Plasma metabolomics and network pharmacology identified glutamate, glutamine, and arginine as biomarkers of depression under Shuganjieyu capsule treatment.

Depression is a psychiatric disorder and confers an enormous burden on society. Mild to moderate forms of depression (MMD) are particularly common. Our previous studies showed that the Shuganjieyu (SGJY) capsule might improve depressive and cognitive symptoms in patients with MMD. However, biomarkers evaluating the efficacy of SGJY and the underlying mechanism remains unclear. The aim of the present study was to discover efficacy biomarkers and explore the underlying mechanisms of SGJY as antidepression treatment. Twenty-three patients with MMD were recruited and administered with SGJY for 8 weeks. Results showed that the content of 19 metabolites changed significantly in the plasma of patients with MMD, among which 8 metabolites improved significantly after SGJY treatment. Network pharmacology analysis showed that 19 active compounds, 102 potential targets, and 73 enzymes were related to the mechanistic action of SGJY. Through a comprehensive analysis, we identified four hub enzymes (GLS2, GLS, GLUL, and ADC), three key differential metabolites (glutamine, glutamate, and arginine), and two shared pathways (alanine, aspartate, and glutamate metabolism; and arginine biosynthesis). Receiver operating characteristic curve (ROC) analysis showed that the three metabolites had a high diagnostic ability. The expression of hub enzymes was validated using RT-qPCR in animal models. Overall, glutamate, glutamine, and arginine may be potential biomarkers for evaluating the efficacy of SGJY. The present study provides a new strategy for pharmacodynamic evaluation and mechanistic study of SGJY, and offers new information for clinical practice and treatment research.

Decoding the underlying mechanisms of Di-Tan-Decoction in treating intracerebral hemorrhage based on network pharmacology.

BACKGROUND: Chinese medicine usually acts as "multi-ingredients, multi-targets and multi-pathways" on complex diseases, and these action modes reflect the coordination and integrity of the treatment process with traditional Chinese medicine (TCM). System pharmacology is developed based on the cross-disciplines of directional pharmacology, system biology, and mathematics, has the characteristics of integrity and synergy in the treatment process of TCM. Therefore, it is suitable for analyzing the key ingredients and mechanisms of TCM in treating complex diseases. Intracerebral Hemorrhage (ICH) is one of the leading causes of death in China, with the characteristics of high mortality and disability rate. Bring a significant burden on people and society. An increasing number of studies have shown that Chinese medicine prescriptions have good advantages in the treatment of ICH, and Ditan Decoction (DTT) is one of the commonly used prescriptions in the treatment of ICH. Modern pharmacological studies have shown that DTT may play a therapeutic role in treating ICH by inhibiting brain inflammation, abnormal oxidative stress reaction and reducing neurological damage, but the specific key ingredients and mechanism are still unclear. METHODS: To solve this problem, we established PPI network based on the latest pathogenic gene data of ICH, and CT network based on ingredient and target data of DTT. Subsequently, we established optimization space based on PPI network and CT network, and constructed a new model for node importance calculation, and proposed a calculation method for PES score, thus calculating the functional core ingredients group (FCIG). These core functional groups may represent DTT therapy for ICH. RESULTS: Based on the strategy, 44 ingredients were predicted as FCIG, results showed that 80.44% of the FCIG targets enriched pathways were coincided with the enriched pathways of pathogenic genes. Both the literature and molecular docking results confirm the therapeutic effect of FCIG on ICH via targeting MAPK signaling pathway and PI3K-Akt signaling pathway. CONCLUSIONS: The FCIG obtained by our network pharmacology method can represent the effect of DTT in treating ICH. These results confirmed that our strategy of active ingredient group optimization and the mechanism inference could provide methodological reference for optimization and secondary development of TCM.

Linking downstream river water quality to urbanization signatures in subtropical climate.

Urbanization has several hydro-ecological effects on receiving waters. Hence, understanding how urbanization influences river water quality is essential for proper river management. However, an inappropriate approach that correlates urbanization signatures with water quality may result in spurious correlations. This study aimed to investigate the relationship of urbanization signatures with two key pollutants of stream flows: nutrients and pathogens. In contrast to the commonly used approaches that are based on economic or demographic metrics, our approach represents urbanization signatures using related anthropogenic activities and evaluates the effect of such activities on water quality parameters. The approach was also applied to evaluate the impacts of urbanization on nutrient and pathogen trends in the river waters of Hong Kong. The data were collected for the period of 1986-2020 from the Environmental Protection Department and monthly measurements were performed. Total nitrogen (TN), total phosphorus (TP), Escherichia. coli (E. coli), and fecal coliforms (FC) showed consistently decreasing trends. However, the long-term seasonality of nutrients differed from that of pathogens. TP and TN exhibited homogenous seasonality with an approximately sinusoidal relationship from January to December, whereas the seasonality of pathogens was more complex and not dependent on river flow dilution effects. Additionally, urbanization impacts on station nutrients and pathogen characteristics were found to be unevenly distributed; under high water temperatures, nutrient concentrations were found to be decreased because of the rainfall dilution effect on river flows. Both urban point and diffuse sources of pollution significantly contributed to nutrient pollution in rivers. Furthermore, the concentrations of FC were not highly influenced by suspended solids, and dissolved oxygen was negatively correlated with all pathogens. Furthermore, the river flow rate was found to improve the water quality in terms of both nutrients and pathogens; urban point source pollution and river temperature alteration were shown to mainly contribute to seasonal variations in both nutrients and pathogens.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling.

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

A global bibliometric and visualized analysis of the links between the autophagy and acute myeloid leukemia.

Background and objectives: Autophagy is a cellular process where damaged organelles or unwanted proteins are packaged into a double-membrane structure and transported to lysosomes for degradation. Autophagy plays a regulatory role in various hematologic malignancies, including acute myeloid leukemia (AML). However, there are few bibliometric studies on the role of autophagy in AML. The purpose of this study is to clarify the role of autophagy in acute myeloid leukemia through bibliometric analysis. Methods: The literature on autophagy and AML research from 2003 to 2023 was searched in Web of Science Core Collection, and bibliometric tools such as VOSviewer 1.6.18, Cite Space (6.1.R3), RStudio (R package bibliometrix), and Scimago Graphica were used to understand the current status and hotspots of autophagy and AML research. The study conducted an analysis of various dimensions including the quantity of publications, countries, institutions, journals, authors, co-references, keywords, and to predict future development trends in this field by drawing relevant visualization maps. Results: A total of 343 articles were obtained, published in 169 journals, written by 2,323 authors from 295 institutions in 43 countries. The journals with the most publications were Blood and Oncotarget. China had the most publications, and Chongqing Medical University and Sun Yat-sen University had the most publications. The author with the highest number of publications was Tschan, Mario P. The main types of research included clinical research, in vitro experiments, in vivo experiments, public database information, and reviews, and the forms of therapeutic effects mainly focused on genetic regulation, traditional Chinese medicine combination, autophagy inhibitors, and drug targets. The research hotspots of autophagy and AML in the past 17 years have focused on genetic regulation, autophagy inhibition, and targeted drugs. Chemotherapy resistance and mitochondrial autophagy will be the forefront of research. Conclusion: The gradual increase in the literature on autophagy and AML research and the decline after 2022 could be a result of authors focusing more on the type of research and the quality of the literature. The current research hotspots are mainly genetic regulation, autophagy inhibition, and autophagy-related targeted drugs. In future, autophagy will remain the focus of the AML field, with research trends likely to focus more on AML chemotherapy resistance and mitochondrial autophagy.

Natural Carotenoids as Neuroprotective Agents for Alzheimer's Disease: An Evidence-Based Comprehensive Review.

Alzheimer's disease (AD) is a neurodegenerative disorder of an ever-increasing aging population with various pathological features such as ß-amyloid (Aß) aggregation, oxidative stress, an impaired cholinergic system, and neuroinflammation. Several therapeutic drugs have been introduced to slow the progression of AD by targeting the above-mentioned pathways. In addition, emerging evidence suggests that naturally occurring compounds have the potential to serve as adjuvant therapies to alleviate AD symptoms. Carotenoids, a group of natural pigments with antioxidative and anti-inflammatory properties, are proposed to be implicated in neuroprotection. To obtain a comprehensive picture of the effect of carotenoids on AD prevention and development, we critically reviewed and discussed recent evidence from in silico, in vitro, in vivo, and human studies in databases including PubMed, Web of Science, Google Scholar, and Cochrane (CENTRAL). After analyzing the existing evidence, we found that high-quality randomized controlled trials (RCTs) are lacking to explore the neuroprotective role of carotenoids in AD pathogenesis and symptoms, especially carotenoids with solid preclinical evidence such as astaxanthin, fucoxanthin, macular carotenoids, and crocin, in order to develop effective preventive dietary supplements for AD patients to ameliorate the symptoms. This review points out directions for future studies to advance the knowledge in this field.

The landscape of potential health benefits of carotenoids as natural supportive therapeutics in protecting against Coronavirus infection.

The Coronavirus Disease-2019 (COVID-19) pandemic urges researching possibilities for prevention and management of the effects of the virus. Carotenoids are natural phytochemicals of anti-oxidant, anti-inflammatory and immunomodulatory properties and may exert potential in aiding in combatting the pandemic. This review presents the direct and indirect evidence of the health benefits of carotenoids and derivatives based on in vitro and in vivo studies, human clinical trials and epidemiological studies and proposes possible mechanisms of action via which carotenoids may have the capacity to protect against COVID-19 effects. The current evidence provides a rationale for considering carotenoids as natural supportive nutrients via antioxidant activities, including scavenging lipid-soluble radicals, reducing hypoxia-associated superoxide by activating antioxidant enzymes, or suppressing enzymes that produce reactive oxygen species (ROS). Carotenoids may regulate COVID-19 induced over-production of pro-inflammatory cytokines, chemokines, pro-inflammatory enzymes and adhesion molecules by nuclear factor kappa B (NF-κB), renin-angiotensin-aldosterone system (RAS) and interleukins-6- Janus kinase-signal transducer and activator of transcription (IL-6-JAK/STAT) pathways and suppress the polarization of pro-inflammatory M1 macrophage. Moreover, carotenoids may modulate the peroxisome proliferator-activated receptors γ by acting as agonists to alleviate COVID-19 symptoms. They also may potentially block the cellular receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human angiotensin-converting enzyme 2 (ACE2). These activities may reduce the severity of COVID-19 and flu-like diseases. Thus, carotenoid supplementation may aid in combatting the pandemic, as well as seasonal flu. However, further in vitro, in vivo and in particular long-term clinical trials in COVID-19 patients are needed to evaluate this hypothesis.

ReDisX, a machine learning approach, rationalizes rheumatoid arthritis and coronary artery disease patients uniquely upon identifying subpopulation differentiation markers from their genomic data.

Diseases originate at the molecular-genetic layer, manifest through altered biochemical homeostasis, and develop symptoms later. Hence, symptomatic diagnosis is inadequate to explain the underlying molecular-genetic abnormality and individual genomic disparities. The current trends include molecular-genetic information relying on algorithms to recognize the disease subtypes through gene expressions. Despite their disposition toward disease-specific heterogeneity and cross-disease homogeneity, a gap still exists in describing the extent of homogeneity within the heterogeneous subpopulation of different diseases. They are limited to obtaining the holistic sense of the whole genome-based diagnosis resulting in inaccurate diagnosis and subsequent management. Addressing those ambiguities, our proposed framework, ReDisX, introduces a unique classification system for the patients based on their genomic signatures. In this study, it is a scalable machine learning algorithm deployed to re-categorize the patients with rheumatoid arthritis and coronary artery disease. It reveals heterogeneous subpopulations within a disease and homogenous subpopulations across different diseases. Besides, it identifies granzyme B (GZMB) as a subpopulation-differentiation marker that plausibly serves as a prominent indicator for GZMB-targeted drug repurposing. The ReDisX framework offers a novel strategy to redefine disease diagnosis through characterizing personalized genomic signatures. It may rejuvenate the landscape of precision and personalized diagnosis and a clue to drug repurposing.

Vitamin a supplementation during pregnancy in shaping child growth outcomes: A meta-analysis.

Abnormal fetal growth increases risks of childhood health complications. Vitamin A supplementation (VAS) is highly accessible, but literature inconsistency regarding effects of maternal VAS on fetal and childhood growth outcomes exists, deterring pregnant women from VAS during pregnancy. This meta-analysis aimed to analyze effects of vitamin A only or vitamin A + co-intervention during pregnancy in healthy mothers (MH) or with complications (MC, night blindness and HIV positive) on perinatal growth outcomes, also assess VAS dose impacts. The Cochrane Library, PubMed, ScienceDirect, Scopus, Embase and Web of Science databases were searched from inception to July 15, 2021. We covered subgroup analyses, including VAS in MH or MC within randomized controlled trial (RCT) or observational studies (OS). Fifty-five studies were included in this meta-analysis (426,098 pregnancies). Vitamin A decreased risk of preterm birth by 9% in MH-RCT (P < 0.001), by 62% in MH-OS (P = 0.029), by 10% in MC-RCT (P = 0.089); decreased LBW by 24% in MC-RCT (P = 0.032); increased neonatal weight in MC-RCT (SMD 0.96; P = 0.051). Besides, vitamin A + co-intervention decreased risks of preterm by 18% in MH-OS (P = 0.021); LBW by 25% in MH-OS (P < 0.001); by 32% in MC-RCT (P = 0.006); decreased neonatal defects by 33% in MH-OS (P = 0.064); decreased anemia by 25% in MH-OS (P = 0.0003); increased neonatal weight in MH-OS (SMD 0.51; P = 0.014); and increased neonatal length in MH-OS (SMD 1.83; P = 0.013). Meta-regression of VAS dose with individual outcomes was not significant, and no side effects were observed for VAS doses up to 4000 mcg (RAE/d). Regardless of maternal health conditions, VAS during pregnancy can safely and effectively improve fetal development and neonatal health even in mothers without VAD.

Uncovering the potential mechanism of Xue Fu Zhu Yu Decoction in the treatment of intracerebral hemorrhage.

BACKGROUND: Chinese herbal medicine (CHM) is characterized by "multi- compounds, multi-targets and multi-pathway", which has advanced benefits for preventing and treating complex diseases, but there still exists unsolved issues, mainly include unclear material basis and underlying mechanism of prescription. Integrated pharmacology is a hot cross research area based on system biology, mathematics and poly-pharmacology. It can systematically and comprehensively investigate the therapeutic reaction of compounds or drugs on pathogenic genes network, and is especially suitable for the study of complex CHM systems. Intracerebral Hemorrhage (ICH) is one of the main causes of death among Chinese residents, which is characterized with high mortality and high disability rate. In recent years, the treatment of ICH by CHM has been deeply researched. Xue Fu Zhu Yu Decoction (XFZYD), one of the commonly used prescriptions in treating ICH at clinic level, has not been clear about its mechanism. METHODS: Here, we established a strategy, which based on compounds-targets, pathogenetic genes, network analysis and node importance calculation. Using this strategy, the core compounds group (CCG) of XFZYD was predicted and validated by in vitro experiments. The molecular mechanism of XFZYD in treating ICH was deduced based on CCG and their targets. RESULTS: The results show that the CCG with 43 compounds predicted by this model is highly consistent with the corresponding Compound-Target (C-T) network in terms of gene coverage, enriched pathway coverage and accumulated contribution of key nodes at 89.49%, 88.72% and 90.11%, respectively, which confirmed the reliability and accuracy of the effective compound group optimization and mechanism speculation strategy proposed by us. CONCLUSIONS: Our strategy of optimizing the effective compound groups and inferring the mechanism provides a strategic reference for explaining the optimization and inferring the molecular mechanism of prescriptions in treating complex diseases of CHM.

Wuzi Yanzong pill attenuates MPTP-induced Parkinson's Disease via PI3K/Akt signaling pathway.

Wuzi Yanzong Pill (WYP) was found to play a protective role on nerve cells and neurological diseases, however the molecular mechanism is unclear. To understand the molecular mechanisms that underly the neuroprotective effect of WYP on dopaminergic neurons in Parkinson's disease (PD). PD mouse model was induced by the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Gait and hanging tests were used to assess motor behavioral function. Immunofluorescence assay was used to determine TH-positive neurons in substantia nigra (SN). Apoptosis, dopamine and neurotrophic factors as well as expression of PI3K/Akt pathway were detected by TUNEL staining, ELISA and western blotting, respectively. First, it was observed that WYP intervention improved abnormal motor function in MPTP-induced PD model, alleviated the loss of TH+ neurons in SN, and increased dopamine content in brain, revealing a potential protective effect. Second, network pharmacology was used to analyze the possible targets and pathways of WYP action in the treatment of PD. A total of 126 active components related to PD were screened in WYP, and the related core targets included ALB, GAPDH, Akt1, TP53, IL6 and TNF. Particularly, the effect of WYP on PD may be medicate through PI3K/Akt signaling pathway and apoptotic regulation. The WYP treated PD mice had higher expression of p-PI3K, p-Akt and Bcl-2 but lower expression of Bax and cleaved caspase-3 than the non-WYP treated PD mice. Secretion of brain-derived neurotrophic factor (BDNF) and cerebral dopamine neurotrophic factor (CDNF) were also increased in the treated mice. WYP may inhibit apoptosis and increase the secretion of neurotrophic factor via activating PI3K/ Akt signaling pathway, thus protecting the loss of dopamine neurons in MPTP-induced PD mice.

Case series: 3D printed orthopedic brace combined with traditional manipulative physiotherapy to treat new-onset scoliosis in adults.

INTRODUCTION: New-onset scoliosis in adults is different from that in congenital and idiopathic scoliosis. We applied personalized custom 3D printed orthopedic braces combined with traditional manipulative physiotherapy to treat adult patients with new-onset scoliosis and observed the effectiveness of the treatment. PATIENT CONCERNS: Nine patients aged 20-52 years presented with unequal height of hips and asymmetrical waist. One shoulder was obviously protruding or enlarged compared to the other; when lying on the bed, the legs were not equal in length, and when bending down, the back was not equal on the left and right. DIAGNOSIS: New-onset scoliosis. INTERVENTIONS: Application of individual customized 3D printing brace combined with traditional treatment. Evaluation of clinical efficacy after treatment, including functional exercise test (FMS) before and after treatment, ability of daily living (ADL), visual analog pain score (VAS), and scoliosis angle (Cobb angle). OUTCOMES: The total effective treatment rate was 100.00% (9/9). The VAS score, Cobb angle of the spine, FMS test, and ADL test were significantly improved compared with those before treatment. CONCLUSION: The customized 3D printed orthopedic brace combined with traditional techniques to treat scoliosis and innovatively combined human bionic technology with traditional medicine to achieve the continuity and precise correction of scoliosis treatment is a clinically effective technique.

UPLC-QQQ-MS/MS-based widely targeted metabolomic analysis reveals the effect of solid-state fermentation with Eurotium cristatum on the dynamic changes in the metabolite profile of dark tea.

Eurotium cristatum is the predominant fungus and key contributor to the characteristics of post-fermented Fu brick tea (FBT) during manufacturing. In this study, the influence of solid-state fermentation (SSF) with E. cristatum on the chemical profile dynamic changes of dark tea was investigated. Results indicated that total phenolics, flavonoids, theaflavins, thearubigins, and galloyl catechins consistently decreased, degalloyl catechins and gallic acid increased in the initial stage of fermentation and decreased after long-term fermentation, and theabrownins continually increased. UPLC-QQQ-MS/MS-based widely targeted metabolomic analysis revealed that the metabolites of dark tea processed by SSF with E. cristatum were drastically different from the raw material. A total of 574 differential metabolites covering 11 subclasses were detected in the whole SSF of dark tea, and the most drastic changes occurred in the middle stage. Phenolic acids and flavonoids were the two major classes of differential metabolites. A series of reactions such as degradation, glycosylation, deglycosylation, methylation, and oxidative polymerization occurred during SSF. Overall, SSF with E. cristatum greatly influenced the metabolites of dark tea, which provided valuable insights that E. cristatum is critical in forming the chemical constituents of FBT.

Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.

OBJECTIVES: Because radiotherapy is indispensible for treating cervical cancer, it is critical to accurately and efficiently delineate the radiation targets. We evaluated a deep learning (DL)-based auto-segmentation algorithm for automatic contouring of clinical target volumes (CTVs) in cervical cancers. METHODS: Computed tomography (CT) datasets from 535 cervical cancers treated with definitive or postoperative radiotherapy were collected. A DL tool based on VB-Net was developed to delineate CTVs of the pelvic lymph drainage area (dCTV1) and parametrial area (dCTV2) in the definitive radiotherapy group. The training/validation/test number is 157/20/23. CTV of the pelvic lymph drainage area (pCTV1) was delineated in the postoperative radiotherapy group. The training/validation/test number is 272/30/33. Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance (HD) were used to evaluate the contouring accuracy. Contouring times were recorded for efficiency comparison. RESULTS: The mean DSC, MSD, and HD values for our DL-based tool were 0.88/1.32 mm/21.60 mm for dCTV1, 0.70/2.42 mm/22.44 mm for dCTV2, and 0.86/1.15 mm/20.78 mm for pCTV1. Only minor modifications were needed for 63.5% of auto-segmentations to meet the clinical requirements. The contouring accuracy of the DL-based tool was comparable to that of senior radiation oncologists and was superior to that of junior/intermediate radiation oncologists. Additionally, DL assistance improved the performance of junior radiation oncologists for dCTV2 and pCTV1 contouring (mean DSC increases: 0.20 for dCTV2, 0.03 for pCTV1; mean contouring time decrease: 9.8 min for dCTV2, 28.9 min for pCTV1). CONCLUSIONS: DL-based auto-segmentation improves CTV contouring accuracy, reduces contouring time, and improves clinical efficiency for treating cervical cancer.

Visual analysis of research hotspots and trends in the treatment of immune thrombocytopenia with traditional Chinese medicine / 数字中医药（英文）

@#Objective Through bibliometrics and visual analysis of the related studies on traditional Chinese medicine (TCM) treatment of immune thrombocytopenia (ITP), this study aims to sort out the overall research progress, hotspots, and trends in this field, and provide reference for further research in ITP. Methods The articles on ITP treated by TCM were retrieved from China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), Web of Science Core Collection (WOSCC), and PubMed. The retrieval time was from the establishment of the databases to July 31, 2022. VOSviewer, CiteSpace, Carrot2, and NoteExpress were used for data analysis of the articles in terms of their quantities, types, and journals, and for visualization of research hotspots, authors, institutions, and keywords. Results 1 493 Chinese articles and 40 English articles were included. The articles in Chinese mainly focus on clinical trial research and clinical experience summary, while the English articles mainly focus on clinical trial research and animal research. The Chinese articles were published in 317 Chinese journals, while English articles were published in 29 English journals. Research hotspots include the clinical syndrome differentiation of ITP, the therapeutic effect of TCM compounds on ITP, and the mechanism of ITP treatment. Keyword analysis shows that there are many research achievements in integrated traditional Chinese and western medicine treatment, clinical research, famous doctors’ experience, TCM treatment, cellular immunity, and humoral immunity. The authors with the most articles in Chinese and English are Professor CHEN Xinyi and Professor MA Rou, respectively, and the research institutions with the most articles are Dongzhimen Hospital of Beijing University of Chinese Medicine and Xiyuan Hospital of China Academy of Chinese Medical Sciences. Chinese herbs often used to treat ITP clinically include Xianhecao (Agrimoniae Herba), Nvzhenzi (Ligustri Lucidi Fructus), Mohanlian (Ecliptae Herba), Zhongjiefeng (Sarcandrae Herba), etc., and the prescription usually used to treat ITP include Guipi Decoction (归脾汤), Xijiao Dihuang Decoction (犀角地黄汤), Bazhen Decoction (八珍汤), Erzhi Pill (二至丸), and Xiaochaihu Decoction (小柴胡汤). The main development trends toward retrospective study, TCM treatment mechanism, and data mining. Conclusion The research on TCM treatment of ITP has progressed steadily, but in-depth studies and close cooperation between research institutions are necessary for the modernization of TCM in treating ITP.

Branched-Chain Amino Acids Catabolism Pathway Regulation Plays a Critical Role in the Improvement of Leukopenia Induced by Cyclophosphamide in 4T1 Tumor-Bearing Mice Treated With Lvjiaobuxue Granule.

Background: Cyclophosphamide is a common tumor chemotherapy drug used to treat various cancers. However, the resulting immunosuppression leads to leukopenia, which is a serious limiting factor in clinical application. Therefore, the introduction of immunomodulators as adjuvant therapy may help to reduce the hematological side effects of cyclophosphamide. Lvjiaobuxue granule has been widely used in the clinical treatment of gynecological diseases such as anemia and irregular menstruation. Recently, it has been found to increase the function of white blood cells, but its mechanism of action is still unclear. We aimed to reveal the mechanisms of Lvjiaobuxue granule against acute leukopenia by an integrated strategy combining metabolomics with network pharmacology. Methods: Subcutaneously inoculated 4T1 breast cancer cells to prepare tumor-bearing mice, intraperitoneal injection of cyclophosphamide to establish a 4T1 tumor-bearing mice leukopenia animal model, using pharmacodynamic indicators, metabolomics, network pharmacology and molecular biology and other technical methods. To comprehensively and systematically elucidate the effect and mechanism of Lvjiaobuxue granule in improving cyclophosphamide-induced leukopenia in 4T1 tumor-bearing mice. Results: Lvjiaobuxue granule can improve the blood routine parameters and organ index levels of the leukopenia model of 4T1 tumor-bearing mice. Metabolomics studies revealed that 15 endogenous metabolites in the spleen of mice were considered as potential biomarkers of Lvjiaobuxue granule for their protective effect. Metabonomics and network pharmacology integrated analysis indicated that Lvjiaobuxue granule exerted the leukocyte elevation activity by inhibiting the branched-chain amino acids (BCAAs) degradation pathway and increasing the levels of valine, leucine and isoleucine. The results of molecular biology also showed that Lvjiaobuxue granule can significantly regulate the key enzymes in the catabolism of BCAAs, which further illustrates the importance of BCAAs in improving leukopenia. Conclusion: Lvjiaobuxue granule exerts obvious pharmacological effects on the leukopenia model of 4T1 tumor-bearing mice induced by cyclophosphamide, which could be mediated by regulating the branched-chain amino acid degradation pathway and the levels of valine, leucine and isoleucine.

Systems biology analysis of the effect and mechanism of total flavonoids of Astragali Radix against cyclophosphamide-induced leucopenia in mice.

This study aimed to demonstrate the pharmacological mechanism of total flavonoids extracted from Astragali Radix (AR) on cyclophosphamide (Cy)-induced leucopenia in mice. First, flow cytometry, network pharmacology and plasma metabolomics were integrated to investigate the pharmacological mechanism of total flavonoids, the targets from network pharmacology and metabolites from metabolomics were analyzed by DAVID. Then, the key cytokines were validated to confirm the predicted metabolic pathway results. The results showed that total flavonoids significantly increased body weight, routine blood indices, bone marrow DNA cells, and also markedly caused lymphocyte proliferation by increasing the percentages of CD4+ and CD8+. Using network pharmacology and metabolomics methods, the study identified 13 signal-related pathways regulated by total flavonoids including PI3K-Akt signaling pathway, Jak-STAT signaling pathway, Sphingolipid signaling pathway, and so on. Total flavonoids also reversed changes in serum cytokines IL-2, IL-6, and GM-CSF. Total flavonoids exhibits protective effects against leucopenia probably by modulating immunologic functions, promoting cell proliferation, and regulating related metabolic pathways at the system level.

Comprehensive Analysis Strategy of Nervous-Endocrine-Immune-Related Metabolites to Evaluate Arachidonic Acid as a Novel Diagnostic Biomarker in Depression.

Depression is one of the most complex multifactorial diseases affected by genetic and environmental factors. The molecular mechanism underlying depression remains largely unclear. To address this issue, a novel nervous-endocrine-immune (NEI) network module was used to find the metabolites and evaluate the diagnostic ability of patients with depression. During this process, metabolites were acquired from a professional depression metabolism database. Over-representation analysis was performed using IMPaLA. Then, the metabolite-metabolite interaction (MMI) network of the NEI system was used to select key metabolites. Finally, the receiver operating characteristic curve analysis was evaluated for the diagnostic ability of arachidonic acid. The results show that the numbers of the nervous system, endocrine system, and immune system pathways are 10, 19, and 12 and the numbers of metabolites are 38, 52, and 13, respectively. The selected shared metabolite-enriched pathways can be 97.56% of the NEI-related pathways. Arachidonic acid was extracted from the NEI system network by using an optimization formula and validated by in vivo experiments. It was indicated that the proposed model was good at screening arachidonic acid for the diagnosis of depression. This method provides reliable evidences and references for the diagnosis and mechanism research of other related diseases.

A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.

Complex disease is a cascade process which is associated with functional abnormalities in multiple proteins and protein-protein interaction (PPI) networks. One drug one target has not been able to perfectly intervene complex diseases. Increasing evidences show that Chinese herb formula usually treats complex diseases in the form of multi-components and multi-targets. The key step to elucidate the underlying mechanism of formula in traditional Chinese medicine (TCM) is to optimize and capture the important components in the formula. At present, there are several formula optimization models based on network pharmacology has been proposed. Most of these models focus on the 2D/3D similarity of chemical structure of drug components and ignore the functional optimization space based on relationship between pathogenetic genes and drug targets. How to select the key group of effective components (KGEC) from the formula of TCM based on the optimal space which link pathogenic genes and drug targets is a bottleneck problem in network pharmacology. To address this issue, we designed a novel network pharmacological model, which takes Lang Chuang Wan (LCW) treatment of systemic lupus erythematosus (SLE) as the case. We used the weighted gene regulatory network and active components targets network to construct disease-targets-components network, after filtering through the network attribute degree, the optimization space and effective proteins were obtained. And then the KGEC was selected by using contribution index (CI) model based on knapsack algorithm. The results show that the enriched pathways of effective proteins we selected can cover 96% of the pathogenetic genes enriched pathways. After reverse analysis of effective proteins and optimization with CI index model, KGEC with 82 components were obtained, and 105 enriched pathways of KGEC targets were consistent with enriched pathways of pathogenic genes (80.15%). Finally, the key components in KGEC of LCW were evaluated by in vitro experiments. These results indicate that the proposed model with good accuracy in screening the KGEC in the formula of TCM, which provides reference for the optimization and mechanism analysis of the formula in TCM.

Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model.

Traditional Chinese medicine (TCM) with the characteristics of "multi-component-multi-target-multi-pathway" has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of "treating the same disease with different treatments". However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by in vitro experiments. Our proposed KNMS prediction and validation strategy provides methodological reference for interpreting the optimization of core components group and inference of molecular mechanism of formula in the treatment of complex diseases in TCM.