Background: Neoadjuvant chemotherapy (NAC) is an important treatment for breast cancer (BC) patients.However, due to the lack of specific therapeutic targets, only 1/3 of human epidermal growth factor receptor 2 (HER2)-negative patients reach pathological complete response (pCR). Therefore, there is an urgent need to identify novel biomarkers to distinguish and predict NAC sensitive in BC patients.Methods: The GSE163882 dataset, containing 159 BC patients treated with NAC, was downloaded from the Gene Expression Omnibus (GEO) database. Patients with pathological complete response (pCR) and those with residual disease (RD) were compared to obtain the differentially expressed genes (DEGs).Functional enrichment analyses were conducted on these DEGs. Then, we intersect the DEGs and immunerelated genes to obtain the hub immune biomarkers, and then use the linear fitting model ("glm" package) to construct a prediction model composed of 9 immune biomarkers. Finally, the single sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze immune cell invasion in BC patients, and the correlation between immune cell content and immune gene expression levels was analyzed.Results: Nine immune-related biomarkers were obtained in the intersection of DEGs and immune-related genes. Compared with RD patients, CXCL9, CXCL10, CXCL11, CXCL13, GZMB, IDO1, and LYZ were highly expressed in pCR patients, while CXCL14 and ESR1 were lowly expressed in pCR patients. After linear fitting of the multi-gene expression model, the area under the curve (AUC) value of the ROC curve diagnosis of pCR patients was 0.844. Immunoinfiltration analysis showed that compared with RD patients, 15 of the 28 immune cell types examined showed high-infiltration in pCR patients, including activated CD8 T cells, effector memory CD8 T cells, and activated CD4 T cells.Conclusions: This investigation ultimately identified 9 immune-related biomarkers as potential tools for assessing the sensitivity of NAC in HER2-negative BC patients. These biomarkers have great potential for predicting pCR BC patients.

The flood propagation at a confluence of channels exhibits a unique routing pattern, while there are few studies on the routing of dam-break flow in confluent channels. In this study, we conducted physical experiments and a numerical simulation to investigate the influence of different confluence angles on the routing of a dam-break flood. Experiments were carried out in smooth, transparent, rectangular prismatic channels to study the dam-break flow under four different confluence angles. The flow velocity was measured using an image processing technique, and the surface flow field was effectively captured by synchronously recording the particle motion images. Based on the variation of the water level and flow discharge, as the confluence angle increased, the retardation and abatement effects on the flood increased. Specifically, the flood arrival time was delayed by approximately 0.91% to 21.18%, and the peak flood discharge was reduced by approximately 9.05% to 58.36%. Combined with the surface flow field at the confluence and in the downstream sections, as the confluence angle increased, the impact points at the confluence and in the downstream straight sections moved upward, and the impact range was reduced. Combined with the pressure variation pattern, the routing of dam-break flow in the confluent channels experienced a process of impact-reflection-return-attenuation.

In this study, we use a lattice Boltzmann method with a multi-relaxation-time model to simulate dam-break flooding in confluence channels with four confluence angles. Compared with physical experiment, the simulation proves reliable. We analyze the influence of the confluence angle on the propagation of dam-break flood. The stage hydrograph at the confluence area can be divided into four stages: before the wavefront reaches—rising rapidly—falling gradually—planarization with periodic fluctuation. The water depth of the measuring points in the confluence area is influenced by two factors: the confluence angle and the distance from the measuring point to the first impact point. The results demonstrate that the backwater effect of the confluence is enhanced at higher confluence angles. As the confluence angle increases, the first impact point moves upstream. Moreover, there is a strong backwater effect close to the first impact point, resulting in superelevation mainly occurring in the confluence area.

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