[Identification and 3D architecture analysis of the LIPC gene mutation in a pedigree with familial hypercholesterolemia-like phenotype]

Objective: To identify and analyze 3D architecture of the mutational sites of susceptible genes in a pedigree with familial hypercholesterolemia-like phenotype (FHLP). Methods: This is a case series study. A pedigree with suspected familial hypercholesterolemia was surveyed. The proband admitted in Beijing Anzhen Hospital in April 2019. Whole-exome sequencing was performed to determine the mutational sites of susceptible genes in the proband. Polymerase chain reaction (PCR) sequencing was used to verify the pathogenic variant on proband's relatives. The structural and functional changes of the proteins were analyzed and predicted by Discovery Studio 4.0 and PyMol 2.0. Results: The patients in the pedigree showed abnormal lipid profiles, especially elevated levels of total cholesterol(TC). The genetic screening detected the c.1330C>T SNP in the exon 8 of lipase C (LIPC) gene, this mutation leads to an amino acid substitution from arginine to cysteine at position 444 (Arg444Cys), in the proband and proband's father and brother. In this family, members with this mutation exhibited elevated TC, whereas lipid profile was normal from the proband's mother without this mutation. This finding indicated that LIPC: c.1330C>T mutation might be the mutational sites of susceptible genes. The analysis showed that Arg444Cys predominantly affected the ligand-binding property of the protein, but had a limited impact on catalytic function. Conclusion: LIPC: c.1330C>T is a new mutational site of susceptible genes in this FHLP pedigree.

Molecular characterization and protective efficacy of vacuolar protein sorting 29 from Eimeria tenella

Introduction

Vacuolar protein sorting 29 (VPS29) is a core component of the retromer-retriever complex and is essential for recycling numerous cell-surface cargoes from endosomes. However, there are no reports yet on VPS29 of Eimeria spp.

Methods

Here, we cloned and prokaryotically expressed a partial sequence of Eimeria tenella VPS29 (EtVPS29) with RT-PCR and engineered strain of Escherichia coli respectively. The localization of the VPS29 protein in E. tenella sporozoites was investigated with immunofluorescence (IFA) and overexpression assays. And its protective efficacy against E. tenella infection was investigated in chickens with the animal protection test.

Results

An EtVPS29 gene fragment with an ORF reading frame of 549 bp was cloned. The band size of the expressed recombinant protein, rEtVPS29, was approximately 39 kDa and was recognized by the chicken anti-E. tenella positive serum. EtVPS29 protein was observed widely distributing in the cytoplasm of E. tenella sporozoites in the IFA and overexpression assays. rEtVPS29 significantly increased average body weight gain and decreased mean lesion score and oocyst output in chickens. The relative weight gain rate in the rEtVPS29-immunized group was 62.9%, which was significantly higher than that in the unimmunized and challenged group (P < 0.05). The percentage of reduced oocyst output in the rEtVPS29 immunized group was 32.2%. The anticoccidial index of the rEtVPS29-immunized group was 144.2. Serum ELISA also showed that rEtVPS29 immunization induced high levels of specific antibodies in chickens.

Discussion

These results suggest that rEtVPS29 can induce a specific immune response and is a potential candidate for the development of novel vaccines against E. tenella infections in chickens.

Methionine restriction promotes cGAS activation and chromatin untethering through demethylation to enhance antitumor immunity

Cyclic GMP-AMP synthase (cGAS) is the major sensor for cytosolic DNA and activates type I interferon signaling and plays an essential role in antitumor immunity. However, it remains unclear whether the cGAS-mediated antitumor activity is affected by nutrient status. Here, our study reports that methionine deprivation enhances cGAS activity by blocking its methylation, which is catalyzed by methyltransferase SUV39H1. We further show that methylation enhances the chromatin sequestration of cGAS in a UHRF1-dependent manner. Blocking cGAS methylation enhances cGAS-mediated antitumor immunity and suppresses colorectal tumorigenesis. Clinically, cGAS methylation in human cancers correlates with poor prognosis. Thus, our results indicate that nutrient stress promotes cGAS activation via reversible methylation, and suggest a potential therapeutic strategy for targeting cGAS methylation in cancer treatment.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Global Visual-Inertial Localization for Autonomous Vehicles with Pre-Built Map

Accurate, robust and drift-free global pose estimation is a fundamental problem for autonomous vehicles. In this work, we propose a global drift-free map-based localization method for estimating the global poses of autonomous vehicles that integrates visual-inertial odometry and global localization with respect to a pre-built map. In contrast to previous work on visual-inertial localization, the global pre-built map provides global information to eliminate drift and assists in obtaining the global pose. Additionally, in order to ensure the local odometry frame and the global map frame can be aligned accurately, we augment the transformation between these two frames into the state vector and use a global pose-graph optimization for online estimation. Extensive evaluations on public datasets and real-world experiments demonstrate the effectiveness of the proposed method. The proposed method can provide accurate global pose-estimation results in different scenarios. The experimental results are compared against the mainstream map-based localization method, revealing that the proposed approach is more accurate and consistent than other methods.

Antifungal Activity, Structure-Activity Relationship and Molecular Docking Studies of 1,2,4-Triazole Schiff Base Derivatives

Fourteen novel Schiff base compounds (AS-1∼AS-14) containing 5-amino-1H-1,2,4-triazole-3-carboxylic acid and substituted benzaldehyde were successfully synthesized, and their structures were verified by melting point, elemental analysis (EA) and spectroscopic techniques (Fourier Transform Infra-Red (FT-IR) and Nuclear Magnetic Resonance (NMR)). In vitro hyphal measurements were used to investigate the antifungal activities of the synthesised compounds against Wheat gibberellic, Maize rough dwarf and Glomerella cingulate. The preliminary studies indicated that all compounds had good inhibitory effect on Wheat gibberellic and Maize rough dwarf, among which the compounds of AS-1 (7.44 mg/L, 7.27 mg/L), AS-4 (6.80 mg/L, 9.57 mg/L) and AS-14 (5.33 mg/L, 6.53 mg/L) showed better antifungal activity than that of the standard drug fluconazole (7.66 mg/L, 6.72 mg/L); while inhibitory effect against Glomerella cingulate was poor, only AS-14 (5.67 mg/L) was superior to that of fluconazole (6.27 mg/L). The research of structure-activity relationship exhibited that the introduction of halogen elements on the benzene ring and electron withdrawing groups at the 2,4,5 positions on the benzene ring was beneficial to the improvement of the activity against Wheat gibberellic, while the large steric hindrance was not conducive to the improvement of the activity. Additionally, except for AS-1, AS-3 and AS-10, the other compounds had one or several ratio systems to achieve synergistic effect after recombination with pyrimethamine, among which AS-7 had significant synergistic effect and was expected to be a combinated agent with application prospects. Finally, the molecular docking results of isocitrate lyase with Wheat gibberellic displayed that the presence of hydrogen bonds enabled stable binding of compounds to receptor proteins, and the residues of ARG A: 252, ASN A: 432, CYS A: 215, SER A: 436 and SER A: 434 were the key residues for their binding. Comparing the docking binding energy and biological activity results, it was revealed that the lower the docking binding energy was, the stronger the inhibitory ability of the Wheat gibberellic, when the same position on the benzene ring was substituted.

Endotypes of chronic rhinosinusitis based on inflammatory and remodeling factors

BACKGROUND

Previous studies on the endotyping of chronic rhinosinusitis (CRS) that were based on inflammatory factors have broadened our understanding of the disease. However, the endotype of CRS combined with inflammatory and remodeling features has not yet been clearly elucidated.

OBJECTIVE

We sought to identify the endotypes of patients with CRS according to inflammatory and remodeling factors.

METHODS

Forty-eight inflammatory and remodeling factors in the nasal mucosal tissues of 128 CRS patients and 24 control subjects from northern China were analyzed by Luminex, ELISA, and ImmunoCAP. Sixteen factors were used to perform the cluster analysis. The characteristics of each cluster were analyzed using correlation analysis and validated by immunofluorescence staining.

RESULTS

Patients were classified into 5 clusters. Clusters 1 and 2 showed non-type 2 signatures with low biomarker concentrations, except for IL-19 and IL-27. Cluster 3 involved a low type 2 endotype with the highest expression of neutrophil factors, such as granulocyte colony-stimulating factor, IL-8, and myeloperoxidase, and remodeling factors, such as matrix metalloproteinases and fibronectin. Cluster 4 exhibited moderate type 2 inflammation. Cluster 5 exhibited high type 2 inflammation, which was associated with relatively higher levels of neutrophil and remodeling factors. The proportion of CRS with nasal polyps, asthma, allergies, anosmia, aspirin sensitivity, and the recurrence of CRS increased from clusters 1 to 5.

CONCLUSION

Diverse inflammatory mechanisms result in distinct CRS endotypes and remodeling profiles. The explicit differentiation and accurate description of these endotypes will guide targeted treatment decisions.

[Preliminary study on the effect of fecal microbiota transplantation on neurobehavior and gut microbiota of offspring rats exposed to arsenic]

Objective: To explore the effects of fecal microbiota transplantation (FMT) on neurobehavior and gut microbiota of arsenic-exposed offspring rats. Methods: In April 2021, Thirty-six SPF SD rats aged 8 weeks were seleted, rats were ranked by weight and divided into four groups according to randomized block design, namely control group, arsenic exposure group (As group) , arsenic+normal saline group (As+NaCl group) and As+FMT group, 6 females and 3 males in each group. Fecal microbiota fluid were provided by feces of rats in control group. Rats drank tap water containing 75 mg/L sodium arsenite for one week and then were caged together. The arsenic exposure was terminated until the pups were born. Female rats with vaginal plug were treated with fecal microbiota fluid via gavage during neurodevelopmental teratogenic window period. The volume of gavage was 1 ml/100 g with once every two days, for a total of three times. Weight alterations of offspring rats were recorded every week after weaning, and when offspring rats grew up for 6 weeks, Morris test and open field experiment was used to observe learning and memory abilities, as well as neurobehavioral performance of autonomous exploration and tension, respectively. 16S rDNA sequencing technology was used to detect microbiota diversities in fecal samples of rats in As group and As+FMT group. Results: Compared with the control group, the ratio of swimming distance and staying time in the target quadrant and the times of crossing the platform of rats in As group decreased significantly, and the motor distance, times entering central zone and the number of grid crossing of rats decreased significantly (P<0.05) . Compared with As group, the ratio of swimming distance in target quadrant, the motor distance in central zone and times entering central zone of rats in As+FMT group were evidently increased (P<0.05) . The analysis of fecal microbiota diversities showed that, at the phyla level, the relative abundance of Bacteroidetes in feces of rats in As+FMT group was higher than that in As group (68.34% vs 60.55%) , while the relative abundance of Firmicutes was lower than that in As group (28.02% vs 33.48%) . At the genus level, the relative abundance of Prevotella in As+FMT group was significantly higher than that in As group, becoming the dominant genus (42.08% vs 21.78%) . Additionally, compared with As group, a total of 22 genus were increased with 21 decreased genus in As+FMT group (P<0.05) . LEfSe analysis showed that dominant genuses in As+FMT group were Prevotella and UCG_005, and their relative abundance was significantly higher than that of As group (P<0.05) . Conclusion: FMT may alleviate the impaired learning and memory ability and anxiety like behavior of the offspring rats exposed to arsenic, and improve the disrupted gut microbiota.

Hetnet connectivity search provides rapid insights into how two biomedical entities are related

Hetnets, short for "heterogeneous networks", contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet connects 11 types of nodes - including genes, diseases, drugs, pathways, and anatomical structures - with over 2 million edges of 24 types. Previous work has demonstrated that supervised machine learning methods applied to such networks can identify drug repurposing opportunities. However, a training set of known relationships does not exist for many types of node pairs, even when it would be useful to examine how nodes of those types are meaningfully connected. For example, users may be curious not only how metformin is related to breast cancer, but also how the GJA1 gene might be involved in insomnia. We developed a new procedure, termed hetnet connectivity search, that proposes important paths between any two nodes without requiring a supervised gold standard. The algorithm behind connectivity search identifies types of paths that occur more frequently than would be expected by chance (based on node degree alone). We find that predictions are broadly similar to those from previously described supervised approaches for certain node type pairs. Scoring of individual paths is based on the most specific paths of a given type. Several optimizations were required to precompute significant instances of node connectivity at the scale of large knowledge graphs. We implemented the method on Hetionet and provide an online interface at https://het.io/search . We provide an open source implementation of these methods in our new Python package named hetmatpy .

Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study

OBJECTIVES

The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults.

DESIGN

A prospective cohort study.

SETTING

English Longitudinal Study of Ageing, 2002-2019.

PARTICIPANTS

A total of 4734 participants aged 50 years and older were included.

MEASUREMENTS

Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors.

RESULTS

During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively].

CONCLUSION

Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.

Hetnet connectivity search provides rapid insights into how biomedical entities are related

BACKGROUND

Hetnets, short for "heterogeneous networks," contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet, connects 11 types of nodes-including genes, diseases, drugs, pathways, and anatomical structures-with over 2 million edges of 24 types. Previous work has demonstrated that supervised machine learning methods applied to such networks can identify drug repurposing opportunities. However, a training set of known relationships does not exist for many types of node pairs, even when it would be useful to examine how nodes of those types are meaningfully connected. For example, users may be curious about not only how metformin is related to breast cancer but also how a given gene might be involved in insomnia.

FINDINGS

We developed a new procedure, termed hetnet connectivity search, that proposes important paths between any 2 nodes without requiring a supervised gold standard. The algorithm behind connectivity search identifies types of paths that occur more frequently than would be expected by chance (based on node degree alone). Several optimizations were required to precompute significant instances of node connectivity at the scale of large knowledge graphs.

CONCLUSION

We implemented the method on Hetionet and provide an online interface at https://het.io/search. We provide an open-source implementation of these methods in our new Python package named hetmatpy.

Hyperspectral imaging with machine learning for non-destructive classification of Astragalus membranaceus var. mongholicus, Astragalus membranaceus, and similar seeds

The roots of Astragalus membranaceus var. mongholicus (AMM) and A. membranaceus (AM) are widely used in traditional Chinese medicine. Although AMM has higher yields and accounts for a larger market share, its cultivation is fraught with challenges, including mixed germplasm resources and widespread adulteration of commercial seeds. Current methods for distinguishing Astragalus seeds from similar (SM) seeds are time-consuming, laborious, and destructive. To establish a non-destructive method, AMM, AM, and SM seeds were collected from various production areas. Machine vision and hyperspectral imaging (HSI) were used to collect morphological data and spectral data of each seed batch, which was used to establish discriminant models through various algorithms. Several preprocessing methods based on hyperspectral data were compared, including multiplicative scatter correction (MSC), standard normal variable (SNV), and first derivative (FD). Then selection methods for identifying informative features in the above data were compared, including successive projections algorithm (SPA), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS). The results showed that support vector machine (SVM) modeling of machine vision data could distinguish Astragalus seeds from SM with >99% accuracy, but could not satisfactorily distinguish AMM seeds from AM. The FD-UVE-SVM model based on hyperspectral data reached 100.0% accuracy in the validation set. Another 90 seeds were tested, and the recognition accuracy was 100.0%, supporting the stability of the model. In summary, HSI data can be applied to discriminate among the seeds of AMM, AM, and SM non-destructively and with high accuracy, which can drive standardization in the Astragalus production industry.

The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma

Objective

We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD).

Methods

We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated.

Results

Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p <0.01). Besides, we found that the infiltration of activated CD4+ T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the TP53, MUC16, and TTN genes were more common in the high-CSS subgroup, while the mutation of TP53, TTN, and CSMD3 genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (p <0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of AKT and PI3K, respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group.

Conclusions

CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.

Extracellular vesicles derived from mesenchymal stem cells confer protection against intervertebral disc degeneration through a microRNA-217-dependent mechanism

OBJECTIVE

Extracellular vesicles released by mesenchymal stem cells (MSC-EVs) can be applied to alleviate intervertebral disc degeneration (IVDD) by curbing apoptosis of nucleus pulposus cells (NPCs). The current study aims to evaluate the effect of MSC-EVs on NPC apoptosis and IVDD and the related regulatory mechanisms involving microRNA (miR)-217.

METHOD

Expression of miR-217 was examined in tumor necrosis factor-α (TNF-α)-induced NPCs and MSC-EVs, followed by identification in the relationship between miR-217, enhancer of zeste homolog 2 (EZH2) and forkhead box O-3 (FOXO3). After isolation of EVs from MSCs and subsequent co-culture with NPCs, we assessed effects of miR-217 on NPC viability, autophagy, senescence and apoptosis along with extracellular matrix (ECM) degradation. Further in vivo experiments were conducted in rat models of IVDD to substantiate the effect of miR-217 on IVDD.

RESULTS

Poor miR-217 expression was found in TNF-α-induced NPCs, while high miR-217 expression was identified in MSC-EVs (P < 0.05). MSC-EVs transferred miR-217 to NPCs and increased its expression, thus attenuating NPC apoptosis and ECM degradation (elevated collagen II and aggrecan but reduced MMP13 and ADAMTS5) (P < 0.05). miR-217 targeted EZH2, and EZH2 bound to the FOXO3 promoter and consequently downregulated its expression. FOXO3 restrained NPC apoptosis and ECM degradation by stimulating cell autophagy (P < 0.05). Furthermore, in vivo experimental results confirmed the suppressive role of miR-217 shuttled by MSC-EVs in IVDD.

CONCLUSION

Overall, the delivery of miR-217 may be a novel mechanism underlying the effect of MSC-EVs on NPC apoptosis and ECM degradation following IVDD.

Knowledge-guided deep learning models of drug toxicity improve interpretation

In drug development, a major reason for attrition is the lack of understanding of cellular mechanisms governing drug toxicity. The black-box nature of conventional classification models has limited their utility in identifying toxicity pathways. Here we developed DTox (deep learning for toxicology), an interpretation framework for knowledge-guided neural networks, which can predict compound response to toxicity assays and infer toxicity pathways of individual compounds. We demonstrate that DTox can achieve the same level of predictive performance as conventional models with a significant improvement in interpretability. Using DTox, we were able to rediscover mechanisms of transcription activation by three nuclear receptors, recapitulate cellular activities induced by aromatase inhibitors and pregnane X receptor (PXR) agonists, and differentiate distinctive mechanisms leading to HepG2 cytotoxicity. Virtual screening by DTox revealed that compounds with predicted cytotoxicity are at higher risk for clinical hepatic phenotypes. In summary, DTox provides a framework for deciphering cellular mechanisms of toxicity in silico.

Automating Predictive Toxicology Using ComptoxAI

ComptoxAI is a new data infrastructure for computational and artificial intelligence research in predictive toxicology. Here, we describe and showcase ComptoxAI's graph-structured knowledge base in the context of three real-world use-cases, demonstrating that it can rapidly answer complex questions about toxicology that are infeasible using previous technologies and data resources. These use-cases each demonstrate a tool for information retrieval from the knowledge base being used to solve a specific task: The "shortest path" module is used to identify mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease; the "expand network" module identifies communities that are linked to dioxin toxicity; and the quantitative structure-activity relationship (QSAR) dataset generator predicts pregnane X receptor agonism in a set of 4,021 pesticide ingredients. The contents of ComptoxAI's source data are rigorously aggregated from a diverse array of public third-party databases, and ComptoxAI is designed as a free, public, and open-source toolkit to enable diverse classes of users including biomedical researchers, public health and regulatory officials, and the general public to predict toxicology of unknowns and modes of action.

Effects of the Chinese herbal medicine Hong Huang decoction, on myocardial injury in breast cancer patients who underwent anthracycline-based chemotherapy

Objective

To assess the effects of Hong Huang Decoction (HHD), a Chinese herbal medicine, on myocardial injury in breast cancer patients who underwent anthracycline (ANT)-based chemotherapy.

Methods

A total of 51 patients with breast cancer who underwent an ANT-based chemotherapy program and met the inclusion/exclusion criteria were allocated to the treatment or placebo groups using a random number generation process. Patients in the treatment group received liquid HHD twice a day. Treatment was given from 1 day prior to chemotherapy up to the end of chemotherapy (after 6 months). Participants in the placebo group received a placebo over the same schedule. Left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), diagnostic markers of acute myocardial infarction [e.g., lactate dehydrogenase (LDH), creatine kinase-MB (CK-MB), and B-type natriuretic peptide (BNP)], nitric oxide (NO), superoxide dismutase (SOD), as well as pro-inflammatory cytokines [e.g., tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and human C-reactive protein (CRP)], and anti-inflammatory cytokine interleukin-10 (IL-10), were outcome measures assessed before chemotherapy, 3 and 6 months after chemotherapy.

Results

Compared to the placebo group, the GLS value was significantly higher in the treatment group (19.95 ± 1.16 vs. 19.06 ± 1.64, P ≤ 0.001). Significant differences were also noted for levels of SOD (689.71 ± 203.60 vs. 807.88 ± 182.10, P < 0.05), IL-6 (58.04 ± 22.06 vs. 194.20 ± 40.14, P ≤ 0.001), IL-10 (237.90 ± 94.98 vs. 68.81 ± 32.92, P ≤ 0.001), NO (75.05 ± 26.39 vs. 55.83 ± 19.37, P ≤ 0.005), and TNF-α (301.80 ± 134.20 vs. 680.30 ± 199.60, P ≤ 0.001) in the patients before chemotherapy compared to 6 months after initiating chemotherapy.

Conclusion

HHD regulated the levels of IL-6, IL-10, SOD, NO, and TNF-α. The results demonstrated that GLS is a better indicator of early myocardial injury compared to LVEF, and HHD could modulate oxidative stress to protect against ANT cardio toxicity.

Clinical trial registration

Chinese Clinical Trial Registry, identifier ChiCTR1900022394. Date of registration: 2019-04-09.