional information and the limited spatial resolution of current technologies present major obstacles to elucidating tissue heterogeneity. RESULTS: To address these challenges, we introduce RegionalST, an efficient computational method that enables users to quantify cell type mixture and interactions, identify sub-regions of interest, and perform cross-region cell type-specific differential analysis for the first time. Our simulations and real data applications demonstrate that RegionalST is an efficient tool for visualizing and analyzing diverse spatial transcriptomics data, thereby enabling accurate and flexible exploration of tissue heterogeneity. Overall, RegionalST provides a one-stop destination for researchers seeking to delve deeper into the intricacies of spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The implementation of our method is available as an open-source R/Bioconductor package with a user-friendly manual available at https://bioconductor.org/packages/release/bioc/html/RegionalST.html.

Analysis of endophytic bacterial diversity in seeds of different genotypes of cotton and the suppression of Verticillium wilt pathogen infection by a synthetic microbial community.

BACKGROUND: In agricultural production, fungal diseases significantly impact the yield and quality of cotton (Gossypium spp.) with Verticillium wilt posing a particularly severe threat. RESULTS: This study is focused on investigating the effectiveness of endophytic microbial communities present in the seeds of disease-resistant cotton genotypes in the control of cotton Verticillium wilt. The technique of 16S ribosomal RNA (16S rRNA) amplicon sequencing identified a significant enrichment of the Bacillus genus in the resistant genotype Xinluzao 78, which differed from the endophytic bacterial community structure in the susceptible genotype Xinluzao 63. Specific enriched strains were isolated and screened from the seeds of Xinluzao 78 to further explore the biological functions of seed endophytes. A synthetic microbial community (SynCom) was constructed using the broken-rod model, and seeds of the susceptible genotype Xinluzao 63 in this community that had been soaked with the SynCom were found to significantly control the occurrence of Verticillium wilt and regulate the growth of cotton plants. Antibiotic screening techniques were used to preliminarily identify the colonization of strains in the community. These techniques revealed that the strains can colonize plant tissues and occupy ecological niches in cotton tissues through a priority effect, which prevents infection by pathogens. CONCLUSION: This study highlights the key role of seed endophytes in driving plant disease defense and provides a theoretical basis for the future application of SynComs in agriculture.

3D Fractal Dimension Analysis: Prognostic Value of Right Ventricular Trabecular Complexity in Participants with Arrhythmogenic Cardiomyopathy.

BACKGROUND: Arrhythmogenic cardiomyopathy (ACM) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. Traditionally, two-dimensional (2D) instead of 3D fractal dimension (FD) analysis has been used to evaluate trabecular disarray. However, the prognostic value of trabecular disorder assessed by 3D FD measurement remains unclear. PURPOSE: To investigate the prognostic value of right ventricular trabecular complexity in ACM patients using 3D FD analysis based on cardiac MR cine images. STUDY TYPE: Retrospective. POPULATION: 85 ACM patients (mean age: 45 ± 17 years, 52 male). FIELD STRENGTH/SEQUENCE: 3.0T/cine imaging, T2-short tau inversion recovery (T2-STIR), and late gadolinium enhancement (LGE). ASSESSMENT: Using cine images, RV (right ventricular) volumetric and functional parameters were obtained. RV trabecular complexity was measured with 3D fractal analysis by box-counting method to calculate 3D-FD. Cox and logistic regression models were established to evaluate the prognostic value of 3D-FD for major adverse cardiac events (MACE). STATISTICAL TESTS: Cox regression and logistic regression to explore the prognostic value of 3D-FD. C-index, time-dependent receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) to evaluate the incremental value of 3D-FD. Intraclass correlation coefficient for interobserver variability. P < 0.05 indicated statistical significance. RESULTS: 26 MACE were recorded during the 60 month follow-up (interquartile range: 48-67 months). RV 3D-FD significantly differed between ACM patients with MACE (2.67, interquartile range: 2.51 ~ 2.81) and without (2.52, interquartile range: 2.40 ~ 2.67) and was a significant independent risk factor for MACE (hazard ratio, 1.02; 95% confidence interval: 1.01, 1.04). In addition, prognostic model fitness was significantly improved after adding 3D-FD to RV global longitudinal strain, LV involvement, and 5-year risk score separately. DATA CONCLUSION: The myocardial trabecular complexity assessed through 3D FD analysis was found associated with MACE and provided incremental prognostic value beyond conventional ACM risk factors. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Efficient Template-Catalyzed In Situ Polymerization for Carbon Xerogels with Large Specific Surface Area and High Adsorption.

The limited specific surface area (SSA), long preparation period, and high cost are significant challenges for carbon xerogels (CXs). To overcome these limitations, we propose an approach to prepare tannin-resorcinol-formaldehyde-based CXs through template-catalyzed in situ polymerization. ZnCl2 acts as a catalyst and significantly accelerates the polymerization reaction through the coordination of Zn2+ to the carbonyl group in formaldehyde, while atmospheric drying instead of special drying and without solvent exchange reduces the preparation period to 24 h. In addition, ZnCl2 acts as an activator for the formation of many pores. Plant-derived tannins not only reduce the preparation cost but also regulate the pore structure. The resulted CXs with hierarchical porous structures show an optimal SSA of 1308 m2/g, high adsorption capabilities (for cationic, nitrosoaniline dyes, metal, and nonmetallic ions, especially for methylene blue with 454.93 mg/g), low shrinkage down to 10%, and reusability with 92.9% retention after 5 cycles. This work provides a promising and cost-effective method for the large-scale preparation of porous carbon materials with large SSA, offering potential applications in adsorption, energy storage, and catalysis.

Comparing Sonazoid contrast-enhanced ultrasound to contrast-enhanced CT and MRI for differentially diagnosing renal lesions: a prospective multicenter study.

PURPOSE: To evaluate the diagnostic performance of contrast-enhanced (CE) ultrasound using Sonazoid (SNZ-CEUS) by comparing with contrast-enhanced computed tomography (CE-CT) and contrast-enhanced magnetic resonance imaging (CE-MRI) for differentiating benign and malignant renal masses. MATERIALS AND METHODS: 306 consecutive patients (from 7 centers) with renal masses (40 benign tumors, 266 malignant tumors) diagnosed by both SNZ-CEUS, CE-CT or CE-MRI were enrolled between September 2020 and February 2021. The examinations were performed within 7 days, but the sequence was not fixed. Histologic results were available for 301 of 306 (98.37%) lesions and 5 lesions were considered benign after at least 2 year follow-up without change in size and image characteristics. The diagnostic performances were evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and compared by McNemar's test. RESULTS: In the head-to-head comparison, SNZ-CEUS and CE-MRI had comparable sensitivity (95.60 vs. 94.51%, P = 0.997), specificity (65.22 vs. 73.91%, P = 0.752), positive predictive value (91.58 vs. 93.48%) and negative predictive value (78.95 vs. 77.27%); SNZ-CEUS and CE-CT showed similar sensitivity (97.31 vs. 96.24%, P = 0.724); however, SNZ-CEUS had relatively lower than specificity than CE-CT (59.09 vs. 68.18%, P = 0.683). For nodules > 4 cm, CE-MRI demonstrated higher specificity than SNZ-CEUS (90.91 vs. 72.73%, P = 0.617) without compromise the sensitivity. CONCLUSIONS: SNZ-CEUS, CE-CT, and CE-MRI demonstrate desirable and comparable sensitivity for the differentiation of renal mass. However, the specificity of all three imaging modalities is not satisfactory. SNZ-CEUS may be a suitable alternative modality for patients with renal dysfunction and those allergic to gadolinium or iodine-based agents.

Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.

Meta-analysis is a widely used tool for synthesizing results from multiple studies. The collected studies are deemed heterogeneous when they do not share a common underlying effect size; thus, the factors attributable to the heterogeneity need to be carefully considered. A critical problem in meta-analyses and systematic reviews is that outlying studies are frequently included, which can lead to invalid conclusions and affect the robustness of decision-making. Outliers may be caused by several factors such as study selection criteria, low study quality, small-study effects, and so on. Although outlier detection is well-studied in the statistical community, limited attention has been paid to meta-analysis. The conventional outlier detection method in meta-analysis is based on a leave-one-study-out procedure. However, when calculating a potentially outlying study's deviation, other outliers could substantially impact its result. This article proposes an iterative method to detect potential outliers, which reduces such an impact that could confound the detection. Furthermore, we adopt bagging to provide valid inference for sensitivity analyses of excluding outliers. Based on simulation studies, the proposed iterative method yields smaller bias and heterogeneity after performing a sensitivity analysis to remove the identified outliers. It also provides higher accuracy on outlier detection. Two case studies are used to illustrate the proposed method's real-world performance.

Prognostic and predictive value of examined lymph node count in stage III colorectal cancer: a population based study.

BACKGROUND: The role of tumor-draining lymph nodes in the progression of malignant tumors, including stage III colorectal cancer (CRC), is critical. However, the prognostic and predictive value of the number of examined lymph nodes (ELNs) are not fully understood. METHODS: This population-based study retrospectively analyzed data from 106,843 patients with stage III CRC who underwent surgical treatment and registered in three databases from 2004 to 2021. The Surveillance, Epidemiology, and End Results (SEER) cohort was divided using into training and test cohorts at a ratio of 3:2. We employed restricted cubic spline (RCS) curves to explore nonlinear relationships between overall survival (OS) and ELNs counts and performed Cox regression to evaluate hazard ratios across different ELNs count subtypes. Additional validation cohorts were utilized from the First Affiliated Hospital, Sun Yat-sen University and The Cancer Genome Atlas (TCGA) under the same criteria. Outcomes measured included OS, cancer-specific survival (CSS), and progression-free survival (PFS). Molecular analyses involved differential gene expression using the "limma" package and immune profiling through CIBERSORT. Tissue microarray slides and multiplex immunofluorescence (MIF) were used to assess protein expression and immune cell infiltration. RESULTS: Patients with higher ELNs counts (≥ 17) demonstrated significantly better long-term survival outcomes across all cohorts. Enhanced OS, CSS, and PFS were notably evident in the LN-ELN group compared to those with fewer ELNs. Cox regression models underscored the prognostic value of higher ELNs counts across different patient subgroups by age, sex, tumor differentiation, and TNM stages. Subtype analysis based on ELNs count revealed a marked survival benefit in patients treated with adjuvant chemotherapy in the medium and large ELNs counts (≥ 12), whereas those with fewer ELNs showed negligible benefits. RNA sequencing and MIF indicated elevated immune activation in the LN-ELN group, characterized by increased CD3+, CD4+, and CD8 + T cells within the tumor microenvironment. CONCLUSIONS: The number of ELNs independently predicts survival and the immunological landscape at the tumor site in stage III CRC, underscoring its dual prognostic and predictive value.

Increasing Cyetpyrafen Spray Volume and Ozone Spray Improves the Control Effects against Two-Spotted Spider Mite (Tetranychus urticae) in Strawberries.

The two-spotted spider mite (Tetranychus urticae) is a constant threat to greenhouse strawberry production. The application of synthetic acaricides is the main method of controlling T. urticae. However, resistance development to traditional acaricides reduces their efficacy and eventually leads to control failure. It is important for strawberry growers to look for new acaricides and application technologies that can limit the harmfulness of T. urticae in environmentally friendly ways. In the current study, laboratory toxicity tests and field trials were performed to screen high-efficiency acaricides, and then application technologies were improved to enhance the management of T. urticae. In the laboratory toxicity tests, the results showed that the LC50 (median lethal concentration) value of cyetpyrafen, cyenopyrafen, cyflumetofen, bifenazate, abamectin, azocyclotin, pyridaben, spirodiclofen, and etoxazole against adult T. urticae was 0.226, 0.240, 0.415, 3.583, 5.531, 25.58, 39.69, 140.3, and 267.7 mg/L, respectively. In addition, the LC50 value of the nine acaricides against eggs of T. urticae was 0.082, 0.097, 0.931, 18.56, 25.52, 45.61, 36.32, 1.954, and 0.040 mg/L, respectively. The field trial results showed that the best control effect was obtained in cyetpyrafen at 300 mL/ha treatment. Cyetpyrafen was chosen for further application technology tests. In the spray volume tests, the results showed that increasing the spray volume from 900 to 1050 L/ha significantly improved the control of T. urticae. In addition, the results from the spray instrument tests demonstrated that the control effects on T. urticae in the ozone spray treatments were significantly higher than those of the conventional and electrostatic sprays 1 and 3 days after treatment (DAT). Therefore, this study suggested that cyetpyrafen effectively controlled T. urticae both in the laboratory tests and in the field trials. Increasing the spray volume and application of ozone spray significantly improved T. urticae management.

Identification of a hub gene VCL for atherosclerotic plaques and discovery of potential therapeutic targets by molecular docking.

BACKGROUND: Atherosclerosis (AS) is a pathology factor for cardiovascular diseases and instability of atherosclerotic plaques contributes to acute coronary events. This study identified a hub gene VCL for atherosclerotic plaques and discovered its potential therapeutic targets for atherosclerotic plaques. METHODS: Differential expressed genes (DEGs) were screened between unstable and stable plaques from GSE120521 dataset and then used for construction of a protein-protein interactions (PPI) network. Through topological analysis, hub genes were identified within this PPI network, followed by construction of a diagnostic model. GSE41571 dataset was utilized to validate the diagnostic model. A key hub gene was identified and its association with immune characteristics and pathways were further investigated. Molecular docking and molecular dynamics (MD) simulation were employed to discover potential therapeutic targets. RESULTS: According to the PPI network, 3 tightly connected protein clusters were found. Topological analysis identified the top 5 hub genes, Vinculin (VCL), Dystrophin (DMD), Actin alpha 2 (ACTA2), Filamin A (FLNA), and transgelin (TAGLN). Among these hub genes, VCL had the highest diagnostic value. VCL was selected for further analysis and we found that VCL was negatively correlated with immune score and AS-related inflammatory pathways. Next, we identified 408 genes that were highly correlated with VCL and determined potential drug candidates. The results from molecular docking and MD simulation showed compound DB07117 combined with VCL protein stably, the binding energy is -7.7 kcal/mol, indicating that compound DB07117 was a potential inhibitor of VCL protein. CONCLUSION: This study identified VCL as a key gene for atherosclerotic plaques and provides a potential therapeutic target of VCL for the treatment of atherosclerotic plaques.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

From ancient wisdom to modern science: Gut microbiota sheds light on property theory of traditional Chinese medicine.

The property theory of traditional Chinese medicine (TCM) has been practiced for thousands of years, playing a pivotal role in the clinical application of TCM. While advancements in energy metabolism, chemical composition analysis, machine learning, ion current modeling, and supercritical fluid technology have provided valuable insight into how aspects of TCM property theory may be measured, these studies only capture specific aspects of TCM property theory in isolation, overlooking the holistic perspective inherent in TCM. To systematically investigate the modern interpretation of the TCM property theory from multidimensional perspectives, we consulted the Chinese Pharmacopoeia (2020 edition) to compile a list of Chinese materia medica (CMM). Then, using the Latin names of each CMM and gut microbiota as keywords, we searched the PubMed database for relevant research on gut microbiota and CMM. The regulatory patterns of different herbs on gut microbiota were then summarized from the perspectives of the four natures, the five flavors and the meridian tropism. In terms of the four natures, we found that warm-natured medicines promoted the colonization of specific beneficial bacteria, while cold-natured medicines boosted populations of some beneficial bacteria while suppressing pathogenic bacteria. Analysis of the five flavors revealed that sweet-flavored and bitter-flavored CMMs positively influenced beneficial bacteria while inhibiting harmful bacteria. CMMs with different meridian tropism exhibited complex modulative patterns on gut microbiota, with Jueyin (Liver) and Taiyin (Lung) meridian CMMs generally exerting a stronger effect. The gut microbiota may be a biological indicator for characterizing the TCM property theory, which not only enhances our understanding of classic TCM theory but also contributes to its scientific advancement and application in healthcare. Please cite this article as: Yang YN, Zhan JG, Cao Y, Wu CM. From ancient wisdom to modern science: Gut microbiota sheds light on property theory of traditional Chinese medicine. J Integr Med 2024; 22(4): 413-445.

3D Printed All-Natural Hydrogels: Flame-Retardant Materials Toward Attaining Green Sustainability.

Biomass-based hydrogel is a promising flame-retardant material and has a high potential for applications in transportation, aerospace, building and electrical engineering, and electronics. However, rapid vat photopolymerization (VP) 3D printing of biomass-based hydrogels, especially that of all-natural ones, is still rare. Herein, a new class of VP 3D-printed hydrogels with strong covalent networks, fabricating using fully biomass materials and a commercial liquid crystal display (LCD) printer assembled with low-intensity visible light is presented. Encouragingly, the highly ordered layer-by-layer packing structures provided by VP 3D printing technology endow these hydrogels with remarkable flame retardancy, exceptional temperature resistance, advantageous combustion behaviors, and favorable mechanical strength, in particular, giving them a better limit oxygen index (83.5%) than various biomass-based hydrogels. The proposed approach enables the green design as well as the precise and efficient preparation for flame-retardant materials, paving the way for the future flame-retardant materials toward attaining green sustainability.

[Whole Exome Sequencing Reveals Gene Mutation Characteristics of Primary Central Nervous System Lymphoma].

OBJECTIVE: To investigate gene mutation characteristics of primary central nervous system lymphoma (PCNSL) through whole exome sequencing (WES) to 18 patients with PCNSL. METHODS: Tumor tissues from 18 patients with diffuse large B-cell lymphoma who were diagnosed with PCNSL in Department of Hematology, Lanzhou University Second Hospital from September 2018 to December 2020 and had normal immune function, no history of HIV or immunosuppressant therapy were collected. High-throughput-based WES was performed on the tumor tissues, with an average sequencing depth of >100×. After data processing and bioinformatics analysis of sequencing results, the mutation maps and mutation characteristics of 18 PCNSL patients were obtained. RESULTS: Obvious somatic mutations were detected in all 18 patients. The median number of somatic mutations was 321. Missense mutations were most prominent (accounting for about 90%), and the mutation type was dominated by C>T (50.2%), reflecting the age-related mutation pattern. Among the top 15 frequently mutated genes, PSD3, DUSP5, MAGEB16, TELO2, FMO2, TRMT13, AOC1, PIGZ, SVEP1, IP6K3, and TIAM1 were the driver genes. The enrichment results of driver gene pathways showed that RTK-RAS, Wnt, NOTCH, Hippo and Cell-Cycle pathways were significantly enriched. The tumor mutation burden was between 3.558 48/Mb and 8.780 89/Mb, and the average was 4.953 32/Mb, which was significantly higher than other cancer research cohorts in the TCGA database. CONCLUSIONS: PCNSL occurs somatic missense mutations frequently, mainly point mutations, and the mutation type is mainly C>T. The driver genes are mainly involved in RTK-RAS, Wnt, NOTCH and Hippo pathways, indicating that the above pathways may be related to the pathogenesis of PCNSL. PCNSL has a significantly high tumor mutation burden, which may explain the efficacy of PD-1 inhibitors in PCNSL.

Prognostic value of right atrial strains in arrhythmogenic right ventricular cardiomyopathy.

OBJECTIVES: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive fibrofatty infiltration of atrial and ventricular myocardium resulting in adverse cardiac events. Atrial function has been increasingly recognized as prognostically important for cardiovascular disease. As the right atrial (RA) strain is a sensitive parameter to describe RA function, we aimed to analyze the prognostic value of the RA strain in ARVC. METHODS: RA strain parameters were derived from cardiac magnetic resonance (CMR) images of 105 participants with definite ARVC. The endpoint was defined as a combination of sudden cardiac death, survival cardiac arrest, and appropriate implantable cardioverter-defibrillator intervention. Cox regression and Kaplan-Meier survival analyses were performed to evaluate the association between RA strain parameters and endpoint. Concordance index (C index), net reclassification index (NRI), and integrated discrimination improvement (IDI) were calculated to assess the incremental value of RA strain in predicting the endpoint. RESULTS: After a median follow-up of 5 years, 36 (34.3%) reaching the endpoint displayed significantly reduced RA strain parameters. At Kaplan-Meier analysis, impaired RA reservoir (RARS) and booster strains (RABS) were associated with an increased risk of the endpoint. After adjusting for conventional risk factors, RARS (hazard ratio [HR], 0.956; p = 0.005) and RABS (HR, 0.906; p = 0.002) resulted as independent predictors for endpoint at Cox regression analyses. In addition, RARS and RABS improved prognostic value to clinical risk factors and CMR morphological and functional predictors (all p < 0.05). CONCLUSION: RARS and RABS were independent predictors for adverse cardiac events, which could provide incremental prognostic value for conventional predictors in ARVC. CRITICAL RELEVANCE STATEMENT: We evaluated the prognostic value of right atrial strain in ARVC patients and suggested cardiologists consider RA strain as a predictive parameter when evaluating the long-term outcome of ARVC patients in order to formulate better clinical therapy. KEY POINTS: • Patients with ARVC had significantly reduced RA strain and strain rates compared with healthy participants. • Participants with lower RA reservoir and booster stains were associated with a significantly higher risk of adverse cardiac events. • RA booster and reservoir strain provide incremental value to conventional parameters.

The tRNA thiolation-mediated translational control is essential for plant immunity.

Plants have evolved sophisticated mechanisms to regulate gene expression to activate immune responses against pathogen infections. However, how the translation system contributes to plant immunity is largely unknown. The evolutionarily conserved thiolation modification of transfer RNA (tRNA) ensures efficient decoding during translation. Here, we show that tRNA thiolation is required for plant immunity in Arabidopsis. We identify a cgb mutant that is hyper-susceptible to the pathogen Pseudomonas syringae. CGB encodes ROL5, a homolog of yeast NCS6 required for tRNA thiolation. ROL5 physically interacts with CTU2, a homolog of yeast NCS2. Mutations in either ROL5 or CTU2 result in loss of tRNA thiolation. Further analyses reveal that both transcriptome and proteome reprogramming during immune responses are compromised in cgb. Notably, the translation of salicylic acid receptor NPR1 is reduced in cgb, resulting in compromised salicylic acid signaling. Our study not only reveals a regulatory mechanism for plant immunity but also uncovers an additional biological function of tRNA thiolation.

[Clinical Features and Prognostic of Patients with Primary Central Nervous System Lymphoma].

OBJECTIVE: To explore the clinical features and prognosis of patients with primary central nervous system lymphoma（PCNSL）. METHODS: A retrospective analysis was performed on the relationship between clinical features, treatment regimen and prognosis in 46 newly diagnosed patients with primary central nervous system lymphoma who were diagnosed and treated in The Second Hospital of Lanzhou University from January 2015 to September 2022. Fisher's exact probability method was used to analyze the differences in clinical data of different subgroups. Kaplan-Meier survival curve was used to analyze the overall survival rate and progression-free survival rate of patients with different treatments, and the factors influencing survival were analyzed. RESULTS: Among 46 patients with PCNSL, which pathological type were diffuse large B-cell lymphoma（DLBCL）. There were 26(56.5%) cases of male and 20(43.5%) of female, with a median age of 54(17-71) years. In Hans subtypes, 14 cases (30.4%) of GCB subtype, 32 cases (69.6%) of non-GCB subtype. 32 cases (69.6%) of Ki-67≥80%. Among 36 patients who completed at least 2 cycles of treatment with follow-up data, the efficacy evaluation was as follows: overall response rate(ORR) was 63.9%, complete response(CR) rate was 47.2%, 17 cases of CR, 6 cases of PR. The 1-year progression-free survival rate and 1-year overall survival rate was 73.6% and 84.9%, respectively. The 2-year progression-free survival rate and 2-year overall survival rate was 52.2% and 68.9%, respectively. The ORR and CR rate of 17 patients treated with RMT regimen was 76.5% and 52.9% (9 cases CR and 4 cases PR), respectively. Univariate analysis of 3 groups of patients treated with RMT regimen, RM-BTKi regimen, and RM-TT regimen as first-line treament showed that deep brain infiltration was associated with adverse PFS(P =0.032), and treatment regimen was associated with adverse OS in PCNSL patients（P =0.025）. CONCLUSION: Different treatment modalities were independent prognosis predictors for OS, the deep brain infiltration of PCNSL is a poor predictive factor for PFS. Patients with relapse/refractory (R/R) PCNSL have a longer overall survival time because to the novel medication BTKi. They have strong toleration and therapeutic potential as a first-line therapy for high-risk patients.

omicsMIC: a comprehensive benchmarking platform for robust comparison of imputation methods in mass spectrometry-based omics data.

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in mass spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometry-based omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. omicsMIC is freely available at https://github.com/WQLin8/omicsMIC.