A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.

BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) using longitudinal MRI in breast cancer. METHODS: We included patients with node-positive breast cancer who received NAC following surgery from January 2012 to June 2022. We collected MRIs before and after NAC, and extracted radiomics features from the tumour, peritumour, and ALN regions. The Mann-Whitney U test, least absolute shrinkage and selection operator, and Boruta algorithm were used to select features. We utilised machine learning techniques to develop three single-modality models and a stacking model for predicting ALN response to NAC. RESULTS: This study consisted of a training cohort (n = 277), three external validation cohorts (n = 313, 164, and 318), and a prospective cohort (n = 81). Among the 1153 patients, 60.62% achieved ypN0. The stacking model achieved excellent AUCs of 0.926, 0.874, and 0.862 in the training, external validation, and prospective cohort, respectively. It also showed lower false-negative rates (FNRs) compared to radiologists, with rates of 14.40%, 20.85%, and 18.18% (radiologists: 40.80%, 50.49%, and 63.64%) in three cohorts. Additionally, there was a significant difference in disease-free survival between high-risk and low-risk groups (p < 0.05). CONCLUSIONS: The stacking model can accurately predict ALN status after NAC in breast cancer, showing a lower false-negative rate than radiologists. TRIAL REGISTRATION NUMBER: The clinical trial numbers were NCT03154749 and NCT04858529.

Bifonazole caffeate: The first molecular salt of bifonazole with enhanced biopharmaceutical property based on experiments and quantum chemistry research.

In order to make novel breakthroughs in molecular salt studies of BCS class-IV antifungal medication bifonazole (BIF), a salification-driven strategy towards ameliorating attributes and aiding augment efficiency is raised. This strategy fully harnesses structural characters together attributes and benefits of caffeic acid (CAF) to concurrently enhance dissolvability and permeability of BIF by introducing the two ingredients into the identical molecular salt lattice through the salification reaction, which, coupled with the aroused potential activity of CAF significantly amplifies the antifungal efficacy of BIF. Guided by this route, the first BIF-organic molecular salt, BIF-CAF, is directionally designed and synthesized with satisfactorily structural characterizations and integrated theoretical and experimental explorations on the pharmaceutical properties. Single-crystal X-ray diffraction resolving confirms that there is a lipid-water amphiphilic sandwich structure constructed by robust charge-assistant hydrogen bonds in the salt crystal, endowing the molecular salt with the potential to enhance both dissolvability and permeability relative to the parent drug, which is validated by experimental evaluations. Remarkably, the comprehensive DFT-based theoretical investigations covering frontier molecular orbital, molecular electrostatic potential, Hirshfeld surface analysis, reduced density gradient, topology, sphericity and planarity analysis strongly support these observations, thereby allowing some positive relationships between macroscopic properties and microstructures of the molecular salt can be made. Intriguingly, the optimal properties, together with the stimulated activity of CAF markedly augment in vitro antifungal ability of the molecular salt, with magnifying inhibition zones and reducing minimum inhibitory concentrations. These findings fill in the gaps on researches of BIF-organic molecular salt, and adequately exemplify the feasibility and validity by integrating theoretical and experimental approaches to resolve BIF's problems via the salification-driven tactic.

Noninvasive Artificial Intelligence System for Early Predicting Residual Cancer Burden during Neoadjuvant Chemotherapy in Breast Cancer.

OBJECTIVE: To develop an artificial intelligence (AI) system for the early prediction of residual cancer burden (RCB) scores during neoadjuvant chemotherapy (NAC) in breast cancer. SUMMARY BACKGROUND DATA: RCB III indicates drug resistance in breast cancer, and early detection methods are lacking. METHODS: This study enrolled 1048 patients with breast cancer from four institutions, who were all receiving NAC. Magnetic resonance images were collected at the pre- and mid-NAC stages, and radiomics and deep learning features were extracted. A multitask AI system was developed to classify patients into three groups (RCB 0-I, II, and III ) in the primary cohort (PC, n=335). Feature selection was conducted using the Mann-Whitney U- test, Spearman analysis, least absolute shrinkage and selection operator regression, and the Boruta algorithm. Single-modality models were developed followed by model integration. The AI system was validated in three external validation cohorts. (EVCs, n=713). RESULTS: Among the patients, 442 (42.18%) were RCB 0-I, 462 (44.08%) were RCB II and 144 (13.74%) were RCB III. Model-I achieved an area under the curve (AUC) of 0.975 in the PC and 0.923 in the EVCs for differentiating RCB III from RCB 0-II. Model-II distinguished RCB 0-I from RCB II-III, with an AUC of 0.976 in the PC and 0.910 in the EVCs. Subgroup analysis confirmed that the AI system was consistent across different clinical T stages and molecular subtypes. CONCLUSIONS: The multitask AI system offers a noninvasive tool for the early prediction of RCB scores in breast cancer, supporting clinical decision-making during NAC.

KAT8/SIRT7-mediated Fascin-K41 acetylation/deacetylation regulates tumor metastasis in esophageal squamous cell carcinoma.

Fascin actin-bundling protein 1 (Fascin) is highly expressed in a variety of cancers, including esophageal squamous cell carcinoma (ESCC), working as an important oncogenic protein and promoting the migration and invasion of cancer cells by bundling F-actin to facilitate the formation of filopodia and invadopodia. However, it is not clear how exactly the function of Fascin is regulated by acetylation in cancer cells. Here, in ESCC cells, the histone acetyltransferase KAT8 catalyzed Fascin lysine 41 (K41) acetylation, to inhibit Fascin-mediated F-actin bundling and the formation of filopodia and invadopodia. Furthermore, NAD-dependent protein deacetylase sirtuin (SIRT) 7-mediated deacetylation of Fascin-K41 enhances the formation of filopodia and invadopodia, which promotes the migration and invasion of ESCC cells. Clinically, the analysis of cancer and adjacent tissue samples from patients with ESCC showed that Fascin-K41 acetylation was lower in the cancer tissue of patients with lymph node metastasis than in that of patients without lymph node metastasis, and low levels of Fascin-K41 acetylation were associated with a poorer prognosis in patients with ESCC. Importantly, K41 acetylation significantly blocked NP-G2-044, one of the Fascin inhibitors currently being clinically evaluated, suggesting that NP-G2-044 may be more suitable for patients with low levels of Fascin-K41 acetylation, but not suitable for patients with high levels of Fascin-K41 acetylation. © 2024 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Tanshinone IIA attenuates osteoarthritis via inhibiting aberrant angiogenesis in subchondral bone.

Excessive angiogenesis in subchondral bone is a pathological feature of osteoarthritis (OA). Tanshinone IIA (TIIA), an active compound found in Salvia miltiorrhiza, demonstrates significant anti-angiogenic properties. However, the effect of TIIA on abnormal subchondral angiogenesis in OA is still unclear. This study aims to investigate the mechanism of TIIA in modulating subchondral bone angiogenesis during OA and assess its therapeutic potential in OA. Our findings demonstrate that TIIA attenuated articular cartilage degeneration, normalized subchondral bone remodeling, and effectively suppressed aberrant angiogenesis within subchondral bone in monosodium iodoacetate (MIA)-induced OA mice. Additionally, the angiogenesis capacity of primary CD31hiEmcnhi endothelial cells was observed to be significantly reduced after treatment with TIIA in vitro. Mechanically, TIIA diminished the proportion of hypertrophic chondrocytes, ultimately leading to a substantial reduction in the secretion of vascular endothelial growth factor A (VEGFA). The supernatant of hypertrophic chondrocytes promoted the tube formation of CD31hiEMCNhi endothelial cells, whereas TIIA inhibited this process. Furthermore, TIIA effectively suppressed the expression of vascular endothelial growth factor receptor 2 (VEGFR2) along with its downstream MAPK pathway in CD31hiEmcnhi endothelial cells. In conclusion, our data indicated that TIIA could effectively inhibit the abnormal angiogenesis in subchondral bone during the progression of OA by suppressing the VEGFA/VEFGR2/MAPK pathway. These findings significantly contribute to our understanding of the abnormal angiogenesis in OA and offer a promising therapeutic target for OA treatment.

Fast and sensitive smartphone colorimetric detection of whole blood samples on a paper-based analytical device.

BACKGROUND: Methods based on paper-based analytical devices (PAD) and smartphone photographic colorimetric detection have become representative instrument-independent point-of-care testing (POCT) platforms due to their low cost and simplicity. However, the detection of target components from whole blood sample still presents challenges in terms of field preparation of small amounts of blood sample and detection sensitivity. This paper presents a rapid online processing method for whole blood samples on PAD based on plasma separation membrane (PSM), and combined with electrokinetic stacking and selective chromatic reaction. Real-time smartphone-based colorimetric detection of free hemoglobin (FHb) and human serum albumin (HSA) was successfully demonstrated. RESULTS: With the proposed method, both detections for low and high concentration analytes could be implemented. The limits of detection of 16.6 mg L-1 for FHb and 0.67 g L-1 for HSA were obtained, respectively, with RSD below 8 %. The reliability of the method was verified by the recovery test and desktop spectrophotometric method. The detection results for real blood samples were in agreement with that by clinical methods. SIGNIFICANCE AND NOVELTY: The PAD method is inexpensive, simple and fast, and detection of a whole blood sample of 5 µL can be finished in 5 min. This work shows that POCT of biomarkers from whole blood with PAD is possible without using any desktop facilities.