Application of carbon nanoparticles combined with refined extracapsular anatomy in endoscopic thyroidectomy.

Objective: To evaluate the value of refined extracapsular anatomy combined with carbon nanoparticle suspension tracing technology for protecting parathyroid function and the thoroughness of lymph node dissection in the central region during endoscopic thyroid cancer surgery. Patients and methods: Retrospective clinical data analysis was performed on 108 patients who underwent endoscopic thyroid cancer surgery at the First Affiliated Hospital of Wannan Medical College (Yijishan Hospital) from November 2019 to November 2022. Before surgery, thyroid function tests, color Doppler ultrasounds and neck-enhanced CT scans were performed on all patients. Cytopathological diagnosis obtained via ultrasound-guided fine-needle aspiration served as confirmation for the primary diagnosis. It was determined whether to perform a total thyroidectomy or a hemithyroidectomy (HT) together with preventive unilateral (ipsilateral) central neck dissection. Follow-up times were 1 to 34 months. Results: Transient neuromuscular symptoms were present in 3.70% (4/108) cases, with no permanent neuromuscular symptoms or permanent hypoparathyroidism. Regarding transient hypoparathyroidism, the patients recovered after three months and did not need long-term calcium supplementation. The number of harvested LNs (mean± SD) was 5.54 ± 3.84, with ≤5 in 57.41% (62/108) and >5 in 42.59% (46/108) cases. The number of patients with metastatic LNs was 37.96% (41/108), with ≤2 in 65.85% (27/41) and >2 in 34.15% (14/41) cases. Conclusions: Fine extracapsular anatomy combined with carbon nanoparticle suspension tracing is effective in endoscopic thyroid cancer surgery. It can improve the thoroughness of prophylactic central neck dissection and recognition of the parathyroid gland and avoid parathyroid injury and other complications to effectively protect parathyroid function.

PRAF2 is an oncogene acting to promote the proliferation and invasion of breast cancer cells.

Prenylated rab acceptor 1 domain family member 2 (PRAF2) acts as an oncogene and is closely related to the occurrence and development of various tumors. The present study aimed to clarify the functional relevance of PRAF2 in the biological behaviors of breast cancer by determining the expression of PRAF2 in breast cancer tissues and the corresponding adjacent tissues. The gene phenotypes of PRAF2 in patients with breast cancer in The Cancer Genome Atlas database were predicted using a cancer data online analysis website: The University of Alabama at Birmingham Cancer Data Analaysis Portal (UALCAN). The mRNA and protein expression of PRAF2 was further examined in 37 pairs of fresh frozen breast cancer tissues and adjacent non-tumor tissues by reverse transcription-quantitative PCR (RT-qPCR) and western blotting. High expression of PRAF2 was verified by RT-qPCR in the breast cancer cell line, MCF-7, and small interfering RNA (siRNA) technology was used to silence PRAF2. In the in vitro cell functional experiment, three groups were used: Negative control (NC) group, siRNA-NC group and siRNA-PRAF2 group. Cell Counting Kit-8 (CCK-8) and colony formation assays were conducted to analyze the effect of downregulation of PRAF2 on the proliferation of breast cancer cells. Transwell invasion and cell scratch assays were performed to examine the effect of downregulation of PRAF2 on the invasion and migration of breast cancer cells. UALCAN analysis results indicated that PRAF2 expression was upregulated in breast cancer compared with normal tissue samples (P<0.001). High expression of PRAF2 in breast cancer was associated with TNM stage and regional lymph node metastasis. RT-qPCR results showed increased mRNA expression of PRAF2 in clinical tissue samples from 37 patients with breast cancer, compared with normal adjacent tissues (P<0.001). Protein expression of PRAF2 was also shown to be higher in the breast cancer MCF-7 cells than in the MDA-MB-231 cells. Western blotting analysis combined with ImageJ software quantification showed that the relative expression of PRAF2 protein was significantly higher in clinical tissue samples from 37 patients with breast cancer (1.9750±0.0103) than that in normal adjacent tissues (0.9818±0.0140) (P<0.001). Western blotting analysis results indicated that transfection with siRNA PRAF2 in MCF-7 cells decreased PRAF2 expression (P<0.001). The results of CCK-8 and colony formation assays revealed that downregulation of PRAF2 expression suppressed the proliferation of MCF-7 cells (P<0.05 and P<0.001, respectively). In addition, Transwell invasion and cell scratch assay results showed that downregulation of PRAF2 expression in MCF-7 cells repressed invasion and migration of cancer cells (P<0.001). Overall, PRAF2 expression was significantly higher in breast cancer tissues than normal adjacent tissues, and was closely related to TNM stage and regional lymph node metastasis in breast cancer. PRAF2 was found to act as an oncogene that is able to promote breast cancer cell proliferation and invasion. Thus, PRAF2 may be a potential prognostic factor in patients with breast cancer and a potential target for the treatment of breast cancer metastasis.

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19.

The anti-epidemic supply chain plays an important role in the prevention and control of the COVID-19 pandemic. Prior research has focused on studying the facility location, inventory management, and route optimization of the supply chain by using certain parameters and models. Nevertheless, uncertainty, as a vital influence factor, greatly affects the supply chain. As such, the uncertainty that comes with technological innovation has a heightened influence on the supply chain. Few studies have explicitly investigated the influence of technological innovation on the anti-epidemic supply chain under the COVID-19 pandemic. Hence, the current research aims to investigate the influences of the uncertainty caused by technological innovation on the supply chain from demand and supply, shortage penalty, and budget. This paper presents a three-level model of the anti-epidemic supply chain under technological innovation and employs an interval data robust optimization to tackle the uncertainties of the model. The findings are obtained as follows. Firstly, the shortage penalty will increase the costs of the objective function but effectively improve demand satisfaction. Secondly, if the shortage penalty is sufficiently large, the minimum demand satisfaction rate can ensure a fair distribution of materials among the affected areas. Thirdly, technological innovation can reduce costs. The technological innovation related to the transportation costs of the anti-epidemic material distribution center has a greater influence on the optimal value. Meanwhile, the technological innovation related to the transportation costs of the supplier has the least influence. Fourthly, both supply and demand uncertainty can influence costs, but demand uncertainty has a greater influence. Fifthly, the multi-scenario budgeting approach can decrease the calculation complexity. These findings provide theoretical support for anti-epidemic dispatchers to adjust the conservativeness of uncertain parameters under the influence of technological innovation.