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The study of low-carbon multimodal transport path optimization problems considered in a fuzzy demand environment has important theoretical and practical significance in the situation of high-quality development. By analysing the demand uncertainty problem in the transport process, an improved simulated annealing genetic algorithm is designed to solve the model. The impact of various carbon policies on multimodal transport solutions, costs and carbon emissions is analysed through arithmetic examples. The results show that: 1) the improved simulated annealing genetic algorithm is better than the traditional genetic algorithm in terms of time finding and effect finding to achieve the lowest cost and lowest carbon emission; 2) the carbon tax policy is studied through the example and it is found that the carbon tax constraint is relatively lenient and the improper setting of carbon tax will lead to the increase of total cost; the model and algorithm proposed in this paper can provide theoretical support to the policy making departments and multimodal transport enterprises to optimise transport solutions. The model and algorithm proposed in this paper can provide a theoretical basis for policymaking authorities and multimodal transport enterprises to optimize transport solutions.

Purpose The important role of the androgen receptor (AR) in invasive carcinoma of no specific type (NST) has been increasingly recognised. However, only a few studies have been reported in special subtypes of breast cancer. Thus, we aim to investigate the AR expression and its expression features in special subtypes of breast cancer. Methods This study collected clinicopathological data of 718 special subtypes of breast cancer from Tianjin Medical University Cancer Institute and Hospital. Immunohistochemical staining of AR and other biomarkers was performed. Results If the threshold of AR is ≥ 1%, the positive rate of AR in specific subtypes of breast cancer is 77.9% (559/718) of cases. Compared with the threshold of AR is ≥ 10%, the positive percentage of AR in each subtype of breast cancer increases about 10%. The positive expression rate of AR in carcinomas with apocrine differentiation is highest, and the coloration intensity is much stronger than that of other subtypes. The positive expression rate of AR is lowest in metaplastic carcinomas, almost negative; the positive expression rate of AR in invasive lobular carcinomas (ILCs), invasive micropapillary carcinomas (IMPCs), invasive papillary carcinomas (IPCs), and is mucinous carcinomas about 70.0%–80.0%. Conclusions The expression features of AR in special subtypes of breast cancer vary in different subtypes, and to some extent, AR may be a useful biomarker for clinical diagnosis. Routine testing of AR has a certain guiding significance for clinical work. In addition, AR is expected to treat carcinomas with apocrine differentiation as a target.