Peripheral nerve injury may lead to the formation of a painful neuroma. In patients, palpating the tissue overlying a neuroma evokes paraesthesias/dysaesthesias in the distribution of the injured nerve. Previous animal models of neuropathic pain have focused on the mechanical hyperalgesia and allodynia that develops at a location distant from the site of injury and not on the pain from direct stimulation of the neuroma. We describe a new animal model of neuroma pain in which the neuroma was located in a position that is accessible to mechanical testing and outside of the innervation territory of the injured nerve. This allowed testing of pain in response to mechanical stimulation of the neuroma (which we call neuroma tenderness) independent of pain due to mechanical hyperalgesia. In the tibial neuroma transposition (TNT) model, the posterior tibial nerve was ligated and transected in the foot just proximal to the plantar bifurcation. Using a subcutaneous tunnel, the end of the ligated nerve was positioned just superior to the lateral malleolus. Mechanical stimulation of the neuroma produced a profound withdrawal behavior that could be distinguished from the hyperalgesia that developed on the hind paw. The neuroma tenderness (but not the hyperalgesia) was reversed by local lidocaine injection and by proximal transection of the tibial nerve. Afferents originating from the neuroma exhibited spontaneous activity and responses to mechanical stimulation of the neuroma. The TNT model provides a useful tool to investigate the differential mechanisms underlying the neuroma tenderness and mechanical hyperalgesia associated with neuropathic pain.

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Crossover between breast and ipsilateral arm lymphatic drainage system contributes for ipsilateral arm lymph node metastasis. When ARM and SLNB are simultaneously performed in a patient, selectively preservation of the ARM nodes that do not coincided with SLNs would be safe, even if the SLNs are positive. Pathological lymph node status does not account for the occurrence of metastasis in ARM nodes. ARM nodes could be preserved safely, independent of the pathological lymph node status.

Metastasis-associated in colon cancer-1 (MACC1) promotes colorectal cancer progression and predicts prognosis. The aim of our study was to determine the diagnostic and prognostic value of preoperative serum MACC1 levels in breast cancer patients. Serum MACC1 levels were measured in 378 breast cancer patients, 120 patients with benign breast disease, and 40 healthy volunteers using an ELISA. Serum MACC1 levels were higher in breast cancer patients than patients with benign disease or healthy volunteers. Increased serum MACC1 was associated with breast cancer TNM stage (P < 0.001), tumor size (P < 0.001), lymph node metastasis (P < 0.001), and Ki-67 status (P = 0.014). Serum MACC1 measurement successfully discriminated breast cancer patients from normal and healthy controls (AUC = 0.785, 95% CI: 0.746–0.825) with an optimal cut-off value of 38.35 pg/ml (sensitivity = 0.725, specificity = 0.696). Moreover, serum MACC1 exhibited significant prognostic value in breast cancer (AUC = 0.757, 95% CI: 0.700–0.814), and high MACC1 was associated with poor disease-free survival (HR 5.63, 95% CI: 3.51–9.04; P < 0.001). Our findings demonstrated that circulating MACC1 could serve as a reliable diagnostic and prognostic biomarker for breast cancer.

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Construction of an immune-related genes nomogram for the preoperative prediction of axillary lymph node metastasis in triple-negative breast cancer,

Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.