Multi-scale variational autoencoder for imputation of missing values in untargeted metabolomics using whole-genome sequencing data.

BACKGROUND: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in metabolomics studies. METHOD: In this study, we propose a novel method that leverages the information from WGS data and reference metabolites to impute unknown metabolites. Our approach utilizes a multi-scale variational autoencoder to jointly model the burden score, polygenetic risk score (PGS), and linkage disequilibrium (LD) pruned single nucleotide polymorphisms (SNPs) for feature extraction and missing metabolomics data imputation. By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information. RESULTS: We evaluate the performance of our method on empirical metabolomics datasets with missing values and demonstrate its superiority compared to conventional imputation techniques. Using 35 template metabolites derived burden scores, PGS and LD-pruned SNPs, the proposed methods achieved R2-scores > 0.01 for 71.55 % of metabolites. CONCLUSION: The integration of WGS data in metabolomics imputation not only improves data completeness but also enhances downstream analyses, paving the way for more comprehensive and accurate investigations of metabolic pathways and disease associations. Our findings offer valuable insights into the potential benefits of utilizing WGS data for metabolomics data imputation and underscore the importance of leveraging multi-modal data integration in precision medicine research.

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.

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.

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; Epub ahead of print.

Dion-Jacobson-Phase 2D Sn-Based Perovskite Comprising a High Dipole Moment of π-Conjugated Short-Chain Organic Spacers for High-Performance Solar Cell Applications.

The stability issue of Sn-based perovskite solar cells (PSCs) is expected to be resolved by involving a two-dimensional (2D) layered structure. However, Sn-based 2D PSCs, especially Dion-Jacobson (DJ)-phase ones with potentially good stability, have rarely been reported. Herein, superior DJ-phase Sn 2D perovskites with 3-aminobenzylamine (3ABA2+) or 4-aminobenzylamine (4ABA2+) π-conjugated short-chain ligands are reported to fabricate efficient 2D lead-free PSCs. Notably, the high dipole moment of the 3ABAI2 organic spacer is approved to possess faster charge transfer for forming (3ABA)FA4Sn5I16 2D perovskite with an extremely low exciton binding energy (only 84 meV). In combination with a diacetate partial substitution and methylamine iodide/bromide (MAI/MABr) post-treatment strategy to delay crystallization and improve compactness and coverage of the perovskite film, a record power conversion efficiency (PCE) of 6.81% and stability of 840 h (less than 5% degradation in a N2 atmosphere for unencapsulated devices) are acquired in eventual (3ABA)FA4Sn5I16 2D PSCs, which are among the highest PCE and the longest stability of Sn-based 2D PSCs reported to date. Our work provides a prospective molecule design and film preparation strategy of 2D Sn perovskites toward nontoxic high-performance tin-based PSCs, which pushes the almost stagnant research forward.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus.

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Fractal analysis of left ventricular trabeculae in heart failure with preserved ejection fraction patients with multivessel coronary artery disease.

OBJECTIVES: Endocardial trabeculae undergo varicose changes and hyperplasia in response to hemodynamic influences and are a variable phenotype reflecting changes in disease. Fractal analysis has been used to analyze the complexity of endocardial trabeculae in a variety of cardiomyopathies. The aim of this paper was to quantify the myocardial trabecular complexity through fractal analysis and to investigate its predictive value for the diagnosis of heart failure with preserved ejection fraction (HFpEF) in patients with multivessel coronary artery disease (CAD). METHODS: The retrospective study population consisted of 97 patients with multivessel CAD, 39 of them were diagnosed with HFpEF, while 46 healthy volunteers were recruited as controls. Fractal dimension (FD) was obtained through fractal analysis of endocardial trabeculae on LV short-axis cine images. Logistic regression analyses were used to confirm the predictors and compare different prediction models. RESULTS: Mean basal FD was significantly higher in patients with HFpEF than in patients without HFpEF or in the healthy group (median: 1.289; IQR: 0.078; p < 0.05). Mean basal FD was also a significant independent predictor in univariate and multivariate logistic regression (OR: 1.107 and 1.043, p < 0.05). Furthermore, adding FD to the prediction model improved the calibration and accuracy of the model (c-index: 0.806). CONCLUSION: The left ventricular FD obtained with fractal analysis can reflect the complexity of myocardial trabeculae and has an independent predictive value for the diagnosis of HFpEF in patients with multivessel CAD. Including FD into the diagnostic model can help improve the diagnosis. CRITICAL RELEVANCE STATEMENT: Differences show in the complexity of endocardial trabeculae in multivessel coronary artery disease patients, and obtaining fractal dimensions (FD) by fractal analysis can help identify heart failure with preserved ejection fraction (HFpEF) patients. KEY POINTS: The complexity of myocardial trabeculae differs among patients with multivessel coronary artery disease. Left ventricular fractal dimensions can reflect the complexity of the myocardial trabecular. Fractal dimensions have predictive value for the diagnosis of heart failure with preserved ejection fraction.

Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention.

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.

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.

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.

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.

[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.

[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.

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.

Oral bacteriome and mycobiome of patients with idiopathic membranous nephropathy with different tongue coatings treated with a Chinese herbal formula.

ETHNOPHARMACOLOGICAL RELEVANCE: Moshen Fuyuan Formula (MSFY) is one of the representative Chinese medicine compound for Idiopathic membranous nephropathy (IMN), that originate from Fang Ji Huang Qi decoction in the Han dynasty. IMN is usually accompanied by different tongue coatings in traditional Chinese medicine (TCM), and tongue microorganisms are important factors affecting the formation of the tongue coating. Recently, oral microbiomes, including bacteria and fungi, have been identified as pivotal factors that contribute to disease development. However, the regulation of oral microbiomes by MSFY has not been defined. AIM OF THE STUDY: In this work, we explore the characteristics of oral bacteria and fungi in IMN patients with different tongue coatings, and clarify the therapeutic effect of MSFY based on oral microbiome. MATERIALS AND METHODS: We enrolled 24 patients with IMN, including 11 with white tongue (IMN-W) and 13 with yellow tongue (IMN-Y), and recruited an additional 10 healthy individuals. Patients with IMN were treated with the MSFY. The oral bacteriome and fungi before and after treatment were detected using full-length 16S rRNA and internal transcribed spacer gene sequencing. RESULTS: The therapeutic effect of MSFY on patients with yellow tongue coating was more significant than that on patients with white tongue coating. In terms of oral bacteriome, Campylobacter bacteria were enriched in patients with yellow tongue and could be a promising biomarker for yellow coating. Enrichment of Veillonella parvula_A may partially account for the therapeutic effect of MSFY. As for oral fungi, Malassezia globosa was enhanced in patients with IMN-W and reduced in patients with IMN-Y. Notably, it was reduced by MSFY. We also found that mycobiome-bacteriome interactions were highly complex and dynamic in patients with IMN. CONCLUSION: The regulation of the dynamic balance between oral fungi and bacteria by MSFY contributes to the treatment of IMN. This study determined the oral bacteriome and mycobiome of patients with IMN with different tongue coatings before and after MSFY treatment, which aids in promoting personalized treatment in clinical TCM and provides direction for investigating the mechanism of Chinese herbal medicines.

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.