Detection of Maize Mold Based on a Nanocomposite Colorimetric Sensor Array under Different Substrates.

This study developed a novel nanocomposite colorimetric sensor array (CSA) to distinguish between fresh and moldy maize. First, the headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) method was used to analyze volatile organic compounds (VOCs) in fresh and moldy maize samples. Then, principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to identify 2-methylbutyric acid and undecane as key VOCs associated with moldy maize. Furthermore, colorimetric sensitive dyes modified with different nanoparticles were employed to enhance the dye properties used in the nanocomposite CSA analysis of key VOCs. This study focused on synthesizing four types of nanoparticles: polystyrene acrylic (PSA), porous silica nanospheres (PSNs), zeolitic imidazolate framework-8 (ZIF-8), and ZIF-8 after etching. Additionally, three types of substrates, qualitative filter paper, polyvinylidene fluoride film, and thin-layer chromatography silica gel, were comparatively used to fabricate nanocomposite CSA combining with linear discriminant analysis (LDA) and K-nearest neighbor (KNN) models for real sample detection. All moldy maize samples were correctly identified and prepared to characterize the properties of the CSA. Through initial testing and nanoenhancement of the chosen dyes, four nanocomposite colorimetric sensitive dyes were confirmed. The accuracy rates for LDA and KNN models in this study reached 100%. This work shows great potential for grain quality control using CSA methods.

Efficient Poly-Adenine-Tailed DNA Functionalization of Gold Nanorods for Tailored Nanostructure Assembly.

Gold nanorods (AuNRs) with unique optical properties play a pivotal role in applications in plasmonic imaging, small molecule detection, and photothermal therapy. However, challenges in DNA functionalization of AuNRs hinder their full potential due to the presence of a dense cetyltrimethylammonium bromide (CTAB) bilayer, impeding close DNA contact. In this study, we introduced a convenient approach for the rapid assembly of polyadenine (polyA) tailed DNA on AuNRs with control of DNA density, rigidity, and valence. We explored the impact of DNA with designed properties on the construction of core-satellite structures by employing AuNRs as cores and spherical gold nanoparticles (AuNSs) as satellites. Density, rigidity, and valence are identified as crucial factors for efficient construction. Specifically, polyA-tailed DNA modulated DNA density and reduced spatial hindrance and electrostatic repulsion, thereby facilitating the construction. Enhancing the rigidity of DNA and incorporating multiple binding sites can further improve the efficiency.

Medium-Entropy Monosilicates Deliver High Corrosion Resistance to Calcium-Magnesium Aluminosilicate Molten Salt.

For decreasing the global cost of corrosion, it is essential to understand the intricate mechanisms of corrosion and enhance the corrosion resistance of materials. However, the ambiguity surrounding the dominant mechanism of calcium-magnesium aluminosilicate (CMAS) molten salt corrosion in extreme environments hinders the mix-and-matching of the key rare earth elements for increasing the resistance of monosilicates against corrosion of CMAS. Herein, an approach based on correlated electron microscopy techniques combined with density functional theory calculations is presented to elucidate the complex interplay of competing mechanisms that control the corrosion of CMAS of monosilicates. These findings reveal a competition between thermodynamics and kinetics that relies on the temperatures and corrosion processes. Innovative medium-entropy monosilicates with exceptional corrosion resistance even at 1500 °C are developed. This is achieved by precisely modulating the radii of rare earth ions in monosilicates to strike a delicate balance between the competition in thermodynamics and kinetics. After 50 and 100 h of corrosion, the thinnest reactive layers are measured to be only 28.8 and 35.4 µm, respectively.

HICL: Hashtag-Driven In-Context Learning for Social Media Natural Language Understanding.

Natural language understanding (NLU) is integral to various social media applications. However, the existing NLU models rely heavily on context for semantic learning, resulting in compromised performance when faced with short and noisy social media content. To address this issue, we leverage in-context learning (ICL), wherein language models learn to make inferences by conditioning on a handful of demonstrations to enrich the context and propose a novel hashtag-driven ICL (HICL) framework. Concretely, we pretrain a model, which employs #hashtags (user-annotated topic labels) to drive BERT-based pretraining through contrastive learning. Our objective here is to enable to gain the ability to incorporate topic-related semantic information, which allows it to retrieve topic-related posts to enrich contexts and enhance social media NLU with noisy contexts. To further integrate the retrieved context with the source text, we employ a gradient-based method to identify trigger terms useful in fusing information from both sources. For empirical studies, we collected 45 M tweets to set up an in-context NLU benchmark, and the experimental results on seven downstream tasks show that HICL substantially advances the previous state-of-the-art results. Furthermore, we conducted an extensive analysis and found that the following hold: 1) combining source input with a top-retrieved post from is more effective than using semantically similar posts and 2) trigger words can largely benefit in merging context from the source and retrieved posts.

Corrigendum: The utility of high-frequency 18 MHz ultrasonography for preoperative evaluation of acral melanoma thickness in Chinese patients.

[This corrects the article DOI: 10.3389/fonc.2023.1185389.].

Serum α-hydroxybutyrate dehydrogenase as a biomarker for predicting survival outcomes in patients with UTUC after radical nephroureterectomy.

PURPOSE: We aimed to determine the prognostic value of α-hydroxybutyrate dehydrogenase (α-HBDH) in upper tract urothelial carcinoma (UTUC) patients after radical nephroureterectomy (RNU). MATERIALS AND METHODS: We retrospectively enrolled the data of 544 UTUC patients at West China Hospital from May 2003 to June 2019. Cancer-specific survival (CSS) was the endpoint of interest. The optimal cutoff value of α-HBDH was identified by X-Tile program. After propensity score matching (PSM), we utilized Kaplan‒Meier curves to estimate survival and Cox proportional hazard model for risk assessment. A nomogram was built based on the results of multivariate analysis, and calibration curve, time-dependent receiver operating characteristic (ROC) curves and decision curve analysis were also performed to evaluate the predictive accuracy. RESULTS: Overall, 394 and 150 patients were divided into the α-HBDH-low group and α-HBDH -high group at the cutoff value of 158 U/L, respectively. After PSM, the two groups were well matched for all confounding factors. High α-HBDH was associated with inferior CSS (P = 0.006), and preoperative α-HBDH was an independent predictor for CSS (HR: 1.36; 95% CI:1.08, 1.80), especially in localized UTUC patients (HR: 2.04; 95% CI:1.11, 3.74). Furthermore, the nomogram based on α-HBDH achieved great predictive ability for CSS with areas under the curves of 0.800 and 0.778 for 3-year and 5-year CSS, respectively. CONCLUSION: Serum α-HBDH was a novel and reliable biomarker for predicting survival outcomes in UTUC patients after RNU but should be further explored.

Dialysis-functionalized microfluidic platform for in situ formation of purified liposomes.

Continuous-flow microfluidic devices have been extensively used for producing liposomes due to their high controllability and efficient synthesis processes. However, traditional methods for liposome purification, such as dialysis, gel chromatography, and ultrafiltration, are incompatible with microfluidic devices, which would dramatically restrict the efficiency of liposome synthesis. In this study, we developed a dialysis-functionalized microfluidic platform (DFMP) for in situ formation of purified drug-loaded liposomes. The device was successfully fabricated by using a high-resolution projection micro stereolithography (PµSL) 3D printer. The integrated DFMP consists of a microfluidic mixing unit, a microfluidic dialysis unit, and a dialysis membrane, enabling the liposome preparation and purification in one device. The purified ICG-loaded liposomes prepared by DFMP had a smaller size (264.01±5.34 nm to 173.93±10.71 nm) and a higher encapsulation efficiency (EE) (43.53±0.07% to 46.07±0.67%). In vivo photoacoustic (PA) imaging experiment demonstrated that ICG-loaded liposomes purified with microfluidic dialysis exhibited a stronger penetration and accumulation (2-3 folds) in tumor sites. This work provides a new strategy for one-step production of purified drug-loaded liposomes.

A novel difficult-to-segment samples focusing network for oral CBCT image segmentation.

Using deep learning technology to segment oral CBCT images for clinical diagnosis and treatment is one of the important research directions in the field of clinical dentistry. However, the blurred contour and the scale difference limit the segmentation accuracy of the crown edge and the root part of the current methods, making these regions become difficult-to-segment samples in the oral CBCT segmentation task. Aiming at the above problems, this work proposed a Difficult-to-Segment Focus Network (DSFNet) for segmenting oral CBCT images. The network utilizes a Feature Capturing Module (FCM) to efficiently capture local and long-range features, enhancing the feature extraction performance. Additionally, a Multi-Scale Feature Fusion Module (MFFM) is employed to merge multiscale feature information. To further improve the loss ratio for difficult-to-segment samples, a hybrid loss function is proposed, combining Focal Loss and Dice Loss. By utilizing the hybrid loss function, DSFNet achieves 91.85% Dice Similarity Coefficient (DSC) and 0.216 mm Average Symmetric Surface Distance (ASSD) performance in oral CBCT segmentation tasks. Experimental results show that the proposed method is superior to current dental CBCT image segmentation techniques and has real-world applicability.

A noninvasive method for predicting clinically significant prostate cancer using magnetic resonance imaging combined with PRKY promoter methylation level: a machine learning study.

BACKGROUND: Traditional process for clinically significant prostate cancer (csPCA) diagnosis relies on invasive biopsy and may bring pain and complications. Radiomic features of magnetic resonance imaging MRI and methylation of the PRKY promoter were found to be associated with prostate cancer. METHODS: Fifty-four Patients who underwent prostate biopsy or photoselective vaporization of the prostate (PVP) from 2022 to 2023 were selected for this study, and their clinical data, blood samples and MRI images were obtained before the operation. Methylation level of two PRKY promoter sites, cg05618150 and cg05163709, were tested through bisulfite sequencing PCR (BSP). The PI-RADS score of each patient was estimated and the region of interest (ROI) was delineated by 2 experienced radiologists. After being extracted by a plug-in of 3D-slicer, radiomic features were selected through LASSCO regression and t-test. Selected radiomic features, methylation levels and clinical data were used for model construction through the random forest (RF) algorithm, and the predictive efficiency was analyzed by the area under the receiver operation characteristic (ROC) curve (AUC). RESULTS: Methylation level of the site, cg05618150, was observed to be associated with prostate cancer, for which the AUC was 0.74. The AUC of T2WI in csPCA prediction was 0.84, which was higher than that of the apparent diffusion coefficient ADC (AUC = 0.81). The model combined with T2WI and clinical data reached an AUC of 0.94. The AUC of the T2WI-clinic-methylation-combined model was 0.97, which was greater than that of the model combined with the PI-RADS score, clinical data and PRKY promoter methylation levels (AUC = 0.86). CONCLUSIONS: The model combining with radiomic features, clinical data and PRKY promoter methylation levels based on machine learning had high predictive efficiency in csPCA diagnosis.

Research on reliability index and failure probability of inherent defect insurance from the insurance perspective.

With the continuous improvement of people 's living standards, people have put forward higher requirements for the safety and comfort of housing. Therefore, Inherent Defect Insurance, a financial method to guarantee the quality of construction projects, has also emerged. At present, China 's Inherent Defect Insurance has been gradually promoted, but its claim mechanism has not been analyzed and studied. From the perspective of construction engineering, this paper first makes a bibliometric analysis of the influencing factors of insurance claims that may be caused by construction engineering quality through VOSViewers, and the evaluation index system of inherent defects is constructed. Then, according to the influencing factors, the PSO-LSSVR model is adopted to fit the performance function of the inherent defects. Finally, based on the reliability design principle of engineering structure, the reliability index and failure probability of Inherent Defect Insurance are derived from the performance function of inherent defects. This paper also analyzes its application in insurance practice and determines the relationship between the number of insurance underwriting policies and the initial reserve of insurance at a certain risk level. This paper studies the probability of Inherent Defect Insurance by constructing the reliability model of inherent defect risks in construction quality, and analyzes the anti-risk ability of insurance companies from the perspective of claim, which provides scientific analysis methods and theoretical basis for the scientific decision-making of insurance companies.

Potential molecular biomarkers for the diagnosis and prognosis of bladder cancer.

Bladder cancer (BC) is a common malignant tumor of urinary system, which can be divided into muscle-invasive BC (MIBC) and nonmuscle-invasive BC (NMIBC). The number of BC patients has been gradually increasing currently. At present, bladder tumours are diagnosed and followed-up using a combination of cystoscopic examination, cytology and histology. However, the detection of early grade tumors, which is much easier to treat effectively than advanced stage disease, is still insufficient. It frequently recurs and can progress when not expeditiously diagnosed and monitored following initial therapy for NMIBC. Treatment strategies are totally different for different stage diseases. Therefore, it is of great practical significance to study new biomarkers for diagnosis and prognosis. In this review, we summarize the current state of biomarker development in BC diagnosis and prognosis prediction. We retrospectively analyse eight diagnostic biomarkers and eight prognostic biomarkers, in which CK, P53, PPARγ, PTEN and ncRNA are emphasized for discussion. Eight molecular subtype systems are also identified. Clinical translation of biomarkers for diagnosis, prognosis, monitoring and treatment will hopefully improve outcomes for patients. These potential biomarkers provide an opportunity to diagnose tumors earlier and with greater accuracy, and help identify those patients most at risk of disease recurrence.

Inflammatory markers predict survival in patients with postoperative urothelial carcinoma receiving tislelizumab (PD-1 inhibitor) adjuvant therapy.

BACKGROUND: In the management of urothelial carcinoma, patient selection for immunotherapy, particularly with immune checkpoint inhibitors such as PD-1 (programmed cell death protein 1), is important for treatment efficacy. Inflammatory markers are useful for predicting treatment outcomes and immune-related adverse events (irAEs). This study aims to retrospectively explore the associations between inflammatory markers and outcomes in patients with postoperative urothelial carcinoma undergoing tislelizumab (PD-1 inhibitor) adjuvant therapy. METHODS: A retrospective analysis was conducted on 133 patients with postoperative urothelial carcinoma who received tislelizumab adjuvant therapy at the Affiliated Hospital of Xuzhou Medical University from April 2020 to August 2023. The prognostic effects of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) on disease-free survival (DFS) and overall survival (OS) were assessed using Cox regression models. The correlation between inflammatory markers and the onset of irAEs was analyzed using logistic regression models. RESULTS: NLR < 5 and MLR < 0.31 were significantly associated with better outcomes compared to NLR >5 and MLR >0.31, respectively. Multivariate analysis revealed that an NLR < 5 was independently associated with better DFS and OS. However, there was no significant effect on the DFS and OS between PLR < 135 and PLR >135. Patients who experienced irAEs had longer DFS and OS. Multivariate analysis demonstrated that irAEs were an independent prognostic risk factor for DFS and OS. There was no significant difference in the occurrence of irAEs among different NLR, PLR, and MLR groups. CONCLUSION: In patients with postoperative urothelial carcinoma receiving tislelizumab adjuvant therapy, the assessment of NLR and MLR before treatment may serve as valuable predictive markers of clinical outcome.

An AhR-Ovol1-Id1 regulatory axis in keratinocytes promotes skin homeostasis against atopic dermatitis.

Skin is our outer permeability and immune defense barrier against myriad external assaults. Aryl hydrocarbon receptor (AhR) senses environmental factors and regulates barrier robustness and immune homeostasis. AhR agonist is in clinical trial for atopic dermatitis (AD) treatment, but the underlying mechanism of action remains ill-defined. Here we report OVOL1/Ovol1 as a conserved and direct transcriptional target of AhR in epidermal keratinocytes. We show that OVOL1/Ovol1 impacts AhR regulation of keratinocyte gene expression, and Ovol1 deletion in keratinocytes hampers AhR's barrier promotion function and worsens AD-like inflammation. Mechanistically, we identify Ovol1's direct downstream targets genome-wide, and provide in vivo evidence for Id1's critical role in barrier maintenance and disease suppression. Furthermore, our findings reveal an IL-1/dermal γδT cell axis exacerbating both type 2 and type 3 immune responses downstream of barrier perturbation in Ovol1 -deficient AD skin. Finally, we present data suggesting the clinical relevance of OVOL1 and ID1 function in human AD. Our study highlights a keratinocyte-intrinsic AhR-Ovol1-Id1 regulatory axis that promotes both epidermal and immune homeostasis against AD-like inflammation, implicating new therapeutic targets for AD.

Acoustic hologram-induced virtual in vivo enhanced waveguide (AH-VIEW).

Optical imaging and phototherapy in deep tissues face notable challenges due to light scattering. We use encoded acoustic holograms to generate three-dimensional acoustic fields within the target medium, enabling instantaneous and robust modulation of the volumetric refractive index, thereby noninvasively controlling the trajectory of light. Through this approach, we achieved a remarkable 24.3% increase in tissue heating rate in vitro photothermal effect tests on porcine skin. In vivo photoacoustic imaging of mouse brain vasculature exhibits an improved signal-to-noise ratio through the intact scalp and skull. These findings demonstrate that our strategy can effectively suppress light scattering in complex biological tissues by inducing low-angle scattering, achieving an effective depth reaching the millimeter scale. The versatility of this strategy extends its potential applications to neuroscience, lithography, and additive manufacturing.

Low-Frequency Ultrasound Sensitive Piezo1 Channels Regulate Keloid-Related Characteristics of Fibroblasts.

Keloids are benign fibroproliferative tumors that severely diminish the quality of life due to discomfort, dysfunction, and disfigurement. Recently, ultrasound technology as a noninvasive adjuvant therapy is developed to optimize treatment protocols. However, the biophysical mechanisms have not yet been fully elucidated. Here, it is proposed that piezo-type mechanosensitive ion channel component 1 (Piezo1) plays an important role in low-frequency sonophoresis (LFS) induced mechanical transduction pathways that trigger downstream cellular signaling processes. It is demonstrated that patient-derived primary keloid fibroblasts (PKF), NIH 3T3, and HFF-1 cell migration are inhibited, and PKF apoptosis is significantly increased by LFS stimulation. And the effects of LFS is diminished by the application of GsMTx-4, the selective inhibitor of Piezo1, and the knockdown of Piezo1. More importantly, the effects of LFS can be imitated by Yoda1, an agonist of Piezo1 channels. Establishing a patient-derived xenograft keloid implantation mouse model further verified these results, as LFS significantly decreased the volume and weight of the keloids. Moreover, blocking the Piezo1 channel impaired the effectiveness of LFS treatment. These results suggest that LFS inhibits the malignant characteristics of keloids by activating the Piezo1 channel, thus providing a theoretical basis for improving the clinical treatment of keloids.

Preoperative Systemic Inflammation Score Predicts the Prognosis of Patients with Upper Tract Urothelial Carcinoma Undergoing Radical Nephroureterectomy.

Background: To investigate the prognostic significance of systemic inflammation score (SIS) in upper tract urothelial carcinoma (UTUC) in patients undergoing radical nephroureterectomy (RNU). Methods: A total of 313 UTUC patients who underwent RNU at West China Hospital from May 2014 to June 2019 were retrospectively analyzed. The predictive value of SIS for relevant endpoints, including overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS), was assessed by Kaplan-Meier curves and the Cox proportional hazards model. Results: According to inclusion and exclusion criteria, 218 UTUC patients were ultimately included in this cohort study. Statistical analysis shows that increased SIS was significantly associated with higher TNM stage (p = 0.017), lower BMI (p = 0.037), absence of hemoglobin (p < 0.001), and pathologic necrosis (p = 0.007). Kaplan-Meier survival curves clearly visually stratified survival for the three outcomes. After adjusting for tumor grade, the multivariate Cox proportional hazards model results showed that SIS was an independent risk factor for poor OS and CSS (HR = 1.89, 95% CI: 1.11-3.21, p = 0.0183, HR = 1.89, 95% CI: 1.07-3.33, p = 0.0285) in the advanced group. Conclusions: SIS was an independent risk factor for OS and CSS after RNU in patients with high-grade UTUC. It may be a novel and conducive tool for preoperative risk stratification and guiding individualized therapy for high-risk UTUC patients.

The relationship between nonsteroidal anti-inflammatory drugs and cancer incidence: An umbrella review.

Several clinical and preclinical studies have shown that nonsteroidal anti-inflammatory drugs (NSAIDs), particularly aspirin, reduce the incidence of various cancer types. However, there is still a lack of literature evaluating the overall association between multiple cancer morbidities and NSAIDs. Thus, we conducted an umbrella review to evaluate the quality of evidence, validity, and biases of the existing systematic reviews and meta-analyses on the relationships between NSAIDS and multiple tumor incidence outcomes. We found that NSAIDs might be associated with a decreased risk of several cancers, including the central nervous system, breast, esophageal, gastric, head and neck, hepatocellular, cholangiocarcinoma, colorectal, endometrial, lung, ovary, prostate, and pancreatic cancers, but regular intake of any dose of non-aspirin NSAIDs (NA-NSAIDs) could increase the incidence of kidney cancer. However, most of included studies are evaluated as low quality according to our evidence assessment. Furthermore, due to the potential side effects, such as hemorrhage, digestive symptoms and peptic ulcer, it is still not recommend to use NSAIDs regularly to prevent cancers.

Novel hydrophobic butyl rubber damping composites modified with bio-based PF/DBA via the construction of a three-dimensional network.

It is of interest to develop wide-temperature domain damped hydrophobic materials. In this paper, we designed incorporating bio-based phenolic resin into the IIR matrix and introducing dibenzyl fork acetone (DBA) into the main chain structure with sodium hydroxide activation to construct three-dimensional network. In this paper, we designed incorporating bio-based phenolic resin into the IIR matrix and introducing dibenzyl fork acetone (DBA) into the main chain structure with sodium hydroxide activation to construct three-dimensional network. The added bio-based phenolic resin has reticulated structure blended with butyl rubber, combined with sodium hydride activation-modified IIR. The results show that sodium hydride activated modification of DBA is introduced into the main chain structure of IIR by infrared and 1H NMR analysis. The material hydrophobic is realized by the introduction of DBA with static water contact angle of 103.5°. The addition of 10phr lignin-based phenolic resin (LPF) is compatible with IIR, and the torque can reach 7.0 N-m. The tensile elongation of the modified butyl rubber composite can reach 2400% with tensile strength up to 11.43 MPa, while the damping factor can reach 0.37 even at 70 °C. The thermal stability of the composites is enhanced with mass retention rate of 28%. The bio-based PF/NaH activation-modified butyl rubber damping material has potential applications in damping hydrophobicity with wide temperature range.

The efficacy and safety of tislelizumab combined with gemcitabine plus cisplatin in the treatment of postoperative patients with muscle-invasive upper tract urothelial carcinoma.

BACKGROUND: A combination of immune checkpoint inhibitors (ICIs) and chemotherapy has demonstrated excellent clinical efficacy and safety in treating a variety of cancers, including urothelial carcinoma (UC). However, its efficacy and safety in patients with muscle-invasive upper tract urothelial carcinoma (UTUC) who are undergoing radical surgery remain uncertain. The purpose of this retrospective study was to examine the effectiveness and safety of tislelizumab combined with gemcitabine plus cisplatin (TGC) as a first-line postoperative adjuvant treatment in this population. METHODS: This single-center, real-world study retrospectively analyzed the data from 71 patients with muscle-invasive UTUC who had radical nephroureterectomy (RNU) at the Affiliated Hospital of Xuzhou Medical University between November 1, 2020, and November 1, 2023. Among the 71 patients, 30 received adjuvant therapy of TGC within 90 days after RNU and 41 underwent surveillance. No patients receive preoperative neoadjuvant therapy. The TGC therapy group received adjuvant therapy every 3 weeks postoperatively until the first recurrence, first metastasis, or death due to any reason, whichever occurred first. The patients were followed up telephonically and through outpatient visits to record and evaluate their disease-free survival (DFS) and treatment-related adverse events (TRAEs). RESULTS: This study assessed the DFS of 41 and 30 patients in the surveillance group and TGC therapy group, respectively. The median DFS of the surveillance group was 16.5 [95% confidence interval (CI), 14.7-18.3] months, while the median DFS of the TGC group has not yet reached [hazard ratio (HR) 0.367 (95% CI, 0.169-0.796); p = 0.008], with 21 patients still undergoing follow-up. Compared with the surveillance group, the TGC therapy group had dramatically improved DFS after RNU and reduced risk by 63.3%. Of the 30 patients receiving combination therapy, 28 experienced TRAEs; all TRAEs were consistent with the frequently reported events in the chemotherapy-alone regimens, and there were no treatment-related deaths. CONCLUSION: This study demonstrates that TGC therapy exhibits excellent clinical efficacy in patients undergoing radical surgery, significantly improving DFS and displaying great safety.