Quantitative susceptibility mapping based basal ganglia segmentation via AGSeg: leveraging active gradient guiding mechanism in deep learning.

Background: With better visual contrast and the ability for magnetic susceptibility quantification analysis, quantitative susceptibility mapping (QSM) has emerged as an important magnetic resonance imaging (MRI) method for basal ganglia studies. Precise segmentation of basal ganglia is a prerequisite for quantification analysis of tissue magnetic susceptibility, which is crucial for subsequent disease diagnosis and surgical planning. The conventional method of localizing and segmenting basal ganglia heavily relies on layer-by-layer manual annotation by experts, resulting in a tedious amount of workload. Although several morphology registration and deep learning based methods have been developed to automate segmentation, the voxels around the nuclei boundary remain a challenge to distinguish due to insufficient tissue contrast. This paper proposes AGSeg, an active gradient guidance-based susceptibility and magnitude information complete (MIC) network for real-time and accurate basal ganglia segmentation. Methods: Various datasets, including clinical scans and data from healthy volunteers, were collected across multiple centers with different magnetic field strengths (3T/5T/7T), with a total of 210 three-dimensional (3D) susceptibility measurements. Manual segmentations following fixed rules for anatomical borders annotated by experts were used as ground truth labels. The proposed network took QSM maps and Magnitude images as two individual inputs, of which the features are selectively enhanced in the proposed magnitude information complete (MIC) module. AGSeg utilized a dual-branch architecture, with Seg-branch aiming to generate a proper segmentation map and Grad-branch to reconstruct the gradient map of regions of interest (ROIs). With the support of the newly designed active gradient module (AGM) and gradient guiding module (GGM), the Grad-branch provided attention guidance for the Seg-branch, facilitating it to focus on the boundary of target nuclei. Results: Ablation studies were conducted to assess the functionality of the proposed modules. Significant performance decrement was observed after ablating relative modules. AGSeg was evaluated against several existing methods on both healthy and clinical data, achieving an average Dice similarity coefficient (DSC) =0.874 and average 95% Hausdorff distance (HD95) =2.009. Comparison experiments indicated that our model had superior performance on basal ganglia segmentation and better generalization ability over existing methods. The AGSeg outperformed all implemented comparison deep learning algorithms with average DSC enhancement ranging from 0.036 to 0.074. Conclusions: The current work integrates a deep learning-based method into automated basal ganglia segmentation. The high processing speed and segmentation robustness of AGSeg contribute to the feasibility of future surgery planning and intraoperative navigation. Experiments show that leveraging active gradient guidance mechanisms and magnitude information completion can facilitate the segmentation process. Moreover, this approach also offers a portable solution for other multi-modality medical image segmentation tasks.

Relationship between weight-adjusted-waist index and blood pressure as well as incident hypertension among middle-aged and elderly Chinese: A longitudinal study.

BACKGROUND AND AIM: The Weight-Adjusted Waist Index (WWI) is a novel obesity metric linked to metabolic disorders. Its relationship with blood pressure and hypertension prevalence in middle-aged and elderly Chinese is unclear. This study examined the association between WWI, blood pressure, and hypertension incidence. METHODS AND RESULTS: This cross-sectional study included 9298 participants from the China Health and Retirement Longitudinal Study, with 4120 non-hypertensive individuals enrolled in the cohort study. In the cross-sectional analysis, WWI was positively associated with systolic blood pressure (SBP) (Beta 0.88, 95% CI: 0.57-1.21, p < 0.001), showing stronger correlations than waist circumference (WC) (Beta 0.20, 95% CI: 0.16-0.23, p < 0.001) and body mass index (BMI) (Beta 0.63, 95% CI: 0.52-0.74, p < 0.001). WWI also showed a positive association with diastolic blood pressure (DBP) (Beta 0.51, 95% CI: 0.32-0.69, p < 0.001), stronger than those with WC (Beta 0.13, 95% CI: 0.11-0.15, p < 0.001) and BMI (Beta 0.43, 95% CI: 0.37-0.50, p < 0.001). In the longitudinal cohort study, there were 1325 (32%) incident cases of hypertension by the end of follow-up. WWI was positively associated with incident hypertension (OR 1.11, 95% CI: 1.04-1.18, p = 0.001), with a stronger predictive value than WC (OR 1.02, 95% CI: 1.01-1.03, p < 0.001) and BMI (OR 1.04, 95% CI: 1.02-1.06, p < 0.001). CONCLUSION: Elevated WWI may serve as an independent risk factor for incident hypertension in the middle-aged and elderly Chinese population.

Bibliometric analysis of global research on air pollution and cardiovascular diseases: 2012-2022.

Background: The relationship between air pollution and cardiovascular diseases (CVDs) has garnered significant interest among researchers globally. This study employed bibliometric analysis to provide an overview of current research on the association between air pollution and CVDs, offering a comprehensive analysis of global research trends in this area. Methods: An exhaustive scrutiny of literature pertaining to the nexus between air pollution and CVDs from 2012 to 2022 was conducted through rigorous screening of the Web of Science Core Collection (WoSCC). Publications were exclusively considered in English. Subsequently, sophisticated analytical tools including CiteSpace 6.2.4R, Vosviewer 1.6.19, HistCite 2.1, Python 3.7.5, Microsoft Charticulator, and Bibliometrix Online Analysis Platform were deployed to delineate research trends in this domain. Results: The analysis of the dataset, comprising 1710 documents, unveiled a consistent escalation in scientific publications, peaking in 2022 with a total of 248 publications. Moreover, Environmental Science and Toxicology stood out as the predominant categories. Examination of keyword frequency highlighted the terms 'air pollution', 'cardiovascular disease', and 'particulate matter' as the most prevalent. Notably, the most prolific entities, in terms of authors, journals, organizations, and countries, were identified as Robert D. Brook, Environmental Health Perspectives, Harvard University, and the United States, respectively. Conclusion: The findings presented a notable increase in high-quality publications on this topic over the past 11 years, suggesting a positive outlook for future research. The study concluded with an examination of three key themes in research trends related to air pollution and CVDs: the initial physiological response to pollutant exposure, the pathways through which pollutants are transmitted, and the subsequent effects on target organs. Additionally, various air pollutants, such as particulate matter, nitric dioxide, and ozone, could contribute to multiple CVDs, including coronary heart disease, hypertension, and heart failure. Although some hypotheses have been put forward, the mechanisms of air pollution-related CVDs still need to be explored in the future.

Multidrug-resistant aeromonas caviae causing cystitis in a renal failure patient.

A 49-year-old female with multiple myeloma complicated by renal failure had dysuria. The urine culture revealed multidrug-resistant aeromonas caviae during her hospital stay. Her symptoms and signs significantly improved after receiving a seven-day course of piperacillin-tazobactam treatment. She had no history of urinary tract infections(UTIs). On follow-up, she felt clinically well. Aeromonas caviae is a rare cause of UTI. We review previous cases of aeromonas caviae UTIs. The purpose of this case report is to assist in the diagnosis and management of aeromonas caviae cystitis.

Lung tumor discrimination by deep neural network model CanDo via DNA methylation in bronchial lavage.

Bronchoscopic-assisted discrimination of lung tumors presents challenges, especially in cases with contraindications or inaccessible lesions. Through meta-analysis and validation using the HumanMethylation450 database, this study identified methylation markers for molecular discrimination in lung tumors and designed a sequencing panel. DNA samples from 118 bronchial washing fluid (BWF) specimens underwent enrichment via multiplex PCR before targeted methylation sequencing. The Recursive Feature Elimination Cross-Validation and deep neural network algorithm established the CanDo classification model, which incorporated 11 methylation features (including 8 specific to the TBR1 gene), demonstrating a sensitivity of 98.6% and specificity of 97.8%. In contrast, bronchoscopic rapid on-site evaluation (bronchoscopic-ROSE) had lower sensitivity (87.7%) and specificity (80%). Further validation in 33 individuals confirmed CanDo's discriminatory potential, particularly in challenging cases for bronchoscopic-ROSE due to pathological complexity. CanDo serves as a valuable complement to bronchoscopy for the discriminatory diagnosis and stratified management of lung tumors utilizing BWF specimens.

Compact In Situ Electrochemical NMR with Wireless and Anti-interference Strategy in Multiscenario Applications.

The integration of electrochemistry with nuclear magnetic resonance (NMR) spectroscopy recently offers a powerful approach to understanding oxidative metabolism, detecting reactive intermediates, and predicting biological activities. This combination is particularly effective as electrochemical methods provide excellent mimics of metabolic processes, while NMR spectroscopy offers precise chemical analysis. NMR is already widely utilized in the quality control of pharmaceuticals, foods, and additives and in metabolomic studies. However, the introduction of additional and external connections into the magnet has posed challenges, leading to signal deterioration and limitations in routine measurements. Herein, we report an anti-interference compact in situ electrochemical NMR system (AICISENS). Through a wireless strategy, the compact design allows for the independent and stable operation of electrochemical NMR components with effective interference isolation. Thus, it opens an avenue toward easy integration into in situ platforms, applicable not only to laboratory settings but also to fieldwork. The operability, reliability, and versatility were validated with a series of biomimetic assessments, including measurements of microbial electrochemical systems, functional foods, and simulated drug metabolisms. The robust performance of AICISENS demonstrates its high potential as a powerful analytical tool across diverse applications.

Differential Mechanisms of Microbial As(III) and Sb(III) Oxidation and Their Contribution to Tailings Reclamation.

Mine tailings are extremely oligotrophic environments frequently contaminated with elevated As and Sb, making As(III) and Sb(III) oxidation potentially important energy sources for the tailing microbiome. Although they have been proposed to share similar metabolic pathways, a systemic comparison of the As(III) and Sb(III) oxidation mechanisms and energy utilization efficiencies requires further elucidation. In this study, we employed a combination of physicochemical, molecular, and bioinformatic analyses to compare the kinetic and genetic mechanisms of As(III) and Sb(III) oxidation as well as their respective energy efficiencies for fueling the key nutrient acquisition metabolisms. Thiobacillus and Rhizobium spp. were identified as functional populations for both As(III) and Sb(III) oxidation in mine tailings by DNA-stable isotope probing. However, these microorganisms mediated As(III) and Sb(III) oxidation via different metabolic pathways, resulting in preferential oxidation of Sb(III) over As(III). Notably, both As(III) and Sb(III) oxidation can facilitate nitrogen fixation and phosphate solubilization in mine tailings, with Sb(III) oxidation being more efficient in powering these processes. Thus, this study provided novel insights into the microbial As(III) and Sb(III) oxidation mechanisms and their respective nutrient acquisition efficiencies, which may be critical for the reclamation of mine tailings.

Discovery of a novel BTK inhibitor S-016 and identification of a new strategy for the treatment of lymphomas including BTK inhibitor-resistant lymphomas.

Bruton's tyrosine kinase (BTK) has emerged as a therapeutic target for B-cell malignancies, which is substantiated by the efficacy of various irreversible or reversible BTK inhibitors. However, on-target BTK mutations facilitating evasion from BTK inhibition lead to resistance that limits the therapeutic efficacy of BTK inhibitors. In this study we employed structure-based drug design strategies based on established BTK inhibitors and yielded a series of BTK targeting compounds. Among them, compound S-016 bearing a unique tricyclic structure exhibited potent BTK kinase inhibitory activity with an IC50 value of 0.5 nM, comparable to a commercially available BTK inhibitor ibrutinib (IC50 = 0.4 nM). S-016, as a novel irreversible BTK inhibitor, displayed superior kinase selectivity compared to ibrutinib and significant therapeutic effects against B-cell lymphoma both in vitro and in vivo. Furthermore, we generated BTK inhibitor-resistant lymphoma cells harboring BTK C481F or A428D to explore strategies for overcoming resistance. Co-culture of these DLBCL cells with M0 macrophages led to the polarization of M0 macrophages toward the M2 phenotype, a process known to support tumor progression. Intriguingly, we demonstrated that SYHA1813, a compound targeting both VEGFR and CSF1R, effectively reshaped the tumor microenvironment (TME) and significantly overcame the acquired resistance to BTK inhibitors in both BTK-mutated and wild-type BTK DLBCL models by inhibiting angiogenesis and modulating macrophage polarization. Overall, this study not only promotes the development of new BTK inhibitors but also offers innovative treatment strategies for B-cell lymphomas, including those with BTK mutations.

Association between hypertension and osteoporosis: a population-based cross-sectional study.

BACKGROUND: Current evidence suggests that metabolic dysregulation is inextricably linked to both hypertension and osteoporosis, but the correlation between hypertension and osteoporosis is still unclear. Therefore, in this study, we explored the correlation between hypertension and osteoporosis. METHODS: A total of 37,807 participants from the National Health and Nutrition Examination Survey (1999-2010, 2013-2014, 2017-2018) were enrolled in this population-based cross-sectional study. Hypertension was considered an exposure factor and osteoporosis was considered an outcome factor. Logistic regression and subgroup analysis were used to assess the association between hypertension and osteoporosis. RESULTS: A total of 2,523 participants, with a mean age of 68.65 ± 12.21 years, suffered from osteoporosis, and 86.2% were female. Participants with osteoporosis had a greater prevalence of hypertension than participants without osteoporosis (p < 0.001). Participants with hypertension also had a greater prevalence of osteoporosis than participants without hypertension (p < 0.001). Univariate logistic regression analysis indicated that hypertension was associated with osteoporosis (OR: 2.693, 95% CI: 2.480-2.924, p < 0.001). Multivariate logistic regression analysis with a fully adjusted model indicated that hypertension was strongly associated with osteoporosis (OR: 1.183, 95% CI: 1.055-1.327, p = 0.004). Subgroup analysis revealed that the associations between hypertension and osteoporosis were significant in the younger than 60 years, male sex, diabetes subgroup and hypercholesterolemia subgroup (p < 0.05). CONCLUSION: Hypertension was independently associated with osteoporosis in the general population.

A Comprehensive Prognostic Model for Colon Adenocarcinoma Depending on Nuclear-Mitochondrial-Related Genes.

Background: Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. Methods: COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. Results: A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including LARS2, PARS2, ETHE1, LRPPRC, TMEM70, AARS2, ACAD9, VARS2, and ATP8A2. The high-RS group had more inflamed immune features, including T and CD4+ memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. Conclusion: This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.

Treatment of phenolic wastewater in an anaerobic fluidized bed microbial fuel cell filled with graphene oxide-macroporous adsorption resin as multifunctional carrier.

A novel graphene oxide-modified resin (graphene oxide-macroporous adsorption resin) was prepared and used as a multifunctional carrier in an anaerobic fluidized bed microbial fuel cell (AFB-MFC) to treat phenolic wastewater (PW). The macroporous adsorption resin (MAR) was used as the carrier, graphene oxide was used as the modified material, the conductive modified resin was prepared by loading graphene oxide (GO) on the resin through chemical reduction. The modified resin particles were characterized by scanning electron microscopy (SEM), Raman spectroscopy (RS), specific surface area and pore structure analysis. Graphene oxide-macroporous adsorption resin special model was established using the Amorphous Cell module in Materials Studio (MS), and the formation mechanism of graphene oxide-macroporous adsorption resin was studied using mean square displacement (MSD) of the force module. Molecular dynamics simulation was used to study the motion law of molecular and atomic dynamics at the interface of graphene oxide-macroporous adsorption resin composites. The strong covalent bond between GO and MAR ensures the stability of GO/MAR. When the modified resin prepared in 3.0 mg/mL GO mixture was used in the AFB-MFC, the COD removal of wastewater was increased by 9.1% to 72.44%, the voltage was increased by 84.04% to 405.8 mV, and power density was increased by 765.44% to 242.67 mW/m2.

Classification of multiple primary lung cancer in patients with multifocal lung cancer: assessment of a machine learning approach using multidimensional genomic data.

Background: Multiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment. Methods: A total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors. Results: We found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p <.01). Conclusion: These data provide novel evidence of MPLC-specific genomic characteristics and demonstrate that our one-step molecular classifier can accurately classify multifocal lung tumors as MPLC or IM, which suggested that broad panel NGS may be a useful tool for assisting with differential diagnoses.

Pure-Shift-Based Proton Magnetic Resonance Spectroscopy for High-Resolution Studies of Biological Samples.

Proton magnetic resonance spectroscopy (1H MRS) presents a powerful tool for revealing molecular-level metabolite information, complementary to the anatomical insight delivered by magnetic resonance imaging (MRI), thus playing a significant role in in vivo/in vitro biological studies. However, its further applications are generally confined by spectral congestion caused by numerous biological metabolites contained within the limited proton frequency range. Herein, we propose a pure-shift-based 1H localized MRS method as a proof of concept for high-resolution studies of biological samples. Benefitting from the spectral simplification from multiplets to singlet peaks, this method addresses the challenge of spectral congestion encountered in conventional MRS experiments and facilitates metabolite analysis from crowded NMR resonances. The performance of the proposed pure-shift 1H MRS method is demonstrated on different kinds of samples, including brain metabolite phantom and in vitro biological samples of intact pig brain tissue and grape tissue, using a 7.0 T animal MRI scanner. This proposed MRS method is readily implemented in common commercial NMR/MRI instruments because of its generally adopted pulse-sequence modules. Therefore, this study takes a meaningful step for MRS studies toward potential applications in metabolite analysis and disease diagnosis.

Gender differences in the association between changes in the atherogenic index of plasma and cardiometabolic diseases: a cohort study.

OBJECTIVE: The relationship between changes in Atherogenic Index of Plasma (AIP) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aims to explore the association between changes in AIP and CMD. METHODS: This study included 3,791 individuals aged over 45 years from CHARLS. Participants were divided into four groups using the K-Means clustering method. Cumulative AIP was used as a quantitative indicator reflecting changes in AIP. Differences in baseline data and CMD incidence rates among these four groups were compared. Multifactorial logistic regression models were used to assess the relationship between changes in AIP and CMD, and subgroup analysis and interaction tests were conducted to evaluate potential relationships between changes in AIP and CMD across different subgroups. Restricted cubic splines (RCS) were used to assess the dose-response relationship between cumulative AIP and CMD. RESULTS: Changes in AIP were independently and positively associated with CMD. In males, the risk significantly increased in class4 compared to class1 (OR 1.75, 95%CI 1.12-2.73). In females, changes in AIP were not significantly associated with CMD. Cumulative AIP was positively correlated with CMD (OR 1.15, 95%CI 1.01-1.30), with significant gender differences in males (OR 1.29, 95%CI 1.07-1.55) and females (OR 1.03, 95%CI 0.87-1.23) (p for interaction = 0.042). In addition, a linear relationship was observed between cumulative AIP and CMD in male. CONCLUSION: Substantial changes in AIP may increase the risk of CMD in middle-aged and elderly Chinese males. Dynamic monitoring of AIP is of significant importance for the prevention and treatment of CMD.

A Novel IRAK4 Inhibitor DW18134 Ameliorates Peritonitis and Inflammatory Bowel Disease.

IRAK4 is a critical mediator in NF-κB-regulated inflammatory signaling and has emerged as a promising therapeutic target for the treatment of autoimmune diseases; however, none of its inhibitors have received FDA approval. In this study, we identified a novel small-molecule IRAK4 kinase inhibitor, DW18134, with an IC50 value of 11.2 nM. DW18134 dose-dependently inhibited the phosphorylation of IRAK4 and IKK in primary peritoneal macrophages and RAW264.7 cells, inhibiting the secretion of TNF-α and IL-6 in both cell lines. The in vivo study demonstrated the efficacy of DW18134, significantly attenuating behavioral scores in an LPS-induced peritonitis model. Mechanistically, DW18134 reduced serum TNF-α and IL-6 levels and attenuated inflammatory tissue injury. By directly blocking IRAK4 activation, DW18134 diminished liver macrophage infiltration and the expression of related inflammatory cytokines in peritonitis mice. Additionally, in the DSS-induced colitis model, DW18134 significantly reduced the disease activity index (DAI) and normalized food and water intake and body weight. Furthermore, DW18134 restored intestinal damage and reduced inflammatory cytokine expression in mice by blocking the IRAK4 signaling pathway. Notably, DW18134 protected DSS-threatened intestinal barrier function by upregulating tight junction gene expression. In conclusion, our findings reported a novel IRAK4 inhibitor, DW18134, as a promising candidate for treating inflammatory diseases, including peritonitis and IBD.

Efficacy and safety of fractional micro-needling radiofrequency for the treatment of enlarged pores on the cheeks of a chinese cohort: a retrospective study.

To explore the efficacy and safety of fractional micro-needling radiofrequency (FMRF) in the treatment of enlarged pores on the cheek in a Chinese cohort. Patients with enlarged facial pores who underwent FMRF between January 2020 and December 2022 were included in this study. Blinded clinical assessments were performed by two independent dermatologists using a six-grade photographic enlarged pore scale and a quartile grading scale. Patients were asked to rate the degree of pain related to treatment on a visual analog scale (VAS), with scores ranging from 0 (no pain) to 10 (worst pain ever). A paired t-test was used to analyze the six-grade photographic enlarged pore scores. A total of 22 patients received three consecutive sessions of FMRF treatment, with intervals of 1-3 months, and underwent follow-up as scheduled. The mean six-grade photographic enlarged score was 3.55 ± 0.96 at baseline, while the score decreased significantly to 2.59 ± 0.59 after three treatment sessions (P < 0.05). The improvement score of the patients, assessed by two independent dermatologists, was 2.31 ± 0.71, according to the quartile grading scale. The mean VAS score was 6.42 ± 1.44. FMRF is effective and safe for the treatment of enlarged facial pores after three sessions.

Causal relationship of genetically predicted particulate matter 2.5 level with Alzheimer's disease and the mediating effect of dehydroepiandrosterone sulphate.

BACKGROUND: The causal association between particulate matter 2.5 (PM2.5) and Alzheimer's disease (AD) remains inconclusive, and the mediators of the association have yet to be explored. AIMS: We aimed to assess the potential causal relationship between PM2.5 and AD, and to investigate the mediating role of dehydroepiandrosterone sulphate (DHEAS). SUBJECTS AND METHODS: We implemented a two-sample Mendelian randomisation (MR) study to examine the genetic predisposition to PM2.5 exposure and its association with AD. The inverse-variance weighted (IVW) method served as the primary analytical tool to estimate the odds ratio (OR) and 95% confidence interval (95% CI). RESULTS: There were 6 and 4 genetic variants associated with DHEAS and PM2.5, respectively. Based on the multivariable MR analysis, we found that after adjusting for DHEAS, each standard deviation increase in PM2.5 was associated with the risk of AD (OR: 2.96, 95% CI: 1.33, 6.58, p = 0.00769). The MR Egger intercept test did not detect horizontal pleiotropy for PM2.5 (P-pleiotropy = 0.879) and DHEAS(P-pleiotropy = 0.941). According to the results of the mediation analysis, DHEAS accounted for 18.3% of the association between PM2.5 and AD. CONCLUSION: Our findings affirm a significant causal association between PM2.5 exposure and AD, with DHEAS playing a mediating role in this relationship.

SCPL acyltransferases catalyze the metabolism of chlorogenic acid during purple coneflower seed germination.

The metabolism of massively accumulated chlorogenic acid is crucial for the successful germination of purple coneflower (Echinacea purpurea (L.) Menoch). A serine carboxypeptidase-like (SCPL) acyltransferase (chicoric acid synthase, CAS) utilizes chlorogenic acid to produce chicoric acid during germination. However, it seems that the generation of chicoric acid lags behind the decrease in chlorogenic acid, suggesting an earlier route of chlorogenic acid metabolism. We discovered another chlorogenic acid metabolic product, 3,5-dicaffeoylquinic acid, which is produced before chicoric acid, filling the lag phase. Then, we identified two additional typical clade IA SCPL acyltransferases, named chlorogenic acid condensing enzymes (CCEs), that catalyze the biosynthesis of 3,5-dicaffeoylquinic acid from chlorogenic acid with different kinetic characteristics. Chlorogenic acid inhibits radicle elongation in a dose-dependent manner, explaining the potential biological role of SCPL acyltransferases-mediated continuous chlorogenic acid metabolism during germination. Both CCE1 and CCE2 are highly conserved among Echinacea species, supporting the observed metabolism of chlorogenic acid to 3,5-dicaffeoylquinic acid in two Echinacea species without chicoric acid accumulation. The discovery of SCPL acyltransferase involved in the biosynthesis of 3,5-dicaffeoylquinic acid suggests convergent evolution. Our research clarifies the metabolism strategy of chlorogenic acid in Echinacea species and provides more insight into plant metabolism.

CTCOSY-JRES: A high-resolution three-dimensional NMR method for unveiling J-couplings.

Two-dimensional (2D) J-resolved spectroscopy provides valuable information on J-coupling constants for molecular structure analysis by resolving one-dimensional (1D) spectra. However, it is challenging to decipher the J-coupling connectivity in 2D J-resolved spectra because the J-coupling connectivity cannot be directly provided. In addition, 2D homonuclear correlation spectroscopy (COSY) can directly elucidate molecular structures by tracking the J-coupling connectivity between protons. However, this method is limited by the problem of spectral peak crowding and is only suitable for simple sample systems. To fully understand the intuitive coupling relationship and coupling constant information, we propose a three-dimensional (3D) COSY method called CTCOSY-JRES (Constant-Time COrrelation SpectroscopY and J-REsolved Spectroscopy) in this paper. By combining the J-resolved spectrum with the constant-time COSY technique, a doubly decoupled COSY spectrum can be provided while preserving the J-coupling constant along an additional dimension, ensuring high-resolution analysis of J-coupling connectivity and J-coupling information. Moreover, compression sensing and fold-over correction techniques are introduced to accelerate experimental acquisition. The CTCOSY-JRES method has been successfully validated in a variety of sample systems, including industrial, agricultural, and biopharmaceutical samples, revealing complex coupling interactions and providing deeper insights into the resolution of molecular structures.

Time-/dose- series transcriptome data analysis and traditional Chinese medicine treatment of pneumoconiosis.

Pneumoconiosis' pathogenesis is still unclear and specific drugs for its treatment are lacking. Analysis of series transcriptome data often uses a single comparison method, and there are few reports on using such data to predict the treatment of pneumoconiosis with traditional Chinese medicine (TCM). Here, we proposed a new method for analyzing series transcriptomic data, series difference analysis (SDA), and applied it to pneumoconiosis. By comparison with 5 gene sets including existing pneumoconiosis-related genes and gene set functional enrichment analysis, we demonstrated that the new method was not inferior to two existing traditional analysis methods. Furthermore, based on the TCM-drug target interaction network, we predicted the TCM corresponding to the common pneumoconiosis-related genes obtained by multiple methods, and combined them with the high-frequency TCM for its treatment obtained through literature mining to form a new TCM formula for it. After feeding it to pneumoconiosis modeling mice for two months, compared with the untreated group, the coat color, mental state and tissue sections of the mice in the treated group were markedly improved, indicating that the new TCM formula has a certain efficacy. Our study provides new insights into method development for series transcriptomic data analysis and treatment of pneumoconiosis.