Effects of polypropylene microplastics on digestion performance, microbial community, and antibiotic resistance during microbial anaerobic digestion.

As an emerging pollutant, microplastics (MPs) have attracted increasing attention worldwide. The effects of polypropylene (PP) MPs on digestion performance, behaviors of dominant microbial communities, antibiotic resistance genes (ARGs) and mobile genetic elements in microbial anaerobic digesters were investigated. The results showed that the addition of PP-MPs to digesters led to an increase in methane production of 10.8% when 300 particles/g TSS of PP-MPs was introduced compared with that in digester not treated with PP-MPs. This increase was attributed to the enrichment of acetogens such as Syntrophobacter (42.0%), Syntrophorhabdus (27.0%), and Syntrophomonas (10.6%), and methanogens including Methanobacterium and Methanosaeta. tetX was highly enriched due to PP-MP exposure, whereas parC exhibited the greatest increase (35.5% - 222.7%). Horizontal gene transfer via ISCR1 and intI1 genes might play an important role in the spread of ARGs. Overall, these findings provide comprehensive insight into the ecological dynamics of PP-MPs during microbial anaerobic digestion.

Convergent functional change of frontoparietal network in obsessive-compulsive disorder: a voxel-based meta-analysis.

Background: Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness with complex clinical manifestations. Cognitive dysfunction may underlie OC symptoms. The frontoparietal network (FPN) is a key region involved in cognitive control. However, the findings of impaired FPN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the FPN in OCD. Methods: PubMed, Web of Science, Scopus, and EBSCOhost were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies exploring dysfunction in the FPN of OCD patients using three indicators: the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo) and functional connectivity (FC). We compared all patients with OCD and control group in a primary analysis, and divided the studies by medication in secondary meta-analyses with the activation likelihood estimation (ALE) algorithm. Results: A total of 31 eligible studies with 1359 OCD patients (756 men) and 1360 healthy controls (733 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of FPN, mainly in the left dorsolateral prefrontal cortex (DLPFC, BA9), left inferior frontal gyrus (IFG, BA47), left superior temporal gyrus (STG, BA38), right posterior cingulate cortex (PCC, BA29), right inferior parietal lobule (IPL, BA40) and bilateral caudate. Additionally, altered connectivity within- and between-FPN were observed in the bilateral DLPFC, right cingulate gyrus and right thalamus. The secondary analyses showed improved convergence relative to the primary analysis. Conclusion: OCD patients showed dysfunction FPN, including impaired local important nodal brain regions and hypoconnectivity within the FPN (mainly in the bilateral DLPFC), during the resting state. Moreover, FPN appears to interact with the salience network (SN) and default mode network (DMN) through pivotal brain regions. Consistent with the hypothesis of fronto-striatal circuit dysfunction, especially in the dorsal cognitive circuit, these findings provide strong evidence for integrating two pathophysiological models of OCD.

Small molecule agents against alopecia: Potential targets and related pathways.

Alopecia has emerged as a global concern, extending beyond the middle-aged and elderly population and increasingly affecting younger individuals. Despite its growing prevalence, the treatment options and effective drugs for alopecia remain limited due to the incomplete understanding of its underlying mechanisms. Therefore, it is urgent to explore the pathogenesis of alopecia and discover novel and safer therapeutic agents. This review provided an overview of the prevailing clinical disorders of alopecia, and the key pathways and targets involved in hair growth process. Additionally, it discusses FDA-approved drugs and clinical candidates for the treatment of alopecia, and explores small molecule compounds with anti-alopecia potential in the drug discovery phase. These endeavors are expected to provide researchers with valuable scientific insights and practical information for anti-alopecia drug discovery.

Screening the Protective Agents Able to Improve the Survival of Lactic Acid Bacteria Strains Subjected to Spray Drying Using Several Key Enzymes Responsible for Carbohydrate Utilization.

The aim of this study was to identify the most effective protectants for enhancing the viability of specific lactic acid bacteria (LAB) strains (Lactobacillus delbrueckii subsp. bulgaricus CICC 6097, Lactiplantibacillus plantarum CICC 21839, Lactobacillus acidophilus NCFM) by assessing their enzymatic activity when exposed to spray drying (inlet/outlet temperature: 135 °C/90 °C). Firstly, it was found that the live cell counts of the selected LAB cells from the 10% (w/v) recovered skim milk (RSM) group remained above 107 CFU/g after spray drying. Among all the three groups (1% w/v RSM group, 10% w/v RSM group, and control group), the two enzymes pyruvate kinase (PK) and lactate dehydrogenase (LDH) were more sensitive to spray drying than hexokinase (HK) and ß-galactosidase (ß-GAL). Next, transcriptome data of Lb. acidophilus NCFM showed that 10% (w/v) RSM improved the down-regulated expressions of genes encoding PK (pyk) and LDH (ldh) after spray drying compared to 1% (w/v) RSM. Finally, four composite protectants were created, each consisting of 10% (w/v) RSM plus a different additive-sodium glutamate (CP-A group), sucrose (CP-B group), trehalose (CP-C group), or a combination of sodium glutamate, sucrose, and trehalose (CP-D group)-to encapsulate Lb. acidophilus NCFM. It was observed that the viable counts of strain NCFM (8.56 log CFU/g) and enzymatic activity of PK and LDH in the CP-D group were best preserved compared to the other three groups. Therefore, our study suggested that measuring the LDH and PK activity could be used as a promising tool to screen the effective spray-dried protective agent for LAB cells.

Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.

Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and synthesizability of the generated molecules present critical challenges for the successful application of AI technology. Therefore, we developed an advanced reinforcement learning model to bridge the gap between the theory of de novo molecular generation and the practical aspects of drug discovery. This model utilizes chemical reaction templates and commercially available building blocks as a starting point and employs forward reaction prediction to generate molecules, while real-time docking and drug-likeness predictions are conducted to ensure synthesizability and drug-likeness. We applied this model to design active molecules targeting the inflammation-related receptor CXCR4 and successfully prepared them according to the AI-proposed synthetic routes. Several molecules exhibited potent anti-CXCR4 and anti-inflammatory activity in subsequent in vitro and in vivo assays. The top-performing compound XVI alleviated symptoms related to inflammatory bowel disease and showed reasonable pharmacokinetic properties.

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis.

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.

Thyroid receptor ß: A promising target for developing novel anti-androgenetic alopecia drugs.

Androgenetic alopecia (AGA) significantly impacts the self-confidence and mental well-being of people. Recent research has revealed that thyroid receptor ß (TRß) agonists can activate hair follicles and effectively stimulate hair growth. This review aims to comprehensively elucidate the specific mechanism of action of TRß in treating AGA from various perspectives, highlighting its potential as a drug target for combating AGA. Moreover, this review provides a thorough summary of the research advances in TRß agonist candidates with anti-AGA efficacy and outlines the structure-activity relationships (SARs) of TRß agonists. We hope that this review will provide practical information for the development of effective anti-alopecia drugs.

Artificial Intelligence-Assisted Optimization of Antipigmentation Tyrosinase Inhibitors: De Novo Molecular Generation Based on a Low Activity Lead Compound.

Artificial intelligence (AI) de novo molecular generation is a highly promising strategy in the drug discovery, with deep reinforcement learning (RL) models emerging as powerful tools. This study introduces a fragment-by-fragment growth RL forward molecular generation and optimization strategy based on a low activity lead compound. This process integrates fragment growth-based reaction templates, while target docking and drug-likeness prediction were simultaneously performed. This comprehensive approach considers molecular similarity, internal diversity, synthesizability, and effectiveness, thereby enhancing the quality and efficiency of molecular generation. Finally, a series of tyrosinase inhibitors were generated and synthesized. Most compounds exhibited more improved activity than lead, with an optimal candidate compound surpassing the effects of kojic acid and demonstrating significant antipigmentation activity in a zebrafish model. Furthermore, metabolic stability studies indicated susceptibility to hepatic metabolism. The proposed AI structural optimization strategies will play a promising role in accelerating the drug discovery and improving traditional efficiency.

A combination of genomics and transcriptomics provides insights into the distribution and differential mRNA expression of type VI secretion system in clinical Klebsiella pneumoniae.

The type VI secretion system (T6SS) serves as a crucial molecular weapon in interbacterial competition and significantly influences the adaptability of bacteria in their ecological niche. However, the distribution and function of T6SS in clinical Klebsiella pneumoniae, a common opportunistic nosocomial pathogen, have not been fully elucidated. Here, we conducted a genomic analysis of 65 clinical K. pneumoniae isolates obtained from patients with varying infections. Genes encoding a T6SS cluster present in all analyzed strains of K. pneumoniae, and strains with identical sequence type carried structurally and numerically identical T6SS. Our study also highlights the importance of selecting conserved regions within essential T6SS genes for PCR-based identification of T6SS in bacteria. Afterward, we utilized the predominant sequence type 11 (ST11) K. pneumoniae HS11286 to investigate the effect of knocking out T6SS marker genes hcp or vgrG. Transcriptome analysis identified a total of 1,298 co-upregulated and 1,752 co-downregulated differentially expressed genes in both mutants. Pathway analysis showed that only Δhcp mutant exhibited alterations in transport, establishment of localization, localization, and cell processes. The absence of hcp or vgrG gene suppressed the expression of other T6SS-related genes within the locus I cluster. Additionally, interbacterial competition experiments showed that hcp and vgrG are essential for competitive ability of ST11 K. pneumoniae HS11286. This study furthers our understanding of the genomic characteristics of T6SS in clinical K. pneumoniae and suggests the involvement of multiple genes in T6SS of strain HS11286. IMPORTANCE: Gram-negative bacteria use type VI secretion system (T6SS) to deliver effectors that interact with neighboring cells for niche advantage. Klebsiella pneumoniae is an opportunistic nosocomial pathogen that often carries multiple T6SS loci, the function of which has not yet been elucidated. We performed a genomic analysis of 65 clinical K. pneumoniae strains isolated from various sources, confirming that all strains contained T6SS. We then used transcriptomics to further study changes in gene expression and its effect on interbacterial competition following the knockout of key T6SS genes in sequence type 11 (ST11) K. pneumoniae HS11286. Our findings revealed the distribution and genomic characteristics of T6SS in clinical K. pneumoniae. This study also described the overall transcriptional changes in the predominant Chinese ST11 strain HS11286 upon deletion of crucial T6SS genes. Additionally, this work provides a reference for future research on the identification of T6SS in bacteria.

Comparison of Disease Severity, Anxiety and Depression in Obsessive-Compulsive Disorder Patients with Different Insight.

BACKGROUND: Significant individual differences exist in the insight of patients with obsessive-compulsive disorder (OCD), and the clinical characteristics of OCD patients with varying levels of insight are not entirely uniform. This study aims to investigate disparities in disease severity, anxiety, and depression status among OCD patients with differing levels of insight, with the goal of generating novel treatment strategies for OCD. METHODS: A total of 114 patients diagnosed with OCD were recruited from the Department of Psychology at Affiliated Mental Health Center & Hangzhou Seventh People's Hospital to participate in this research. Based on their Total Insight and Treatment Attitude Questionnaire (ITAQ) scores, the patients were divided into two groups: Group OCD with high insight (referred to as Group OCD-HI, ITAQ score ≥20 points, n = 80) and Group OCD with low insight (referred to as Group OCD-LI, ITAQ score <20 points, n = 34). Subsequently, the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD) scores were compared between the two groups. All questionnaires for this study were completed by experienced psychiatrists. RESULTS: The Y-BOCS scores for YB1, YB2, YB4, YB5, YB6, YB9, and the total Y-BOCS scores in Group OCD-HI were significantly higher than those in Group OCD-LI (p < 0.05). Conversely, Group OCD-HI exhibited significantly lower HAMA and HAMD scores compared to Group OCD-LI (p < 0.05). Furthermore, the total ITAQ score displayed a significant negative correlation with the total Y-BOCS, HAMA, and HAMD scores (p < 0.05). CONCLUSIONS: This study revealed that certain OCD patients exhibit incomplete insight, and this lack of insight is strongly associated with increased disease severity and heightened levels of anxiety and depression. It is hoped that by enhancing the insight of OCD patients, the goal of ameliorating disease symptoms and alleviating negative emotions can be attained.

Small-molecule agents for treating skin diseases.

Skin diseases are a class of common and frequently occurring diseases that significantly impact daily lives. Currently, the limited effective therapeutic drugs are far from meeting the clinical needs; most drugs typically only provide symptomatic relief rather than a cure. Developing small-molecule drugs with improved efficacy holds paramount importance for treating skin diseases. This review aimed to systematically introduce the pathogenesis of common skin diseases in daily life, list related drugs applied in the clinic, and summarize the clinical research status of candidate drugs and the latest research progress of candidate compounds in the drug discovery stage. Also, it statistically analyzed the number of publications and global attention trends for the involved skin diseases. This review might provide practical information for researchers engaged in dermatological drugs and further increase research attention to this disease area.

The effectiveness of interventions to reduce cancer-related stigma: An integrative review.

AIMS: The clinical significance of cancer-related stigma on patients' well-being has been widely established. Stigma can be perceived and internalised by cancer patients or implemented by the general population and healthcare workers. Various interventions have been carried out to reduce cancer-related stigma, but their effectiveness is not well-understood. This review aims to synthesise evidence on the effectiveness of interventions to reduce cancer-related stigma. DESIGN: An integrative review. METHODS: This integrative review combined both qualitative and quantitative studies and followed five steps to identify problems, search for the literature, appraise the literature quality, analyse data, and present data. Mixed Methods Appraisal Tool (version 2018) was applied to evaluate the quality of the included studies. DATA SOURCES: Databases included Web of Science, MEDLINE, SpringerLink, Wiley Online Journals, Cochrane Library, ScienceDirect, OVID, and China National Knowledge Infrastructure (from the inception of each database to 30 April 2021). RESULTS: Eighteen quantitative, six qualitative, and five mixed-methods studies were included in this review. Cultural factors should be considered when conducting interventions to reduce cancer-related stigma. For cancer patients, multi-component interventions have demonstrated a positive effect on their perceived stigma. For general population, interactive interventions show promise to reduce their implemented stigma towards cancer patients. For healthcare workers, there is a paucity of studies to reduce their implemented stigma. Existing studies reported inconclusive evidence, partially due to the lack of a robust study design with an adequate sample size. CONCLUSIONS: Multi-component and interactive interventions show promise to relieve cancer-related stigma. More methodologically robust studies should be conducted in different cultures to elucidate the most appropriate interventions for different populations to reduce cancer-related stigma. IMPLICATION FOR THE PROFESSION AND PATIENT CARE: These findings will facilitate healthcare workers to design and implement interventions to reduce cancer-related stigma, thus improving the quality of life for cancer patients. PATIENT AND PUBLIC CONTRIBUTION: No patient and public contribution.

Quality Evaluation of Metabolic-Associated Fatty Liver Disease Guidelines and Expert Consensus.

The purpose of this study is to evaluate and analyze the quality of guidelines and expert consensus on clinical practice regarding metabolically associated fatty liver disease (MAFLD) over the past five years. Data from the websites were retrieved using computers. We evaluated guidelines and expert consensus on MAFLD that were officially published between January 1, 2018 and March 24, 2023. Two evaluators independently examined the literature and extracted data. The included literature on guidelines and expert consensus was then subjected to quality review and analysis using assessment tools from Appraisal of Guidelines for Research and Evaluation (AGREE) II and the Joanna Briggs Institute Qualitative Assessment and Review Instrument (JBI-QARI) (2016). The intraclass correlation coefficient (ICC) values of all items on the AGREE II scale for the two evaluators were greater than 0.75, indicating a high degree of agreement between their assessments. Scope and purpose (48.90%), participants (49.21%), rigor in the formulation process (56.97%), clarity of expression (90.08%), applicability (66.08%), and independence of file compiling (60.12%) were the AGREE II scoring items with the standardized average scores. Apart from the participants, the average scores of all the scoring items in the guidelines from other countries other than China were higher than those from China (|Z|+>+2.272, p+<+0.05). MAFLD guidelines must be revised to enhance their methodological quality. When creating guidelines, it is recommended that the formulators strictly adhere to the formulation and drafting standards of AGREE II and elevate the quality of the guidelines.

Type I BREX system defends against antibiotic-resistant plasmids in Escherichia coli.

The Bacteriophage Exclusion (BREX) system is a novel antiphage defense system identified in Bacillus cereus in 2015. The purpose of this study was to investigate the presence of the BREX system defenses against antibiotic-resistant plasmids such as blaKPC and blaNDM invasion in Escherichia coli. The BREX system was present in 5.4% (23/424) of E. coli clinical isolates and 6.5% (84/1283) of E. coli strains with completely sequenced genomes in the GenBank database. All 23 BREX-positive E. coli clinical isolates were susceptible to carbapenems, while all five isolates carrying blaKPC and 11 carrying blaNDM were BREX-negative. For E. coli strains in the GenBank database, 37 of 38 strains carrying blaKPC and 109 of 111 strains carrying blaNDM were BREX negative. The recognition site sequence of methyltransferase PglX in a clinical E. coli 3756 was 5'-CANCATC-3' using PacBio single-molecular real-time sequencing. The transformation efficiency of plasmid psgRNA-ColAori-target with the PglX recognition site was reduced by 100% compared with the plasmid without the recognition site in E. coli DH5α-pHSG398-BREX. The BREX showed lower defense efficacy against plasmid psgRNA-15Aori-target which had the same plasmid backbone but different surrounding sequences of recognition sites with psgRNA-ColAori-target. The conjugation frequency of the KPC-2 plasmid and NDM-5 plasmid in E. coli 3756-ΔBREX was higher than that in E. coli 3756 clinical isolate (1.0 × 10-6 vs 1.3 × 10-7 and 5.5 × 10-7 vs 1.7 × 10-8, respectively). This study demonstrated that the type I BREX system defends against antibiotic-resistant plasmids in E. coli.

CXCR4/CXCL12 axis: "old" pathway as "novel" target for anti-inflammatory drug discovery.

Inflammation is the body's defense response to exogenous or endogenous stimuli, involving complex regulatory mechanisms. Discovering anti-inflammatory drugs with both effectiveness and long-term use safety is still the direction of researchers' efforts. The inflammatory pathway was initially identified to be involved in tumor metastasis and HIV infection. However, research in recent years has proved that the CXC chemokine receptor type 4 (CXCR4)/CXC motif chemokine ligand 12 (CXCL12) axis plays a critical role in the upstream of the inflammatory pathway due to its chemotaxis to inflammatory cells. Blocking the chemotaxis of inflammatory cells by CXCL12 at the inflammatory site may block and alleviate the inflammatory response. Therefore, developing CXCR4 antagonists has become a novel strategy for anti-inflammatory therapy. This review aimed to systematically summarize and analyze the mechanisms of action of the CXCR4/CXCL12 axis in more than 20 inflammatory diseases, highlighting its crucial role in inflammation. Additionally, the anti-inflammatory activities of CXCR4 antagonists were discussed. The findings might help generate new perspectives for developing anti-inflammatory drugs targeting the CXCR4/CXCL12 axis.

Molecular Characteristics and Antimicrobial Susceptibility Profiles of blaKPC-Producing Escherichia Coli Isolated from a Teaching Hospital in Shanghai, China.

Introduction: Carbapenem-Resistant Enterobacteriaceae (CRE) has posed a significant threat to humans.The aim of this study was to investigate the molecular characteristics of blaKPC-producing Escherichia coli in a university-affiliated tertiary hospital. Methods: Polymerase chain reaction (PCR) and BLAST+ software were used to detect the prevalence of blaKPC in E. coli and Klebsiella pneumoniae. Whole-genome sequencing was performed for the blaKPC-harboring clinical E. coli isolates. Antimicrobial resistance genes, MLSTs, KPC-carrying plasmid typing and genetic environment of blaKPC were analyzed. A maximum likelihood core single nucleotide polymorphism (SNP)-based phylogeny tree was constructed to determine the evolutionary relationships within this ST131 collection. Conjugation experiments were performed to determine the mobilization of blaKPC. The minimal inhibitory concentrations of the common antimicrobial agents were determined using the broth microdilution method. Results: The prevalence of blaKPC in 424 clinical E. coli isolates and 1636 E. coli strains from GenBank database were 2.2% (45/2060) whereas the detection rate of blaKPC in K. pneumoniae from the GenBank database was 29.8% (415/1394). The blaKPC-harboring conjugants exhibited resistance to multiple ß-lactams, except for cefepime-zidebactam and ceftazidime-avibactam. All blaKPC-carring E. coli isolates were susceptible to tigecycline and polymyxin B. ST131 was the dominant sequence type of blaKPC-carring E. coli, accounting for 40.0% (18/45). Most of the blaKPC-producing ST131 E. coli (89.5%,17/19) belonged to clade C ST131 lineage. Genetic environment analysis revealed that 57.8% (26/45) of blaKPC gene was linked to Tn4401-associated structure ISKpn6-blaKPC-ISKpn7. IncN was the most common plasmid type in KPC-producing E. coli whereas IncFII was the dominant plasmid type in KPC-producing K. pneumoniae. Conclusion: The detection rate of blaKPC was lower in E. coli compared with K. pneumoniae. The dominant sequence and plasmid types of blaKPC-harboring isolates differed between E. coli and K. pneumoniae. Further studies about the role of the defense system in acquisition of KPC-plasmids in E. coli will be performed to provide new insights into the low prevalence of blaKPC.

Discovery of matrix metalloproteinase inhibitors as anti-skin photoaging agents.

Photodamage is the result of prolonged exposure of the skin to sunlight. This exposure causes an overexpression of matrix metalloproteinases (MMPs), leading to the abnormal degradation of collagen in the skin tissue and resulting in skin aging and damage. This review presents a detailed overview of MMPs as a potential target for addressing skin aging. Specifically, we elucidated the precise mechanisms by which MMP inhibitors exert their anti-photoaging effects. Furthermore, we comprehensively analyzed the current research progress on MMP inhibitors that demonstrate significant inhibitory activity against MMPs and anti-skin photoaging effects. The review also provides insights into the structure-activity relationships of these inhibitors. Our objective in conducting this review is to provide valuable practical information to researchers engaged in investigations on anti-skin photoaging.

The roles of long noncoding RNA NEAT1 in cardiovascular diseases.

The morbidity of cardiovascular diseases (CVDs) gradually increases worldwide. Long noncoding RNAs (lncRNAs) are a large class of non-(protein)-coding RNAs with lengths beyond 200 nucleotides. Increasing evidence suggests that lncRNA NEAT1 plays important roles in the pathogenesis of CVDs, such as myocardial infarction, heart failure, myocardial ischemia-reperfusion (I/R) injury, atherosclerosis, hypertension, cardiomyopathy, and others. We summarized the current studies of NEAT1 in CVDs, which shed light on the understanding of the molecular mechanisms of CVDs and understanding the therapeutic potential of NEAT1.

Elemene Antitumor Drugs Development Based on "Molecular Compatibility Theory" and Clinical Application: A Retrospective and Prospective Outlook.

Elemene, derived from Curcuma wenyujin, one of the "8 famous genuine medicinal materials of Zhejiang province," exhibits remarkable antitumor activity. It has gained wide recognition in clinical practice for effectiveness on tumors. Dr. XIE Tian, introduced the innovative concept of "molecular compatibility theory" by combining Chinese medicine principles, specifically the "monarch, minister, assistant, and envoy" theory, with modern biomedical technology. This groundbreaking approach, along with a systematic analysis of Chinese medicine and modern biomedical knowledge, led to the development of elemene nanoliposome formulations. These novel formulations offer numerous advantages, including low toxicity, well-defined composition, synergistic effects on multiple targets, and excellent biocompatibility. Following the principles of the "molecular compatibility theory", further exploration of cancer treatment strategies and methods based on elemene was undertaken. This comprehensive review consolidates the current understanding of elemene's potential antitumor mechanisms, recent clinical investigations, advancements in drug delivery systems, and structural modifications. The ultimate goal of this review is to establish a solid theoretical foundation for researchers, empowering them to develop more effective antitumor drugs based on the principles of "molecular compatibility theory".