Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis.

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. eNet is robust and widely applicable in various human or mouse tissues datasets. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells.

Proteomic Analysis of Idiopathic Nephrotic Syndrome Triggered by Primary Podocytopathies in Adults: Regulatory Mechanisms and Diagnostic Implications.

Idiopathic nephrotic syndrome (NS) is a heterogeneous group of glomerular disorders which includes two major phenotypes: minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). MCD and FSGS are classic types of primary podocytopathies. We aimed to explore the molecular mechanisms in NS triggered by primary podocytopathies and evaluate diagnostic value of the selected proteomic signatures by analyzing blood proteome profiling. Totally, we recruited 90 participants in two cohorts. The first cohort was analyzed using label-free quantitative (LFQ) proteomics to discover differential expressed proteins and identify enriched biological process in NS which were further studied in relation to clinical markers of kidney injury. The second cohort was analyzed using parallel reaction monitoring-based quantitative proteomics to verify the data of LFQ proteomics and assess the diagnostic performance of the selected proteins using receiver-operating characteristic curve analysis. Several biological processes (such as immune response, cell adhesion, and response to hypoxia) were found to be associated with kidney injury during MCD and FSGS. Moreover, three proteins (CSF1, APOC3, and LDLR) had over 90% sensitivity and specificity in detecting adult NS triggered by primary podocytopathies. The identified biological processes may play a crucial role in MCD and FSGS pathogenesis. The three blood protein markers are promising for diagnosing adult NS triggered by primary podocytopathies.

Mechanism of ferroptosis in breast cancer and research progress of natural compounds regulating ferroptosis.

Breast cancer is the most prevalent cancer worldwide and its incidence increases with age, posing a significant threat to women's health globally. Due to the clinical heterogeneity of breast cancer, the majority of patients develop drug resistance and metastasis following treatment. Ferroptosis, a form of programmed cell death dependent on iron, is characterized by the accumulation of lipid peroxides, elevated levels of iron ions and lipid peroxidation. The underlying mechanisms and signalling pathways associated with ferroptosis are intricate and interconnected, involving various proteins and enzymes such as the cystine/glutamate antiporter, glutathione peroxidase 4, ferroptosis inhibitor 1 and dihydroorotate dehydrogenase. Consequently, emerging research suggests that ferroptosis may offer a novel target for breast cancer treatment; however, the mechanisms of ferroptosis in breast cancer urgently require resolution. Additionally, certain natural compounds have been reported to induce ferroptosis, thereby interfering with breast cancer. Therefore, this review not only discusses the molecular mechanisms of multiple signalling pathways that mediate ferroptosis in breast cancer (including metastasis, invasion and proliferation) but also elaborates on the mechanisms by which natural compounds induce ferroptosis in breast cancer. Furthermore, this review summarizes potential compound types that may serve as ferroptosis inducers in future tumour cells, providing lead compounds for the development of ferroptosis-inducing agents. Last, this review proposes the potential synergy of combining natural compounds with traditional breast cancer drugs in the treatment of breast cancer, thereby suggesting future directions and offering new insights.

HyperGCN: an effective deep representation learning framework for the integrative analysis of spatial transcriptomics data.

BACKGROUND: Advances of spatial transcriptomics technologies enabled simultaneously profiling gene expression and spatial locations of cells from the same tissue. Computational tools and approaches for integration of transcriptomics data and spatial context information are urgently needed to comprehensively explore the underlying structure patterns. In this manuscript, we propose HyperGCN for the integrative analysis of gene expression and spatial information profiled from the same tissue. HyperGCN enables data visualization and clustering, and facilitates downstream analysis, including domain segmentation, the characterization of marker genes for the specific domain structure and GO enrichment analysis. RESULTS: Extensive experiments are implemented on four real datasets from different tissues (including human dorsolateral prefrontal cortex, human positive breast tumors, mouse brain, mouse olfactory bulb tissue and Zabrafish melanoma) and technologies (including 10X visium, osmFISH, seqFISH+, 10X Xenium and Stereo-seq) with different spatial resolutions. The results show that HyperGCN achieves superior clustering performance and produces good domain segmentation effects while identifies biologically meaningful spatial expression patterns. This study provides a flexible framework to analyze spatial transcriptomics data with high geometric complexity. CONCLUSIONS: HyperGCN is an unsupervised method based on hypergraph induced graph convolutional network, where it assumes that there existed disjoint tissues with high geometric complexity, and models the semantic relationship of cells through hypergraph, which better tackles the high-order interactions of cells and levels of noise in spatial transcriptomics data.

Enzyme-Driven LC-HRMS Approach for Specific Recognition of 12α-Hydroxy Bile Acids.

The synthesis of 12α-hydroxylated bile acids (12HBAs) and non-12α-hydroxylated bile acids (non-12HBAs) occurs via classical and alternative pathways, respectively. The composition of these BAs is a crucial index for pathophysiologic assessment. However, accurately differentiating 12HBAs and non-12HBAs is highly challenging due to the limited standard substances. Here, we innovatively introduce 12α-hydroxysteroid dehydrogenase (12α-HSDH) as an enzymatic probe synthesized by heterologous expression in Escherichia coli, which can specifically and efficiently convert 12HBAs in vitro under mild conditions. Coupled to the conversion rate determined by liquid chromatography-high resolution mass spectrometry (LC-HRMS), this enzymatic probe allows for the straightforward distinguishing of 210 12HBAs and 312 non-12HBAs from complex biological matrices, resulting in a BAs profile with a well-defined hydroxyl feature at the C12 site. Notably, this enzyme-driven LC-HRMS approach can be extended to any molecule with explicit knowledge of enzymatic transformation. We demonstrate the practicality of this BAs profile in terms of both revealing cross-species BAs heterogeneity and monitoring the alterations of 12HBAs and non-12HBAs under asthma disease. We envisage that this work will provide a novel pattern to recognize the shift of BA metabolism from classical to alternative synthesis pathways in different pathophysiological states, thereby offering valuable insights into the management of related diseases.

FNICM: A New Methodology To Identify Core Metabolites Based on Significantly Perturbed Metabolic Subnetworks.

Metabolomics has emerged as a powerful tool in biomedical research to understand the pathophysiological processes and metabolic biomarkers of diseases. Nevertheless, it is a significant challenge in metabolomics to identify the reliable core metabolites that are closely associated with the occurrence or progression of diseases. Here, we proposed a new research framework by integrating detection-based metabolomics with computational network biology for function-guided and network-based identification of core metabolites, namely, FNICM. The proposed FNICM methodology is successfully utilized to uncover ulcerative colitis (UC)-related core metabolites based on the significantly perturbed metabolic subnetwork. First, seed metabolites were screened out using prior biological knowledge and targeted metabolomics. Second, by leveraging network topology, the perturbations of the detected seed metabolites were propagated to other undetected ones. Ultimately, 35 core metabolites were identified by controllability analysis and were further hierarchized into six levels based on confidence level and their potential significance. The specificity and generalizability of the discovered core metabolites, used as UC's diagnostic markers, were further validated using published data sets of UC patients. More importantly, we demonstrated the broad applicability and practicality of the FNICM framework in different contexts by applying it to multiple clinical data sets, including inflammatory bowel disease, colorectal cancer, and acute coronary syndrome. In addition, FNICM was also demonstrated as a practicality methodology to identify core metabolites correlated with the therapeutic effects of Clematis saponins. Overall, the FNICM methodology is a new framework for identifying reliable core metabolites for disease diagnosis and drug treatment from a systemic and a holistic perspective.

Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.

Glutathione (GSH) redox control and arginine metabolism are critical in regulating the physiological response to injury and oxidative stress. Quantification assessment of the GSH/arginine redox metabolism supports monitoring metabolic pathway shifts during pathological processes and their linkages to redox regulation. However, assessing the redox status of organisms with complex matrices is challenging, and single redox molecule analysis may not be accurate for interrogating the redox status in cells and in vivo. Herein, guided by a paired derivatization strategy, we present a new ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based approach for the functional assessment of biological redox status. Two structurally analogous probes, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) and newly synthesized 2-methyl-6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (MeAQC), were set for paired derivatization. The developed approach was successfully applied to LPS-stimulated RAW 264.7 cells and HDM-induced asthma mice to obtain quantitative information on GSH/arginine redox metabolism. The results suggest that the redox status was remarkably altered upon LPS and HDM stimulation. We expect that this approach will be of good use in a clinical biomarker assay and potential drug screening associated with redox metabolism, oxidative damage, and redox signaling.

HONMF: integration analysis of multi-omics microbiome data via matrix factorization and hypergraph.

MOTIVATION: The accumulation of multi-omics microbiome data provides an unprecedented opportunity to understand the diversity of bacterial, fungal, and viral components from different conditions. The changes in the composition of viruses, bacteria, and fungi communities have been associated with environments and critical illness. However, identifying and dissecting the heterogeneity of microbial samples and cross-kingdom interactions remains challenging. RESULTS: We propose HONMF for the integrative analysis of multi-modal microbiome data, including bacterial, fungal, and viral composition profiles. HONMF enables identification of microbial samples and data visualization, and also facilitates downstream analysis, including feature selection and cross-kingdom association analysis between species. HONMF is an unsupervised method based on hypergraph induced orthogonal non-negative matrix factorization, where it assumes that latent variables are specific for each composition profile and integrates the distinct sets of latent variables through graph fusion strategy, which better tackles the distinct characteristics in bacterial, fungal, and viral microbiome. We implemented HONMF on several multi-omics microbiome datasets from different environments and tissues. The experimental results demonstrate the superior performance of HONMF in data visualization and clustering. HONMF also provides rich biological insights by implementing discriminative microbial feature selection and bacterium-fungus-virus association analysis, which improves our understanding of ecological interactions and microbial pathogenesis. AVAILABILITY AND IMPLEMENTATION: The software and datasets are available at https://github.com/chonghua-1983/HONMF.

Variability in an effector gene promoter of a necrotrophic fungal pathogen dictates epistasis and effector-triggered susceptibility in wheat.

The fungus Parastagonospora nodorum uses proteinaceous necrotrophic effectors (NEs) to induce tissue necrosis on wheat leaves during infection, leading to the symptoms of septoria nodorum blotch (SNB). The NEs Tox1 and Tox3 induce necrosis on wheat possessing the dominant susceptibility genes Snn1 and Snn3B1/Snn3D1, respectively. We previously observed that Tox1 is epistatic to the expression of Tox3 and a quantitative trait locus (QTL) on chromosome 2A that contributes to SNB resistance/susceptibility. The expression of Tox1 is significantly higher in the Australian strain SN15 compared to the American strain SN4. Inspection of the Tox1 promoter region revealed a 401 bp promoter genetic element in SN4 positioned 267 bp upstream of the start codon that is absent in SN15, called PE401. Analysis of the world-wide P. nodorum population revealed that a high proportion of Northern Hemisphere isolates possess PE401 whereas the opposite was observed in representative P. nodorum isolates from Australia and South Africa. The presence of PE401 removed the epistatic effect of Tox1 on the contribution of the SNB 2A QTL but not Tox3. PE401 was introduced into the Tox1 promoter regulatory region in SN15 to test for direct regulatory roles. Tox1 expression was markedly reduced in the presence of PE401. This suggests a repressor molecule(s) binds PE401 and inhibits Tox1 transcription. Infection assays also demonstrated that P. nodorum which lacks PE401 is more pathogenic on Snn1 wheat varieties than P. nodorum carrying PE401. An infection competition assay between P. nodorum isogenic strains with and without PE401 indicated that the higher Tox1-expressing strain rescued the reduced virulence of the lower Tox1-expressing strain on Snn1 wheat. Our study demonstrated that Tox1 exhibits both 'selfish' and 'altruistic' characteristics. This offers an insight into a complex NE-NE interaction that is occurring within the P. nodorum population. The importance of PE401 in breeding for SNB resistance in wheat is discussed.

Development and validation of a nomogram for predicting the interstitial fibrosis and tubular atrophy in patients with lupus nephritis.

OBJECTIVE: Interstitial fibrosis and tubular atrophy (IFTA) were frequent histologic features of lupus nephritis (LN), and LN patients with IFTA have poor renal outcomes. In this study, we aimed to construct prediction models for the IFTA in LN patients. METHODS: This retrospective study included 303 patients with biopsy proven LN at the Affiliated Hospital of Qingdao University and Union Hospital of Fujian Medical University. The participants were randomly divided into development and validation cohorts. They were further divided into IFTA and non-IFTA groups. The least absolute shrinkage and selection operator (LASSO) regression model with laboratory test results collected at the time of kidney biopsy was used to optimize feature selection for the risk model. Multivariable logistic regression analysis was applied to build a predicting model incorporating the feature selected in the LASSO regression model. Discrimination, calibration, and clinical usefulness of the predicting model were assessed using the C-index, calibration plot, and ROC curve analysis. Internal validation was assessed using the bootstrapping validation. A nomogram for individual assessment was constructed based on the preferable model. RESULTS: Predictors contained in the prediction nomogram included age, body mass index (BMI), mean arterial pressure (MAP), logANA, C3, eGFR and serum uric acid. The model displayed good discrimination with a C-index of 0.794 (95% CI 0.734-0.854) and good calibration. High C-index value of 0.857 (95% CI 0.776-0.938) could still be reached in the interval validation. A nomogram model based on the LASSO model was created for producing a probability score of IFTA in LN patients. CONCLUSION: With excellent predictive abilities, the nomogram may provide a simple and reliable tool to distinguish LN patients with IFTA and helps physicians make clinical decisions in their comprehensive assessment.

Preclinical study and first-in-human imaging of [18F]FAP-2286, and comparison with 2-[18F]FDG PET/CT in various cancer patients.

PURPOSE: Fibroblast-activated protein (FAP) is highly expressed in cancer-associated fibroblasts (CAFs) of many solid cancers, but low or absent in normal tissues. Our study aimed to develop a novel FAP-specific tracer, namely [18F]FAP-2286, and evaluated its performance in comparison with well-established agents such as [18F]FAPI-42 and [68Ga]Ga-FAP-2286 in preclinical research, as well as 2-[18F]FDG in pilot clinical study. METHODS: [18F]FAP-2286 was manually synthesized in accordance with Good Manufacturing Practice (GMP). Subsequent investigations encompassed cell uptake, competitive binding affinity, internalization and efflux assays using HT-1080hFAP cell lines. PET imaging and biodistribution studies were conducted in HEK-293ThFAP, A549hFAP, HT-1080hFAP tumor-bearing mice as well as HEK-293T, A549 and HT-1080 control groups. Furthermore, clinical evaluation of [18F]FAP-2286 was performed in fifteen patients with various cancers compared to 2-[18F]FDG PET. RESULTS: The radiolabeling yield of [18F]FAP-2286 was 30.53 ± 5.20%, with a radiochemical purity exceeding 97%. In cell assays, [18F]FAP-2286 showed specific uptake, high internalization fraction and low cellular efflux. Rapid tumor uptake and satisfactory tumor retention was observed on micro-PET imaging and cancer patients. Meanwhile, the clinical research demonstrated that [18F]FAP-2286 may represent an alternative for low glucose-metabolism malignant tumors PET imaging such as gastric cancers. CONCLUSION: [18F]FAP-2286 showed superior imaging quality including rapid and high target uptake and satisfactory retention in both tumor-bearing mice and cancer patients. It may emerge as a promising candidate for early or delayed phase imaging and 2-[18F]FDG non-avid cancers PET scan.

An investigation into the correlation between early-to-mid pregnancy exercise combined with cognitive behavioral therapy and anxiety levels and quality of life in patients.

OBJECTIVE: The aim of this study was to investigate the effects of exercise combined with cognitive behavioral therapy (CBT) on anxiety and quality of life in pregnant women. METHODS: This study adopted a prospective randomized controlled trial design, and divided 60 pregnant women in the first and second trimesters into two groups. The control group received routine prenatal education, and the experimental group added moderate exercise and CBT on the basis of routine prenatal education. All participants completed the Hamilton Anxiety Rating Scale (HARS) and World Health Organization Quality of Life-BREF (WHOQOL-BREF) at the start of the study (baseline) and at 6 weeks after the intervention. RESULTS: Baseline data, scores on HARS, and scores on WHOQOL-BREF were found to be consistent among the two groups of patients prior to the intervention (all P > 0.05). Following the intervention, the implementation of exercise combined with CBT resulted in significant improvements in anxiety levels within the experimental group, particularly with respect to aspects such as anxious mood, tension, insomnia, cognitive function, cardiovascular symptoms, and gastrointestinal symptoms (all P < 0.05). Similarly, the combination of exercise and CBT led to significant enhancement in the quality of life in the experimental group, particularly in areas such as physical health, psychological health, and environmental factors (all P < 0.05). Nevertheless, no significant disparities were observed between the two groups in terms of fears, depressive mood, muscular and sensory somatic symptoms, respiratory symptoms, genitourinary symptoms, autonomic symptoms, behavior during the interview, and social relationships (all P > 0.05). CONCLUSION: Exercise combined with CBT can effectively reduce the anxiety of pregnant women and improve their quality of life, which has important clinical significance for improving the mental health and quality of life of pregnant women in the first and second trimesters.

Treatment of low-C/N nitrate wastewater using a partial denitrification-anammox granule system: Granule reconstruction, stability, and microbial structure analyses.

Industrial wastewater discharged into sewer systems is often characterized by high nitrate contents and low C/N ratios, resulting in high treatment costs when using conventional activated sludge methods. This study introduces a partial denitrification-anammox (PD/A) granular process to address this challenge. The PD/A granular process achieved an effluent TN level of 3.7 mg/L at a low C/N ratio of 2.3. Analysis of a typical cycle showed that the partial denitrification peaked within 15 min and achieved a nitrate-to-nitrite transformation ratio of 86.9%. Anammox, which was activated from 15 to 120 min, contributed 86.2% of the TN removal. The system exhibited rapid recovery from post-organic shock, which was attributed to significant increases in protein content within TB-EPS. Microbial dispersion and reassembly were observed after coexistence of the granules, with Thauera (39.12%) and Candidatus Brocadia (1.25%) identified as key functional microorganisms. This study underscores the efficacy of PD/A granular sludge technology for treating low-C/N nitrate wastewater.

Green Synthesis and Antifungal Activities of Novel N-Aryl Carbamate Derivatives.

Carbamate is a key structural motif in the development of fungicidal compounds, which is still promising and robust in the discovery of green pesticides. Herein, we report the synthesis and evaluation of the fungicidal activity of 35 carbamate derivatives, among which 19 compounds were synthesized in our previous report. These derivatives were synthesized from aromatic amides in a single step, which was a green oxidation process for Hofmann rearrangement using oxone, KCl and NaOH. Their chemical structures were characterized by 1H NMR, 13C NMR and high-resolution mass spectrometry. Their antifungal activity was tested against seven plant fungal pathogens. Many of the compounds exhibited good antifungal activity in vitro (inhibitory rate > 60% at 50 µg/mL). Compound 1ag exhibited excellent broad-spectrum antifungal activities with inhibition rates close to or higher than 70% at 50 µg/mL. Notably, compound 1af demonstrated the most potent inhibition against F. graminearum, with an EC50 value of 12.50 µg/mL, while compound 1z was the most promising candidate fungicide against F. oxysporum (EC50 = 16.65 µg/mL). The structure-activity relationships are also discussed in this paper. These results suggest that the N-aryl carbamate derivatives secured by our green protocol warrant further investigation as potential lead compounds for novel antifungal agents.

The regulatory mechanism of rapid lignification for timely anther dehiscence.

Anther dehiscence is a crucial event in plant reproduction, tightly regulated and dependent on the lignification of the anther endothecium. In this study, we investigated the rapid lignification process that ensures timely anther dehiscence in Arabidopsis. Our findings reveal that endothecium lignification can be divided into two distinct phases. During Phase I, lignin precursors are synthesized without polymerization, while Phase II involves simultaneous synthesis of lignin precursors and polymerization. The transcription factors MYB26, NST1/2, and ARF17 specifically regulate the pathway responsible for the synthesis and polymerization of lignin monomers in Phase II. MYB26-NST1/2 is the key regulatory pathway responsible for endothecium lignification, while ARF17 facilitates this process by interacting with MYB26. Interestingly, our results demonstrate that the lignification of the endothecium, which occurs within approximately 26 h, is much faster than that of the vascular tissue. These findings provide valuable insights into the regulation mechanism of rapid lignification in the endothecium, which enables timely anther dehiscence and successful pollen release during plant reproduction.

Comparison of outcomes between Hodgkin's lymphoma patients treated in and outside clinical trials: A study based on the EORTC-Dutch late effects cohort-linked data.

Studies have shown higher survival rates for patients with Hodgkin lymphoma (HL) treated within clinical trials compared to patients treated outside clinical trials. However, endpoints are often limited to overall survival (OS). In this retrospective cohort study, we investigated the effect of trial participation on OS, the incidence of relapse, second cancer, and cardiovascular disease (CVD). The study population consisted of patients with HL, aged between 14 and 51 years at diagnosis, who started their treatment between 1962 and 2002 at three Dutch cancer centres. Patients were either included in the EORTC Lymphoma Group trials (H1-H9) or treated according to standard guidelines at the time. After adjusting for differences in baseline characteristics, trial participation was associated with longer OS (median OS: 29.4 years [95%CI: 27.0-31.6] for treatment inside trials versus 27.4 years [95%CI: 26.0-28.5] for treatment outside trials, p = .046), a lower incidence of relapse (HR = 0.79, 95%CI: 0.63-0.98, p = .036) and a higher incidence of CVD (HR = 1.49, 95%CI: 1.23-1.79, p < .001). The trial effect for CVD was present only for patients treated before 1983. No evidence of differences in the incidence of second cancer was found. Consequently, essential results from clinical trials should be implemented into standard practice without undue delay.

Hyposterolactone A, a 3α-Hydroxy Steroidal Lactone from the Deep-Sea-Derived Fungus Hypocrea sp. ZEN14.

Chemical investigation of the deep-sea-derived fungus Hypocrea sp. ZEN14 afforded a new 3α-hydroxy steroidal lactone, hyposterolactone A (1) and 25 known secondary metabolites (2-26). The structure of the new compound was established by detailed spectroscopic analysis, electronic circular dichroism (ECD) calculation as well as a J-based configuration analysis. Compound 10 showed potent cytotoxicity against Huh7 and Jurkat cells with IC50 values of 1.4 µM and 6.7 µM, respectively.

Comparison of Semen Aesculi species from different geographical origins and horse chestnut based on metabolomics and chemometrics analysis.

BACKGROUND: Semen Aesculi, a traditional Chinese herbal medicine, has a long history of use for treating chest and abdominal pain with distension. In addition, the horse chestnut (Aesculus hippocastanum L.) is another species of Aesculus in Europe and has notable clinical significance in alleviating chronic venous insufficiency, hemorrhoids, and postoperative edema. Thus, highlighting the comparative study of Semen Aesculi and horse chestnut may broaden clinical applications. OBJECTIVES: To conduct a comprehensive comparative analysis on the chemical profiling of these two varieties and determine whether they have equivalent clinical efficacy by integrating plant metabolomics and multivariate statistical methods. METHODS: Initially, a comprehensive characterisation was performed using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS/MS) platform, and in total 44 active ingredients were identified. Then, untargeted metabolomics combined with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) was applied for the discrimination of a German species and three official Chinese species. Next, 24 marker compounds responsible for the discrimination of different species were screened out and used to predict the species of unknown samples by genetic algorithm-optimised support vector machine (GA-SVM) with a high prediction accuracy. Finally, a heatmap visualisation was employed for clarifying the distribution of the identified active ingredients. RESULTS: The three species of Chinese Semen Aesculi showed distinct separation from each other, while European horse chestnut and Aesculus chinensis Bunge were similar in chemical composition. CONCLUSIONS: This work provided experimental evidence for further expanding the clinical application of Chinese Semen Aesculi and promoted the species identification and quality control of Semen Aesculi.

Design, Synthesis and Antifungal Activities of Novel Pyrazole Analogues Containing the Aryl Trifluoromethoxy Group.

On the basis of the three-component synthetic methodology developed by us, a total of twenty-six pyrazole compounds bearing aryl OCF3 were designed and synthesized. Their chemical structures were characterized by 1H and 13C nuclear magnetic resonance and high-resolution mass spectrometry. These compounds were evaluated systematically for antifungal activities in vitro against six plant pathogenic fungi by the mycelium growth rate method. Most of the compounds showed some activity against each of the fungi at 100 µg/mL. Compounds 1t and 1v exhibited higher activity against all the tested fungi, and 1v displayed the highest activity against F. graminearum with an EC50 value of 0.0530 µM, which was comparable with commercial pyraclostrobin. Structure-activity relationship analysis showed that, with respect to the R1 substituent, the straight chain or cycloalkyl ring moiety was a key structural moiety for the activity, and the R2 substituent on the pyrazole ring could have significant effects on the activity. Simple and readily available pyrazoles with potent antifungal activity were obtained, which are ready for further elaboration to serve as a pharmacophore in new potential antifungal agents.

Optimized Traffic Light System with AIC and Application to the 2021 M6.7 Yangbi Earthquake Sequence.

One important question in earthquake prediction is whether a moderate or large earthquake will be followed by an even bigger one. Through temporal b-value evolution analysis, the traffic light system can be used to estimate if an earthquake is a foreshock. However, the traffic light system does not take into account the uncertainty of b-values when they constitute a criterion. In this study, we propose an optimization of the traffic light system with the Akaike Information Criterion (AIC) and bootstrap. The traffic light signals are controlled by the significance level of the difference in b-value between the sample and the background rather than an arbitrary constant. We applied the optimized traffic light system to the 2021 Yangbi earthquake sequence, which could be explicitly recognized as foreshock-mainshock-aftershock using the temporal and spatial variations in b-values. In addition, we used a new statistical parameter related to the distance between earthquakes to track earthquake nucleation features. We also confirmed that the optimized traffic light system works on a high-resolution catalog that includes small-magnitude earthquakes. The comprehensive consideration of b-value, significance probability, and seismic clustering might improve the reliability of earthquake risk judgment.