Development of a cost-effective confocal Raman microscopy with high sensitivity.

Confocal Raman microscopy is a powerful technique for identifying materials and molecular species; however, the signal from Raman scattering is extremely weak. Typically, handheld Raman instruments are cost-effective but less sensitive, while high-end scientific-grade Raman instruments are highly sensitive but extremely expensive. This limits the widespread use of Raman technique in our daily life. To bridge this gap, we explored and developed a cost-effective yet highly sensitive confocal Raman microscopy system. The key components of the system include an excitation laser based on readily available laser diode, a lens-grating-lens type spectrometer with high throughput and image quality, and a sensitive detector based on a linear charge-coupled device (CCD) that can be cooled down to -30 °C. The developed compact Raman instrument can provide high-quality Raman spectra with good spectral resolution. The 3rd order 1450 cm-1 peak of Si (111) wafer shows a signal-to-noise ratio (SNR) better than 10:1, demonstrating high sensitivity comparable to high-end scientific-grade Raman instruments. We also tested a wide range of different samples (organic molecules, minerals and polymers) to demonstrate its universal application capability.

Hybrid metal halide family with color-time-dual-resolved phosphorescence for multiplexed information security applications.

Luminescent materials with engineered optical properties play an important role in anti-counterfeiting and information security technology. However, conventional luminescent coding is limited by fluorescence color or intensity, and high-level multi-dimensional luminescent encryption technology remains a critically challenging goal in different scenarios. To improve the encoding capacity, we present an optical multiplexing concept by synchronously manipulating the emission color and decay lifetimes of room-temperature phosphorescence materials at molecular level. Herein, we devise a family of zero-dimensional (0D) hybrid metal halides by combining organic phosphonium cations and metal halide tetrahedral anions as independent luminescent centers, which display blue phosphorescence and green persistent afterglow with the highest quantum yields of 39.9 % and 57.3 %, respectively. Significantly, the luminescence lifetime can be fine-tuned in the range of 0.0968-0.5046 µs and 33.46-125.61 ms as temporary time coding through precisely controlling the heavy atomic effect and inter-molecular interactions. As a consequence, synchronous blue phosphorescence and green afterglow are integrated into one 0D halide platform with adjustable emission lifetime acting as color- and time-resolved dual RTP materials, which realize the multiple applications in high-level anti-counterfeiting and information storage. The color-lifetime-dual-resolved encoding ability greatly broadens the scope of luminescent halide materials for optical multiplexing applications.

Comparative analysis of the therapeutic efficacy of remimazolam tosylate and propofol in older adults undergoing painless endoscopic retrograde cholangiopancreatography.

Objective: The aim of this study is to conduct a comparative analysis of the therapeutic outcomes associated with the administration of remimazolam and propofol during painless endoscopic retrograde cholangiopancreatography (ERCP) procedures in older adults. Methods: A total of 140 older adults who underwent elective painless ERCP were randomly assigned to two groups using the random number table method: the remimazolam group and the propofol group, each consisting of 70 patients. In the remimazolam group, anesthesia was administered using a combination of remimazolam and opioids, while in the propofol group, a combination of propofol and opioids was used. Comparative assessments between the two groups included anesthesia induction time, first induction success rate, intraoperative hemodynamics, awakening duration, stress response index, and the incidence of adverse reactions. Results: The remimazolam group exhibited a prolonged anesthesia induction time compared to the propofol group and a lower success rate of first induction (P < 0.05). At the point of endoscope entry (T2) and 10 min post-operation (T3), patients in the remimazolam group demonstrated higher mean arterial pressure (MAP), heart rate (HR), and bispectral index (BIS) values compared to those in the propofol group (P < 0.05). Furthermore, the remimazolam group had shorter durations for eye-opening, consciousness recovery, and residence in the recovery room compared to the propofol group (P < 0.05). Post-surgery levels of epinephrine (E), norepinephrine (NE), and cortisol (Cor) at 24 h were lower in the remimazolam group than in the propofol group (P < 0.05). The incidence of adverse reactions was significantly lower in the remimazolam group (18.57%) compared to the propofol group (31.43%) (P < 0.05). Conclusion: Remimazolam exhibits a longer induction time compared to propofol in the painless diagnosis and treatment of ERCP in older adults. However, it provides a more stable circulatory state post-induction and throughout the operation, reduces stress response, enables rapid recovery, and has a lower incidence of serious adverse reactions. These attributes suggest that remimazolam has potential for widespread clinical application and adoption. Clinical Trial Registration: clinicaltrials.gov, identifier ChiCTR2400080926.

Association between maximal urethral length preservation and postoperative continence after robot-assisted radical prostatectomy: a meta-analysis and systematic review.

ABSTRACT: Urinary incontinence is a common complication following robot-assisted radical prostatectomy (RARP). Urethral length has been identified as a factor affecting postoperative continence recovery. In this meta-analysis, we examined the association between use of the maximal urethral length preservation (MULP) technique and postoperative urinary continence in patients undergoing RARP. We conducted a comprehensive search of PubMed, Web of Science, Embase, and the Cochrane Library up to December 31, 2023. The quality of the literature was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis was performed to synthesize data and calculate the odds ratio (OR) from eligible studies on continence and MULP. Six studies involving 1869 patients met the eligibility criteria. MULP was positively associated with both early continence (1 month after RARP; Z = 3.62, P = 0.003, OR = 3.10, 95% confidence interval [CI]: 1.68-5.73) and late continence (12 months after RARP; Z = 2.34, P = 0.019, OR = 2.10, 95% CI: 1.13-3.90). Oncological outcomes indicated that MULP did not increase the overall positive surgical margin rate or the positive surgical margin status at the prostate apex (both P > 0.05). In conclusion, the use of the MULP technique in RARP significantly improved both early and late postoperative continence outcomes without compromising oncological outcomes.

Benchmarking Large Language Models in Evidence-Based Medicine.

Evidence-based medicine (EBM) represents a paradigm of providing patient care grounded in the most current and rigorously evaluated research. Recent advances in large language models (LLMs) offer a potential solution to transform EBM by automating labor-intensive tasks and thereby improving the efficiency of clinical decision-making. This study explores integrating LLMs into the key stages in EBM, evaluating their ability across evidence retrieval (PICO extraction, biomedical question answering), synthesis (summarizing randomized controlled trials), and dissemination (medical text simplification). We conducted a comparative analysis of seven LLMs, including both proprietary and open-source models, as well as those fine-tuned on medical corpora. Specifically, we benchmarked the performance of various LLMs on each EBM task under zero-shot settings as baselines, and employed prompting techniques, including in-context learning, chain-of-thought reasoning, and knowledge-guided prompting to enhance their capabilities. Our extensive experiments revealed the strengths of LLMs, such as remarkable understanding capabilities even in zero-shot settings, strong summarization skills, and effective knowledge transfer via prompting. Promoting strategies such as knowledge-guided prompting proved highly effective (e.g., improving the performance of GPT-4 by 13.10% over zero-shot in PICO extraction). However, the experiments also showed limitations, with LLM performance falling well below state-of-the-art baselines like PubMedBERT in handling named entity recognition tasks. Moreover, human evaluation revealed persisting challenges with factual inconsistencies and domain inaccuracies, underscoring the need for rigorous quality control before clinical application. This study provides insights into enhancing EBM using LLMs while highlighting critical areas for further research. The code is publicly available on Github.

Paeonol prevents sepsis-associated encephalopathy via regulating the HIF1A pathway in microglia.

Paeonol, a phenolic acid compound extracted from the Cortex Moutan, exhibits significant anti-inflammatory, antioxidant, and anti-apoptotic properties. This study aimed to investigate the effects of paeonol on neuroinflammation and depressive-like symptoms, and the underlying mechanisms in a mouse model of sepsis-associated encephalopathy (SAE) induced by lipopolysaccharide (LPS). To assess the therapeutic potential of paeonol in mice treated with LPS, behavioral assessments were conducted using the open-field test (OFT), tail suspension test (TST), and forced swimming test (FST), and quantitative PCR (qPCR), Western blot, and immunofluorescent staining were utilized to determine the expression levels of inflammatory molecules in the hippocampus in vivo and microglial cells in vitro. Our results revealed that paeonol significantly alleviated anxiety and depressive-like symptoms, as evidenced by improved activity in OFT, reduced immobility time in TST and FST, and decreased levels of inflammatory markers such as IL6, TNFα, and PFKFB3. Further in vitro experiments confirmed that paeonol downregulated the expression of pro-inflammatory molecules. A network pharmacology-based strategy combined with molecular docking and cellular thermal shift assay highlighted HIF1A as a potential target for paeonol. Similar anti-inflammatory effects of a HIF1A inhibitor were also observed in microglia treated with LPS. Furthermore, these effects were reversed by CoCl2, a HIF1A agonist, indicating the critical role of the HIF1A signaling pathway in mediating the therapeutic effects of paeonol. These findings highlight the potential of paeonol in modulating the HIF1A pathway, offering a promising therapeutic strategy for neuroinflammation in SAE.

Adjustable Phase-Amplitude-Phase Acoustic Metasurface for the Implementation of Arbitrary Impedance Matrices.

Impedance metasurfaces enable accurate regulation of acoustic fields. However, they can hardly supply a flexible response as such perfect operation is accompanied by stringent requirements on the design of unit cells. Actually, an arbitrary lossless and passive target impedance matrix requires the tuning of 3 independent real parameters. The set composed of a reflection phase, a transmission amplitude, and a transmission phase, enables the representation of an arbitrary impedance matrix, possibly possessing singular elements. In this paper, a mechanism of phase-amplitude-phase modulation (PAP modulation) is developed for the generic design of the unit cells of acoustic impedance metasurfaces. Adjustable acoustic impedance metasurfaces are further available under this framework. An impedance unit with 3 mobile parts is designed based on this idea. The assembled metasurface can handle different incidences for acoustic field manipulation at a given frequency. Beam steering and beam splitting are considered as demonstration examples and are verified by numerical simulation and experiment. PAP modulation enriches the design of acoustic impedance metasurfaces and extends the range of application of impedance theory.

Role of TREM2 in immune and neurological diseases: Structure, function, and implications.

Triggering Receptor Expressed on Myeloid Cells 2 (TREM2), a transmembrane receptor initially linked to neurodegenerative diseases, has recently emerged as a key player in conditions such as obesity and cancer. This review explores the structure, function, and mechanisms of TREM2 across these diverse pathological contexts, with a particular focus on its critical roles in immune regulation and neuroprotection. TREM2 primarily modulates cellular activity by binding extracellular ligands, thereby activating downstream signaling pathways and exerting immunomodulatory effects. Additionally, the therapeutic potential of targeting TREM2 is discussed, emphasizing its promise as a future treatment strategy for various diseases.

Dietary inflammatory index and all-cause mortality in adults with COPD: a prospective cohort study from the NHANES 1999-2018.

Background: Chronic inflammation is closely linked to Chronic Obstructive Pulmonary Disease (COPD); however, the impact of the Dietaryq Inflammatory Index (DII) on mortality among COPD patients remains uncertain. Objective: To assess the correlation between the DII and all-cause mortality in COPD patients using data from the National Health and Nutrition Examination Survey (NHANES). Methods: We conducted a retrospective cohort study on 1,820 COPD patients from the NHANES dataset (1999-2018). The influence of DII on mortality was evaluated using multivariate Cox regression, smoothing spline fitting, and threshold effect analysis. Additionally, Kaplan-Meier survival analysis was performed to compare survival curves among different DII groups. Subgroup analyses and E-values identified sensitive cohorts and assessed unmeasured confounding. Results: Over an average follow-up of 91 months, multivariate Cox regression models revealed a significant positive correlation between DII scores and mortality risk, with each unit increase in DII associated with a 10% higher risk of death (HR: 1.10, 95% CI: 1.03-1.16; P = 0.002). Among the DII tertiles, individuals in the second tertile (T2: 1.23-2.94) experienced a 67% increase in mortality risk compared to those in the lowest tertile (T1: -5.28-1.23) (HR: 1.67, 95% CI: 1.26-2.21; p < 0.001). The third tertile (T3) did not show a statistically significant increase in mortality risk (HR: 1.30, 95% CI: 0.98-1.72; p=0.074). A restricted cubic spline analysis indicated a significant nonlinear association between DII and all-cause mortality (p = 0.021). Threshold effect analysis further revealed that below a DII of 2.19, there was a significant increase in all-cause mortality risk (HR = 1.19, 95% CI: 1.07-1.33; p = 0.002), while at or above this threshold, the risk increase was not statistically significant (HR=0.89, 95% CI: 0.68-1.15; p = 0.380). Kaplan-Meier analysis revealed significant differences in survival curves among DII tertiles (p < 0.001), with the lowest DII tertile showing the highest survival probability. Both subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion: DII is positively correlated with mortality risk in COPD patients, showing nonlinear characteristics and threshold effects, underscoring its prognostic value.

Learning Motor Cues in Brain-Muscle Modulation.

Current studies for brain-muscle modulation often analyze selected properties in electrophysiological signals, leading to a partial understanding. This article proposes a cross-modal generative model that converts brain activities measured by electroencephalography (EEG) to corresponding muscular responses recorded by electromyography (EMG). Examining the generation process in the model highlights how the motor cue, representing implicit motor information hidden within brain activities, modulates the interaction between brain and muscle systems. The proposed model employs a two-stage generation process to bridge the semantic gap in cross-modal signals. Initially, the shared movement-related information between EEG and EMG signals is extracted using a contrastive learning framework. These shared representations act as conditional vectors in the subsequent EMG generation stage based on generative adversarial networks (GANs). Experiments on a self-collected multimodal electrophysiological signal data set show the algorithm's superiority over existing time series generative methods in cross-modal EMG generation. Further insights derived from the model's inference process underscore the brain's strategy for muscle control during movements. This research provides a data-driven approach for the neuroscience community, offering a comprehensive perspective of brain-muscular modulation.

BioTRY: A Comprehensive Knowledge Base for Titer, Rate, and Yield of Biosynthesis.

Synthetic biology is rapidly evolving into a data-intensive science that increasingly relies on massive data sets; one of its applications is the evaluation of the economic viability of fermentation processes. However, the key economic indicators, namely titer, rate, and yield (TRY), which respectively reflect the downstream processing, reactor size, and raw material costs, are not well captured in bioinformatics databases. In this paper, we present BioTRY, an intuitive and user-friendly tool that contains >5,000 biochemicals and >3,800 strains, along with over 52,000 corresponding TRY entries with original references. It is freely available at http://www.synbiohealth.cn/biotry. To our knowledge, BioTRY is the first available database on biosynthesis TRY data from original research. We anticipate that BioTRY will become a useful tool that aids researchers and decision-makers in understanding the current development state of biosynthesis and allows them to foresee potential prospects and applications for biosynthesis.

The value of assessing deep disease healing by probe-based confocal laser endomicroscopy and histology for long-term prognosis of ulcerative colitis.

BACKGROUND AND AIM: The benefits of deep disease healing need evaluation by long-term clinical research in different populations. Confocal laser endomicroscopy (CLE) is a superior method for evaluating deep disease healing. METHODS: This prospective study enrolled ulcerative colitis (UC) patients in clinical remission who underwent colonoscopy, CLE, and histological assessment. Patients were monitored for relapse by patient-reported outcomes and colonoscopy evaluation of mucosal healing. The ability of different methods of mucosal healing to predict long-term disease recurrence was assessed using Kaplan-Meier estimation and Cox proportional hazard regression. RESULTS: Forty-two patients in clinical remission were assessed by colonoscopy. Those with Mayo endoscopic subscores (MES) ≤ 1 were enrolled. The 48-month recurrence rates in present healing group, assessed by CLE (colonic barrier assessment and ENHANCE index) and by histological examination (Geboes scale), were 20.0%, 26.7%, and 11.1%, respectively, and were significantly lower than absent healing group (P < 0.05). Univariate Cox proportional risk regression analysis in absent of healing disease, determined by the ENHANCE index and Geboes scale, indicated an increased risk of recurrent events, with hazard ratios (HR) of 3.87 (95% CI: 1.18, 12.62) and 8.20 (95% CI: 1.06, 63.30), respectively. Multivariate Cox proportional hazard regression analysis adjusted for the extent of inflammation (E3 or not) showed a significant difference only for the ENHANCE index, with an HR of 3.53 (95% CI: 1.03, 12.10), P = 0.045. CONCLUSIONS: Deep disease healing has a lower recurrence rate. The colonic barrier healing assessment, ENHANCE index, and histological Geboes scale have superior long-term prognostic value for UC patients.

Tissue-Compatible and Lubricated Hydrogel Catheter with Promising Activity Against Polymicrobial Infections for Ventilator-Associated Pneumonia Prevention.

Endotracheal intubation is a vital means of saving critically ill patients. However, the inserted catheter often causes tissue damage and the formation of tenacious biofilms containing drug-resistant bacteria and fungi, leading to severe ventilator-associated pneumonia (VAP). Currently, the resolution of VAP is usually based on antibiotic treatment and lacks targeted prophylaxis. Here, a quaternary phosphonium salts functionalized hydrogel catheter that enhances tissue compatibility yet inhibits complex and tenacious pathogens in the catheter, thus preventing VAP is reported. By copolymerizing the quaternary phosphonium electrolyte and acrylic acid monomers, the hydrogel catheter demonstrates good shape-supporting ability, and its strength and modulus can be adjusted over a wide range to meet the needs of different ages. Moreover, it possesses good tissue compatibility, antifouling properties, stable lubrication capability, and superior hydrophilicity, which may mitigate tissue damage caused by contact. Importantly, the hydrogel catheter demonstrates potent broad-spectrum intrinsic antimicrobial activity, eradicating nearly 99% of multi-drug resistant bacteria and 80% of fungi. To validate its role in preventing VAP, the real VAP pathogenesis process is mimicked, establishing a polymicrobial infections model considering time effects. The results prove that the hydrogel catheter effectively inhibits the invasion of various drug-resistant pathogens and prevents biofilm formation.

Magnesium-promoted nickel-catalysed chlorination of aryl halides and triflates under mild conditions.

In this study, we present a ligand-free nickel(II)-catalyzed halogen exchange of aromatic halides with magnesium chloride. This method effectively facilitates the retro-Finkelstein reaction for a wide range of aryl bromides, iodides and triflates, demonstrating excellent functional group tolerance. Mechanistic studies reveal that magnesium plays a crucial role in the challenging reductive elimination from Ni(II) intermediates.

Oral microbiome dysbiosis may be associated with intra cranial aneurysms.

BACKGROUND: Although the etiology of aneurysms remains elusive, recent advances in high-throughput sequencing technology and ongoing human microbiome investigations suggest a potential link between microbiome composition and the onset of various human diseases. OBJECTIVE: This study aimed to utilize high-throughput 16 S rRNA gene sequencing to analyze the oral flora bacterial profiles of individuals, comparing patients with intracranial aneurysms to a healthy control group. Importantly, we sought to identify differences in the oral microbiota and offer novel insights and methods for early diagnosis and identification of intracranial aneurysms. METHOD: Saliva samples were collected from 60 patients with cerebral aneurysms (case group) and 130 healthy individuals (control group). The V3-V4 region of the bacterial 16 S rRNA gene was amplified and sequenced using the HiSeq high-throughput sequencing platform to establish the bacterial profile. Sequencing data were analyzed using QIIME2 and Metastats software to compare composition differences and relative abundance at the phylum and genus levels in the oral microbiota of the two groups. RESULTS: Significant differences in oral microbiota composition were observed between patients in the case and control groups (P < 0.05). Genus-level identification highlighted key positions occupied by Eubacterium, Saccharimonadaceae, Rothia, Gemella, Streptococcus, Lactobacillales, Phocaeicola, Bacteroides, Saccharimonadales, and Abiotrophia. CONCLUSION: This study revealed noteworthy distinctions in the composition, abundance, and diversity of oral microbiota between intracranial aneurysm patients and healthy controls. These disparities suggest a potential correlation between oral microbiota and the development of intracranial aneurysms, offering new avenues for early diagnosis and intervention. However, limitations such as a small sample size, lack of prospective design, and absence of causal inference warrant further validation and exploration.

MicroRNA­24 alleviates colorectal cancer progression via a rs28382740 single nucleotide polymorphism in the long noncoding region of X­linked inhibitor of apoptosis protein.

Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide. Recurrence is associated with the poor survival of patients with CRC. Targeted therapy and precision medicine for recurrent CRC may improve the clinical outcome. Therefore, finding biomarkers that can detect CRC early, assess its prognosis and survival, and predict its treatment response is key to improving the clinical prognosis. The aim of this study was to assess CRC recurrence by analyzing molecular differences using postoperative specimens. Whole-exome sequencing was first used to evaluate the molecular differences in CRC tissues from patients with recurrent disease, and the results were then verified with tissue array methods. The regulation of single nucleotide polymorphisms (SNPs) in long noncoding regions of interest was analyzed in the presence of target microRNAs (miRs) using luciferase assays. The results demonstrated that in patients with recurrent CRC, the G allele was mainly detected at the rs28382740 SNP in the 3'-untranslated region of the X-linked inhibitor of apoptosis (XIAP)-encoding gene. From the tissue arrays, 60% (3/5) of patients with the G allele of the rs28382740 SNP were diagnosed with CRC recurrence, whilst only 10% (1/10) of patients without the G allele had recurrent CRC (P=0.077). Furthermore, XIAP levels were high in non-CRC (50%; 2/4) and CRC (75%; 3/4) tissues of patients with recurrent disease and CRC (54.5%; 6/11) tissues of patients without recurrent disease. However, but only 9.1% (1/11) of non-CRC tissues of nonrecurrent patients had significantly high XIAP expression levels (P=0.022). Using a luciferase assay, it was demonstrated that miR-24s (miR-24-1-5p and miR-24-2-5p) targeting the rs28382740 SNP reduced XIAP levels in CRC cells with rs28382740 SNP genotype G. These results indicate that apoptosis-related proteins, such as XIAP, may be therapeutic targets or biomarkers for tumor development. The data from the present study support an inhibitory effect of miR-24s on XIAP expression. However, this inhibitory potency depends on the rs28382740 SNP genotype and may alleviate CRC progression by regulating the expression of XIAP.

NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival. METHODS: To address these challenges, we propose a HCC prognosis prediction model that integrates pathological micronecrosis information through Graph Convolutional Neural Networks (GCN). This approach enables GCN to utilize micronecrosis, which has been shown to be highly correlated with prognosis, thereby significantly enhancing prognostic stratification quality. We developed our model using 3622 slides from 752 patients with primary HCC from the FAH-ZJUMS dataset and conducted internal and external validations on the FAH-ZJUMS and TCGA-LIHC datasets, respectively. RESULTS: Our method outperformed the baseline by 8.18% in internal validation and 9.02% in external validations. Overall, this paper presents a deep learning research paradigm that integrates HCC micronecrosis, enhancing both the accuracy and interpretability of prognostic predictions, with potential applicability to other pathological prognostic markers. CONCLUSIONS: This study proposes a composite GCN prognostic model that integrates information on HCC micronecrosis, collecting large dataset of HCC histopathological images. This approach could assist clinicians in analyzing HCC patient survival and precisely locating and visualizing necrotic tissues that affect prognosis. Following the research paradigm outlined in this paper, other prognostic biomarker integration models with GCN could be developed, significantly enhancing the predictive performance and interpretability of prognostic model.

Hydrogel-based platforms for site-specific doxorubicin release in cancer therapy.

Hydrogels are promising candidates for the delivery of therapeutics in the treatment of human cancers. Regarding to the biocomaptiiblity, high drug and encapsulation efficacy and adjustable physico-chemical features, the hydrogels have been widely utilized for the delivery of chemotherapy drugs. Doxorubicin (DOX) is one of the most common chemotherapy drugs used in cancer therapy through impairing topoisomerase II function and increasing oxidative damage. However, the tumor cells have developed resistance into DOX-mediated cytotoxic impacts, requiring the delivery systems to increase internalization and anti-cancer activity of this drug. The hydrogels can deliver DOX in a sustained manner to maximize its anti-cancer activity, improving cancer elimination and reduction in side effects and drug resistance. The natural-based hydrogels such as chitosan, alginate and gelatin hydrogels have shown favourable biocompatibility and degradability in DOX delivery for tumor suppression. The hydrogels are able to co-deliver DOX with other drugs or genes to enhance drug sensitivity and mediate polychemotherapy, synergistically suppressing cancer progression. The incorporation of nanoparticles in the structure of hydrogels can improve the sustained release of DOX and enhancing intracellular internalization, accelerating DOX's cytotoxicity. Furthermore, the stimuli-responsive hydrogels including pH-, redox- and thermo-sensitive platforms are able to improve the specific release of DOX at the tumor site. The DOX-loaded hydrogels can be further employed in the clinic for the treatment of cancer patients and improving efficacy of chemotherapy.