The development of novel topoisomerase I (TOP1) inhibitors is crucial for overcoming the drawbacks and limitations of current TOP1 poisons. Here, we identified two potential TOP1 inhibitors, namely, FTY720 (a sphingosine 1-phosphate antagonist) and COH29 (a ribonucleotide reductase inhibitor), through experimental screening of known active compounds. Biological experiments verified that FTY720 and COH29 were nonintercalative TOP1 catalytic inhibitors that did not induce the formation of DNA-TOP1 covalent complexes. Molecular docking revealed that FTY720 and COH29 interacted favorably with TOP1. Molecular dynamics simulations revealed that FTY720 and COH29 could affect the catalytic domain of TOP1, thus resulting in altered DNA-binding cavity size. The alanine scanning and interaction entropy identified Arg536 as a hotspot residue. In addition, the bioinformatics analysis predicted that FTY720 and COH29 could be effective in treating malignant breast tumors. Biological experiments verified their antitumor activities using MCF-7 breast cancer cells. Their combinatory effects with TOP1 poisons were also investigated. Further, FTY720 and COH29 were found to cause less DNA damage compared with TOP1 poisons. The findings provide reliable lead compounds for the development of novel TOP1 catalytic inhibitors and offer new insights into the potential clinical applications of FTY720 and COH29 in targeting TOP1.

UNASSIGNED: The objective of this study was to develop a fully automatic mass segmentation method called AMS-U-Net for digital breast tomosynthesis (DBT), a popular breast cancer screening imaging modality. The aim was to address the challenges posed by the increasing number of slices in DBT, which leads to higher mass contouring workload and decreased treatment efficiency.
UNASSIGNED: The study used 50 slices from different DBT volumes for evaluation. The AMS-U-Net approach consisted of four stages: image pre-processing, AMS-U-Net training, image segmentation, and post-processing. The model performance was evaluated by calculating the true positive ratio (TPR), false positive ratio (FPR), F-score, intersection over union (IoU), and 95% Hausdorff distance (pixels) as they are appropriate for datasets with class imbalance.
UNASSIGNED: The model achieved 0.911, 0.003, 0.911, 0.900, 5.82 for TPR, FPR, F-score, IoU, and 95% Hausdorff distance, respectively.
UNASSIGNED: The AMS-U-Net model demonstrated impressive visual and quantitative results, achieving high accuracy in mass segmentation without the need for human interaction. This capability has the potential to significantly increase clinical efficiency and workflow in DBT for breast cancer screening.

UNASSIGNED: We explored the role of maximum intensity projection (MIP) based on high frame rate contrast-enhanced ultrasound (H-CEUS) for the differentiation of breast tumors.
UNASSIGNED: MIP imaging was performed in patients with breast tumors who underwent H-CEUS examinations. The microvasculature morphology of breast tumors was assessed. The receiver operating characteristic curve was plotted to evaluate the diagnostic performance of MIP.
UNASSIGNED: Forty-three breast tumors were finally analyzed, consisting of 19 benign and 24 malignant tumors. For the ≤30-s and >30-s phases, dot-, line-, or branch-like patterns were significantly more common in benign tumors. A tree-like pattern was only present in the benign tumors. A crab claw-like pattern was significantly more common in the malignant tumors. Among the tumors with crab claw-like patterns, three cases of malignant tumors had multiple parallel small spiculated vessels. There were significant differences in the microvasculature morphology for the ≤30-s and >30-s phases between the benign and malignant tumors (all p < 0.001). The area under the curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the ≤30-s phase were all higher than those of the >30-s phase for the classification of breast tumors.
UNASSIGNED: MIP based on H-CEUS can be used for the differentiation of breast tumors, and the ≤30-s phase had a better diagnostic value. Multiple parallel small spiculated vessels were a new finding, which could provide new insight for the subsequent study of breast tumors.

UNASSIGNED: The differences in benign and malignant breast tumors are not only within the nodules but also involve changes in the surrounding tissues. Radiomics can reveal many details that are not discernible to the naked eye. This study aimed to distinguish between benign and malignant breast nodules using an ultrasound-based intra- and peritumoral radiomics model.
UNASSIGNED: This study retrospectively collected the information from 379 patients with Breast Imaging Reporting and Data System (BI-RADS) category 3-5 nodules and clear pathological diagnosis of breast nodules screened by routine ultrasound examination in the Sixth People\'s Hospital Affiliated to Medical College of Shanghai Jiao Tong University from January 2017 to December 2022. The largest dimension of the lesion on the 2D ultrasound image was selected to outline the area of interest which was conformally and outwardly expanded automatically by 5 mm to extract intra- and peritumor radiomics features. The included cases were randomly divided into training sets and test sets in a ratio of 7:3. The optimal features of the included models were retained by statistical and machine learning methods of dimensionality reduction, and logistic regression was used as the classifier to build an intratumoral model and a combined intratumoral-peritumoral radiomics model, respectively; through single-factor and multifactor logistic regression, the optimal features that could predict benign and malignant breast tumors were screened. The clinical and imaging models were established by selecting independent risk factors as clinical and imaging features through univariate and multifactorial logistic regression.
UNASSIGNED: Among 379 BI-RADS category 3-5 breast nodules, there were 124 malignant nodules and 255 benign nodules; patients were aged 14 to 88 (46.22±15.51) years, and the age differences, radiomics score, and mass diameter between the training and test sets were not statistically significant (P>0.05). The intra- and peritumor radiomics model had an area under the curve (AUC) of 0.840 [95% confidence interval (CI): 0.766-0.914] in the test set. The model with intra- and peritumoral ultrasound radiomics features combined with clinical features had an AUC value of 0.960 (95% CI: 0.920-0.999).
UNASSIGNED: The nomogram, developed using intratumoral and peritumoral radiomics features combined with clinical risk features, demonstrated superior performance in distinguishing between benign and malignant BI-RADS 3-5 lesions.

Breast cancer is considered as the most prevalent cancer. Using ultrasound images is a momentous clinical diagnosis method to locate breast tumors. However, accurate segmentation of breast tumors remains an open problem due to ultrasound artifacts, low contrast, and complicated tumor shapes in ultrasound images. To address this issue, we proposed a boundary-oriented network (BO-Net) for boosting breast tumor segmentation in ultrasound images. The BO-Net boosts tumor segmentation performance from two perspectives. Firstly, a boundary-oriented module (BOM) was designed to capture the weak boundaries of breast tumors by learning additional breast tumor boundary maps. Second, we focus on enhanced feature extraction, which takes advantage of the Atrous Spatial Pyramid Pooling (ASPP) module and Squeeze-and-Excitation (SE) block to obtain multi-scale and efficient feature information. We evaluate our network on two public datasets: Dataset B and BUSI. For the Dataset B, our network achieves 0.8685 in Dice, 0.7846 in Jaccard, 0.8604 in Precision, 0.9078 in Recall, and 0.9928 in Specificity. For the BUSI dataset, our network achieves 0.7954 in Dice, 0.7033 in Jaccard, 0.8275 in Precision, 0.8251 in Recall, and 0.9814 in Specificity. Experimental results show that BO-Net outperforms the state-of-the-art segmentation methods for breast tumor segmentation in ultrasound images. It demonstrates that focusing on boundary and feature enhancement creates more efficient and robust breast tumor segmentation.

UNASSIGNED: To evaluate the utility of apparent diffusion coefficient (ADC) values for differentiating breast tumors.
UNASSIGNED: The medical records of 17 patients with phyllodes tumor [PT; circular regions of interest (ROI-cs) n = 171], 74 patients with fibroadenomas (FAs; ROI-cs, n = 94), and 57 patients with breast cancers (BCs; ROI-cs, n = 104) confirmed by surgical pathology were retrospectively reviewed.
UNASSIGNED: There were significant differences between PTs, FAs, and BCs in ADCmean, ADCmax, and ADCmin values. The cutoff ADCmean for differentiating PTs from FAs was 1.435 × 10-3 mm2/s, PTs from BCs was 1.100 × 10-3 mm2/s, and FAs from BCs was 0.925 × 10-3 mm2/s. There were significant differences between benign PTs, borderline PTs, and malignant PTs in ADCmean, ADCmax, and ADCmin values. The cutoff ADCmean for differentiating benign PTs from borderline PTs was 1.215 × 10-3 mm2/s, and borderline PTs from malignant PTs was 1.665 × 10-3 mm2/s.
UNASSIGNED: DWI provides quantitative information that can help distinguish breast tumors.

OBJECTIVE: In recent years, breast cancer has become the greatest threat to women. There are many studies dedicated to the precise segmentation of breast tumors, which is indispensable in computer-aided diagnosis. Deep neural networks have achieved accurate segmentation of images. However, convolutional layers are biased to extract local features and tend to lose global and location information as the network deepens, which leads to a decrease in breast tumors segmentation accuracy. For this reason, we propose a hybrid attention-guided network (HAG-Net). We believe that this method will improve the detection rate and segmentation of tumors in breast ultrasound images.
METHODS: The method is equipped with multi-scale guidance block (MSG) for guiding the extraction of low-resolution location information. Short multi-head self-attention (S-MHSA) and convolutional block attention module are used to capture global features and long-range dependencies. Finally, the segmentation results are obtained by fusing multi-scale contextual information.
RESULTS: We compare with 7 state-of-the-art methods on two publicly available datasets through five random fivefold cross-validations. The highest dice coefficient, Jaccard Index and detect rate ([Formula: see text]%, [Formula: see text]%, [Formula: see text]% and [Formula: see text]%, [Formula: see text]%, [Formula: see text]%, separately) obtained on two publicly available datasets(BUSI and OASUBD), prove the superiority of our method.
CONCLUSIONS: HAG-Net can better utilize multi-resolution features to localize the breast tumors. Demonstrating excellent generalizability and applicability for breast tumors segmentation compare to other state-of-the-art methods.

The major challenges of photothermal therapy (PTT) toward clinical application are the severe skin injury and inflammation response associated with high power laser irradiation. Herein, polydopamine nanoparticles (PDA-EST and PDA-RAL) targeted to estrogen receptor α (ERα) for efficient ablation of breast tumor under a low irradiation density of 0.1 W cm-2 are reported. These nanoparticles are capable of recruiting ERα on their surface and induce a complete ERα degradation via localized heat. Owing to the ERα targetability, PDA-EST and PDA-RAL strongly suppress the proliferation of breast cancer cells without causing significant inflammation. This work provides a generalized method for enhancing PTT efficacy under low irradiation density.

For the biomedical application of engineered bacteria, strictly regulating the function of engineered bacteria has always been the goal pursued. However, the existing regulation methods do not meet the needs of the in vivo application of engineered bacteria. Therefore, the exploration of the precise regulation of engineered bacteria is necessary. Herein, heat-sensitive engineered bacteria that can respond to thermal stimuli within 30 min were constructed, and the precise control of functions was verified in the intestines of various model organisms (including C. elegans, bees, and mice). Subsequently, heat-sensitive engineered bacteria were shown to colonize the mouse tumor microenvironment. Finally, thermal stimulation was proven to control engineered bacteria to produce the therapeutic protein tumor necrosis factor α (TNF-α) in the tumor. After three heat stimulation treatments, the growth of the tumor was significantly inhibited, suggesting that heat can be used as a strategy to precisely control engineered bacteria in vivo.

The selective disruption of tumor-associated vasculature represents an attractive therapeutic approach. We have undertaken the first in vivo evaluation of KGP265, a water-soluble prodrug of a benzosuberene-based tubulin-binding agent, and found promising vascular-disrupting activity in three distinct tumor types. Dose escalation in orthotopic MDA-MB-231-luc breast tumor xenografts in mice indicated that higher doses produced more effective vascular shutdown, as revealed by dynamic bioluminescence imaging (BLI). In syngeneic orthotopic 4T1-luc breast and RENCA-luc kidney tumors, dynamic BLI and oxygen enhanced multispectral optoacoustic tomography (OE-MSOT) were used to compare vascular shutdown following the administration of KGP265 (7.5 mg/kg). The BLI signal and vascular oxygenation response (ΔsO2) to a gas breathing challenge were both significantly reduced within 2 h, indicating vascular disruption, which continued over 24 h. A correlative histology confirmed increased necrosis and hemorrhage. Twice-weekly doses of KGP265 caused significant growth delay in both MDA-MB-231 and 4T1 breast tumors, with no obvious systemic toxicity. A combination with carboplatin produced significantly greater tumor growth delay than carboplatin alone, though significant carboplatin-associated toxicity was observed (whole-body weight loss). KGP265 was found to be effective at low concentrations, generating long-term vascular shutdown and tumor growth delay, thus providing strong rationale for further development, particularly in combination therapies.