Multimodal smart systems reprogramme macrophages and remove urate to treat gouty arthritis.

Gouty arthritis is a chronic and progressive disease characterized by high urate levels in the joints and by an inflammatory immune microenvironment. Clinical data indicate that urate reduction therapy or anti-inflammatory therapy alone often fails to deliver satisfactory outcomes. Here we have developed a smart biomimetic nanosystem featuring a 'shell' composed of a fusion membrane derived from M2 macrophages and exosomes, which encapsulates liposomes loaded with a combination of uricase, platinum-in-hyaluronan/polydopamine nanozyme and resveratrol. The nanosystem targets inflamed joints and promotes the accumulation of anti-inflammatory macrophages locally, while the uricase and the nanozyme reduce the levels of urate within the joints. Additionally, site-directed near-infrared irradiation provides localized mild thermotherapy through the action of platinum and polydopamine, initiating heat-induced tissue repair. Combined use of these components synergistically enhances overall outcomes, resulting in faster recovery of the damaged joint tissue.

The potential and pitfalls of using a large language model such as ChatGPT, GPT-4, or LLaMA as a clinical assistant.

OBJECTIVES: This study aims to evaluate the utility of large language models (LLMs) in healthcare, focusing on their applications in enhancing patient care through improved diagnostic, decision-making processes, and as ancillary tools for healthcare professionals. MATERIALS AND METHODS: We evaluated ChatGPT, GPT-4, and LLaMA in identifying patients with specific diseases using gold-labeled Electronic Health Records (EHRs) from the MIMIC-III database, covering three prevalent diseases-Chronic Obstructive Pulmonary Disease (COPD), Chronic Kidney Disease (CKD)-along with the rare condition, Primary Biliary Cirrhosis (PBC), and the hard-to-diagnose condition Cancer Cachexia. RESULTS: In patient identification, GPT-4 had near similar or better performance compared to the corresponding disease-specific Machine Learning models (F1-score ≥ 85%) on COPD, CKD, and PBC. GPT-4 excelled in the PBC use case, achieving a 4.23% higher F1-score compared to disease-specific "Traditional Machine Learning" models. ChatGPT and LLaMA3 demonstrated lower performance than GPT-4 across all diseases and almost all metrics. Few-shot prompts also help ChatGPT, GPT-4, and LLaMA3 achieve higher precision and specificity but lower sensitivity and Negative Predictive Value. DISCUSSION: The study highlights the potential and limitations of LLMs in healthcare. Issues with errors, explanatory limitations and ethical concerns like data privacy and model transparency suggest that these models would be supplementary tools in clinical settings. Future studies should improve training datasets and model designs for LLMs to gain better utility in healthcare. CONCLUSION: The study shows that LLMs have the potential to assist clinicians for tasks such as patient identification but false positives and false negatives must be mitigated before LLMs are adequate for real-world clinical assistance.

M2 Macrophage Hybrid Membrane-Camouflaged Targeted Biomimetic Nanosomes to Reprogram Inflammatory Microenvironment for Enhanced Enzyme-Thermo-Immunotherapy.

Excessive inflammatory reactions caused by uric acid deposition are the key factor leading to gout. However, clinical medications cannot simultaneously remove uric acid and eliminate inflammation. An M2 macrophage-erythrocyte hybrid membrane-camouflaged biomimetic nanosized liposome (USM[H]L) is engineered to deliver targeted self-cascading bienzymes and immunomodulators to reprogram the inflammatory microenvironment in gouty rats. The cell-membrane-coating endow nanosomes with good immune escape and lysosomal escape to achieve long circulation time and intracellular retention times. After being uptaken by inflammatory cells, synergistic enzyme-thermo-immunotherapies are achieved: uricase and nanozyme degraded uric acid and hydrogen peroxide, respectively; bienzymes improved the catalytic abilities of each other; nanozyme produced photothermal effects; and methotrexate has immunomodulatory and anti-inflammatory effects. The uric acid levels markedly decrease, and ankle swelling and claw curling are effectively alleviated. The levels of inflammatory cytokines and ROS decrease, while the anti-inflammatory cytokine levels increase. Proinflammatory M1 macrophages are reprogrammed to the anti-inflammatory M2 phenotype. Notably, the IgG and IgM levels in USM[H]L-treated rats decrease substantially, while uricase-treated rats show high immunogenicity. Proteomic analysis show that there are 898 downregulated and 725 upregulated differentially expressed proteins in USM[H]L-treated rats. The protein-protein interaction network indicates that the signaling pathways include the spliceosome, ribosome, purine metabolism, etc.

Nanoemulsions of Hydroxysafflor Yellow A for Enhancing Physicochemical and In Vivo Performance.

Stroke was always a disease that threatened human life and health worldwide. We reported the synthesis of a new type of hyaluronic acid-modified multi-walled carbon nanotube. Then, we produced hydroxysafflor yellow A-hydroxypropyl-ß-cyclodextrin phospholipid complex water-in-oil nanoemulsion with hyaluronic acid-modified multi-walled carbon nanotubes and chitosan (HC@HMC) for oral treatment of an ischemic stroke. We measured the intestinal absorption and pharmacokinetics of HC@HMC in rats. We found that the intestinal absorption and the pharmacokinetic behavior of HC@HMC was superior to that of HYA. We measured intracerebral concentrations after oral administration of HC@HMC and found that more HYA crossed the blood-brain barrier (BBB) in mice. Finally, we evaluated the efficacy of HC@HMC in middle cerebral artery occlusion/reperfusion (MCAO/R)-injured mice. In MCAO/R mice, oral administration of HC@HMC demonstrated significant protection against cerebral ischemia-reperfusion injury (CIRI). Furthermore, we found HC@HMC may exert a protective effect on cerebral ischemia-reperfusion injury through the COX2/PGD2/DPs pathway. These results suggest that oral administration of HC@HMC may be a potential therapeutic strategy for the treatment of stroke.

Curcumin-Loaded Platelet Membrane Bioinspired Chitosan-Modified Liposome for Effective Cancer Therapy.

Cancer is a serious threat to human health, and chemotherapy for cancer is limited by severe side effects. Curcumin (CUR) is a commonly used natural product for antitumor treatment without safety concerns. However, low bioavailability and poor tumor accumulation are great obstacles for its clinical application. Our previous research has demonstrated that platelet membrane-camouflaged nanoparticles can efficiently ameliorate the in vivo kinetic characteristics and enhance the tumor affinity of payloads. Nevertheless, the antitumor efficiency of this formulation still needs to be thoroughly investigated, and its drug release behavior is limited. Herein, CUR-loaded platelet membrane bioinspired chitosan-modified liposome (PCLP-CUR) was constructed to improve CUR release. PCLP-CUR was shown to have long retention time, improved bioavailability, strong tumor targeting capacity and effective cellular uptake. The incorporation of chitosan enabled PCLP-CUR to release cargoes quickly under mild acidic tumor conditions, leading to more complete drug release and favoring subsequent treatment. Both in vitro and in vivo investigations showed that PCLP-CUR could significantly enhance the anticancer efficacy of CUR with minimal side effects through biomimetic membrane and chitosan modification. In summary, this developed delivery system can provide a promising strategy for tumor-targeting therapy and phytochemical delivery.

Effects of Reductive Soil Disinfestation Combined with Liquid-Readily Decomposable Compounds and Solid Plant Residues on the Bacterial Community and Functional Composition.

Reductive soil disinfestation (RSD) incorporated with sole plant residues or liquid-readily decomposable compounds is an effective management strategy to improve soil health. However, the synthetic effects of RSD incorporated with liquid-readily decomposable compounds and solid plant residues on soil ecosystem services remain unclear. Field experiments were carried out to investigate the effects of untreated soil (CK), RSD incorporated with sawdust (SA), molasses (MO), and their combinations (SA + MO) on the bacterial community and functional composition. The results showed that RSD treatments significantly altered soil bacterial community structure compared to CK treatment. The bacterial community structure and composition in MO and SA + MO treatments were clustered compared to SA treatment. This was mainly attributed to the readily decomposable carbon sources in molasses having a stronger driving force to reshape the soil microbial community during the RSD process. Furthermore, the functional compositions, such as the disinfestation efficiency of F. oxysporum (96.4 - 99.1%), abundances of nitrogen functional genes, soil metabolic activity, and functional diversity, were significantly increased in all of the RSD treatments. The highest disinfestation efficiency and abundances of denitrification (nirS and nrfA) and nitrogen fixation (nifH) genes were observed in SA + MO treatment. Specifically, SA + MO treatment enriched more abundant beneficial genera, e.g., Oxobacter, Paenibacillus, Cohnella, Rummeliibacillus, and Streptomyces, which were significantly and positively linked to disinfestation efficiency, soil metabolic activity, and denitrification processes. Our results indicated that combining RSD practices with liquid-readily decomposable compounds and solid plant residues could effectively improve soil microbial community and functional composition.

Clinical utility of automatic phenotype annotation in unstructured clinical notes: intensive care unit use.

OBJECTIVE: Clinical notes contain information that has not been documented elsewhere, including responses to treatment and clinical findings, which are crucial for predicting key outcomes in patients in acute care. In this study, we propose the automatic annotation of phenotypes from clinical notes as a method to capture essential information to predict outcomes in the intensive care unit (ICU). This information is complementary to typically used vital signs and laboratory test results. METHODS: In this study, we developed a novel phenotype annotation model to extract the phenotypical features of patients, which were then used as input features of predictive models to predict ICU patient outcomes. We demonstrated and validated this approach by conducting experiments on three ICU prediction tasks, including in-hospital mortality, physiological decompensation and length of stay (LOS) for over 24 000 patients using the Medical Information Mart for Intensive Care (MIMIC-III) dataset. RESULTS: The predictive models incorporating phenotypical information achieved 0.845 (area under the curve-receiver operating characteristic (AUC-ROC)) for in-hospital mortality, 0.839 (AUC-ROC) for physiological decompensation and 0.430 (kappa) for LOS, all of which consistently outperformed the baseline models using only vital signs and laboratory test results. Moreover, we conducted a thorough interpretability study showing that phenotypes provide valuable insights at both the patient and cohort levels. CONCLUSION: The proposed approach demonstrates that phenotypical information complements traditionally used vital signs and laboratory test results and significantly improves the accuracy of outcome prediction in the ICU.

Phenotyping in clinical text with unsupervised numerical reasoning for patient stratification.

Phenotypic information of patients, as expressed in clinical text, is important in many clinical applications such as identifying patients at risk of hard-to-diagnose conditions. Extracting and inferring some phenotypes from clinical text requires numerical reasoning, for example, a temperature of 102°F suggests the phenotype Fever. However, while current state-of-the-art phenotyping models using natural language processing (NLP) are in general very efficient in extracting phenotypes, they struggle to extract phenotypes that require numerical reasoning. In this article, we propose a novel unsupervised method that leverages external clinical knowledge and contextualized word embeddings by ClinicalBERT for numerical reasoning in different phenotypic contexts. Experiments show that the proposed method achieves significant improvement against unsupervised baseline methods with absolute increase in generalized Recall and F1 scores of up to 79% and 71%, respectively. Also, the proposed method outperforms supervised baseline methods with absolute increase in generalized Recall and F1 scores of up to 70% and 44%, respectively. In addition, we validate the methodology on clinical use cases where the detected phenotypes significantly contribute to patient stratification systems for a set of diseases, namely, HIV and myocardial infarction (heart attack). Moreover, we find that these phenotypes from clinical text can be used to impute the missing values in structured data, which enrich and improve data quality.

Better Bioactivity, Cerebral Metabolism and Pharmacokinetics of Natural Medicine and Its Advanced Version.

Currently, many people are afflicted by cerebral diseases that cause dysfunction in the brain and perturb normal daily life of people. Cerebral diseases are greatly affected by cerebral metabolism, including the anabolism and catabolism of neurotransmitters, hormones, neurotrophic molecules and other brain-specific chemicals. Natural medicines (NMs) have the advantages of low cost and low toxicity. NMs are potential treatments for cerebral diseases due to their ability to regulate cerebral metabolism. However, most NMs have low bioavailability due to their low solubility/permeability. The study is to summarize the better bioactivity, cerebral metabolism and pharmacokinetics of NMs and its advanced version. This study sums up research articles on the NMs to treat brain diseases. NMs affect cerebral metabolism and the related mechanisms are revealed. Nanotechnologies are applied to deliver NMs. Appropriate delivery systems (exosomes, nanoparticles, liposomes, lipid polymer hybrid nanoparticles, nanoemulsions, protein conjugation and nanosuspensions, etc.) provide better pharmacological and pharmacokinetic characteristics of NMs. The structure-based metabolic reactions and enzyme-modulated catalytic reactions related to advanced versions of NMs alter the pharmacological activities of NMs.

Oral supramolecular nanovectors for dual natural medicine codelivery to prevent gastric mucosal lesion.

The oral administration of a single formulation loaded with more than one natural medicine to treat chronic diseases has advantages such as convenience, effectiveness, and economy. Here, using biomaterials approved by the drug administration, we fabricated supramolecular nanovectors containing dual natural medicines to prevent gastric mucosal lesions. Nanovectors exhibited superior intestinal absorption and bioavailability, which might be due to their high dispersion, good muco-adhesiveness, blood-lymph circulation transport, lipid sensing, and protective effects. Molecular docking results clarified the possible mechanisms in aspects of efflux pump (p-glycoprotein and multidrug resistance protein 1) inhibition effects, metabolic enzyme (cytochrome P450 3A4/1A2) blocking effects, serum albumin deposit effects, and dual drug interaction effects. Nanovectors decreased ethanol-induced gastric mucosal lesions by lowering the gastric ulcer index, preventing oxidative damage, decreasing interleukin-6, tumor necrosis factor-α and malondialdehyde, increasing glutathione, superoxide dismutase, and prostaglandin E2 levels. The interactions of inhibitor of nuclear factor-κB or κB kinase-related proteins and dual drugs or nanovector components were simulated computationally to provide an understanding of the gastro-protective action mechanism. In all, industrializable supramolecular nanovectors could effectively co-deliver dual natural medicines via the oral route by improving the pharmacokinetic behavior and exerting protective efficacy of the gastric mucosa by decreasing the oxidative stress and inflammatory level.

Biomimetic lipidic nanovectors for effective asparaginase supramolecule delivery.

Effectiveness of enzyme therapy is limited by enzyme drawbacks such as short half-life, low bioavailability and high immunogenicity. We loaded asparaginase (Aase) into hydroxypropyl- or sulfonbutylether-beta cyclodextrin to form supramolecular amphiphilic molecules by self-assembly followed by entrapment inside the cores of two biomimetic lipidic nanovectors (AS-XLNs). Supramolecular structure was simulated by molecular docking. AS-XLNs maintained superior activity through isolating Aase from external environment due to docking with cyclodextrin and coating with biomimetic membrane. Fluorescent probes and computational simulations were used to reveal possible interactions between serum albumin/trypsin and Aase/nanovector membrane components which were partly responsible for enhanced bioavailability and bioactivity of AS-XLNs compared to Aase. AS-XLNs significantly increased cytotoxicity against pulmonary tumor cells due to synergistic effects of Aase and nanovector membrane components (killing tumor cells through apoptosis induced by asparagine depletion and autophagy inhibition or via targets such as vascular endothelial growth factor A, alpha-amylase, p-selectin or androgen receptor).

Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients.

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein-protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

Bone-targeted erythrocyte-cancer hybrid membrane-camouflaged nanoparticles for enhancing photothermal and hypoxia-activated chemotherapy of bone invasion by OSCC.

BACKGROUND: Jaw bones are the most common organs to be invaded by oral malignancies, such as oral squamous cell carcinoma (OSCC), because of their special anatomical relationship. Various serious complications, such as pathological fractures and bone pain can significantly decrease the quality of life or even survival outcomes for a patient. Although chemotherapy is a promising strategy for bone invasion treatment, its clinical applications are limited by the lack of tumor-specific targeting and poor permeability in bone tissue. Therefore, it is necessary to develop a smart bone and cancer dual targeting drug delivery platform. RESULTS: We designed a dual targeting nano-biomimetic drug delivery vehicle Asp8[H40-TPZ/IR780@(RBC-H)] that has excellent bone and cancer targeting as well as immune escape abilities to treat malignancies in jaw bones. These nanoparticles were camouflaged with a head and neck squamous cell carcinoma WSU-HN6 cell (H) and red blood cell (RBC) hybrid membrane, which were modified by an oligopeptide of eight aspartate acid (Asp8). The spherical morphology and typical core-shell structure of biomimetic nanoparticles were observed by transmission electron microscopy. These nanoparticles exhibited the same surface proteins as those of WSU-HN6 and RBC. Flow cytometry and confocal microscopy showed a greater uptake of the biomimetic nanoparticles when compared to bare H40-PEG nanoparticles. Biodistribution of the nanoparticles in vivo revealed that they were mainly localized in the area of bone invasion by WSU-HN6 cells. Moreover, the Asp8[H40-TPZ/IR780@(RBC-H)] nanoparticles exhibited effective cancer growth inhibition properties when compared to other TPZ or IR780 formulations. CONCLUSIONS: Asp8[H40-TPZ/IR780@(RBC-H)] has bone targeting, tumor-homing and immune escape abilities, therefore, it is an efficient multi-targeting drug delivery platform for achieving precise anti-cancer therapy during bone invasion.

Ternary supramolecular nanocomplexes for superior anticancer efficacy of natural medicines.

The discovery of effective anticancer drug delivery systems and elucidation of the mechanism are enormous challenges. Using two drug administration-approved biomaterials, we constructed a natural medicine (NM)-loaded ternary supramolecular nanocomplex (TSN) suitable for large-scale production. The TSN has a better effect against cancer cells/stem cells than NM with differentially upregulated (27 versus 59) and downregulated (165 versus 66) proteins, respectively. Treatment with the TSN induced apoptosis and G2/M arrest, inhibited cell proliferation, metastasis and invasion, reduced colony/sphere formation, and decreased the frequency of side population cells and CD133+CD44+ABCG2+ cells. These results were revealed by multiple analyses (proteomic analysis, transwell migration and colony/sphere formation assays, biomarker profiling, etc.). We first reported the proteomic analysis of small lung cancer cells responding to a drug or its nanovesicles. We first conducted a proteomic evaluation of tumor cells responding to a drug supramolecular nanosystem. The supramolecular conformation of the TSN and the interactions of the TSN with albumin were verified by molecular docking experiments. The dominant binding forces in the TSN complexation process were electrostatic interactions, van der Waalsinteractions and bond stretching. The TSN binds to albumin more readily than NM does. The TSN has good in situ absorptive and in vitro/vivo kinetic properties. The relative bioavailability of the TSN to EA was 458.39%. The NM-loaded TSN is a supramolecular vesicle that can be produced at an industrial scale for efficient cancer therapy.

Antiviral Drug Delivery System for Enhanced Bioactivity, Better Metabolism and Pharmacokinetic Characteristics.

Antiviral drugs (AvDs) are the primary resource in the global battle against viruses, including the recent fight against corona virus disease 2019 (COVID-19). Most AvDs require multiple medications, and their use frequently leads to drug resistance, since they have poor oral bioavailability and low efficacy due to their low solubility/low permeability. Characterizing the in vivo metabolism and pharmacokinetic characteristics of AvDs may help to solve the problems associated with AvDs and enhance their efficacy. In this review of AvDs, we systematically investigated their structure-based metabolic reactions and related enzymes, their cellular pharmacology, and the effects of metabolism on AvD pharmacodynamics and pharmacokinetics. We further assessed how delivery systems achieve better metabolism and pharmacology of AvDs. This review suggests that suitable nanosystems may help to achieve better pharmacological activity and pharmacokinetic behavior of AvDs by altering drug metabolism through the utilization of advanced nanotechnology and appropriate administration routes. Notably, such AvDs as ribavirin, remdesivir, favipiravir, chloroquine, lopinavir and ritonavir have been confirmed to bind to the severe acute respiratory syndrome-like coronavirus (SARS-CoV-2) receptor and thus may represent anti-COVID-19 treatments. Elucidating the metabolic and pharmacokinetic characteristics of AvDs may help pharmacologists to identify new formulations with high bioavailability and efficacy and help physicians to better treat virus-related diseases, including COVID-19.

[Preparation, Characterization and Pharmacokinetic Study of Arginine Deiminase Lipid Nanoparticles].

OBJECTIVE: To prepare and characterize D-alpha-Tocopheryl polyethylene glycol 1000 succinate (TPGS) modified arginine deiminase (ADI) sulfobutyl-ß-Cyclodextrin liposome nanoparticles (ATCL), and to investigate the pharmacokinetic characteristics of ATCL in animals. METHODS: The reverse evaporation method was used to prepare ATCL, and the particle size and Zeta potential of ATCL were measured. Thiosemicarbazone-diacetylmonooxime colorimetric method was used to measure the activity of ADI. After intravenous administration, blood was drawn at set intervals of time and the enzyme activity in the plasma was measured. Enzyme activity-time curve was drawn subsequently and Debris Assessment Software (DAS) 2.1.1 was used to analyze the pharmacokinetic characteristics. RESULTS: The particle size and the potential of ATCL were (216.1±13.6) nm and (-19.4±2.1) mV, respectively. The optimal temperature and optimal pH for the catalytic reaction of ADI and ATCL were the same, both being 37 ℃ and pH6.5. Results of the analysis showed that the AUC (0-168 h), MRT (0-168 h), C max, T max, and t 1/2 of ATCL were 3.99, 2.56, 1.58, 3.2, and 9.88 times those of free ADI, respectively. Compared with ADI, the bioavailability of ATCL increased by 298.54%. CONCLUSION: ATCL prepared in the study can effectively improve the enzyme activity and bioavailability of ADI in Sprague-Dawley rats.

A novel evodiamine amino derivative as a PI3K/AKT signaling pathway modulator that induces apoptosis in small cell lung cancer cells.

Evodiamine (EVO) was derivatized to a C10-amino derivative (EVA) using a two-step method suitable for industrializing production. This method has advantages such as a short reaction time, high yield, few byproducts and simple purification. The AUC and Cmax values of EVA were 7.02- and 4.62-fold, while the Tmax and Cl values were one-half and one-eighth that of EVO, respectively. EVA markedly improved the bioavailability, which might be ascribed to the serum albumin deposit effect. EVA was bound to albumin in the same hydrophobic pocket as EVO, but one more hydrogen bond was formed between Asp323 and the amino group at the C10 position. The amino derivative of natural alkaloids showed a substantial increase in antitumor activity on small cell lung cancer (SCLC) cells. The role of the PI3K/AKT signaling pathway in alkaloid/derivative-induced apoptosis in tumor cells was thoroughly described. p-AKT, its downstream effectors Bcl-2, Bax, caspase-3 and its upstream regulator PTEN were regulated by EVA. The interaction between EVO/EVA and the upstream protein PI3K p110 was first investigated with molecular docking. The apoptosis induced by EVA was abrogated after the PI3K/AKT signaling pathway was reactivated by IGF-1. The interaction between EVO/EVA and P-gp was also first studied using docking method. Their binding forces were weak. But EVA might reduce much expression of P-gp than EVO, and ultimately led to reduction of EVA efflux. Our study provides novel insights into a feasible and productive amino derivative of natural alkaloids for SCLC therapy.

Smart Stimuli-Responsive and Mitochondria Targeting Delivery in Cancer Therapy.

Dysfunction in the mitochondria (Mc) contributes to tumor progression. It is a major challenge to deliver therapeutic agents specifically to the Mc for precise treatment. Smart drug delivery systems are based on stimuli-responsiveness and active targeting. Here, we give a whole list of documented pathways to achieve smart stimuli-responsive (St-) and Mc-targeted DDSs (St-Mc-DDSs) by combining St and Mc targeting strategies. We present the formulations, targeting characteristics of St-Mc-DDSs and clarify their anti-cancer mechanisms as well as improvement in efficacy and safety. St-Mc-DDSs usually not only have Mc-targeting groups, molecules (lipophilic cations, peptides, and aptamers) or materials but also sense the surrounding environment and correspondingly respond to internal biostimulators such as pH, redox changes, enzyme and glucose, and/or externally applied triggers such as light, magnet, temperature and ultrasound. St-Mc-DDSs exquisitely control the action site, increase therapeutic efficacy and decrease side effects of the drug. We summarize the clinical research progress and propose suggestions for follow-up research. St-Mc-DDSs may be an innovative and sensitive precision medicine for cancer treatment.