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Metastasis is the most life-threatening complication in all cancers. The chemokine receptor 4 (CXCR4) is expressed at high levels in many breast-cancer tumors and may modulate metastasis. We compared the time-to-metastasis and the sites of metastasis between breast-cancer tumors expressing CXCR4 at high or low levels. We enrolled 191 early breast cancer patients in our study. The expression of CXCR4 was evaluated using immunohistochemical staining, and the patients were divided into low-level (CXCR4-) and high-level (CXCR4+) CXCR4 expression groups. Associations between the patients' level of CXCR4 expression and their basic clinical characteristics, time-to-metastasis, and metastatic sites were examined using a Cox proportional-hazards regression model. A total of 107 CXCR4+ patients (56 %) were identified. No statistical differences were evident in basic characteristics between the CXCR4+ and CXCR4- groups. The CXCR4+ group had a higher incidence of distant metastasis during the first year (10.3 % versus 1.1 %, P = 0.009) and shorter event-free survival (17.43 months versus 27.5 months, P = 0.026) than those of the CXCR4- group. The CXCR4+ group also had a higher incidence of bone metastasis (P = 0.008) than the CXCR4- group. No significant difference in metastasis sites in other organs was observed between the two groups. A high level of CXCR4 expression in breast cancer is associated with early distant and bone metastases. The CXCR4+ phenotype may be a useful predictor for the prevention of early treatment failure and bone metastasis in breast cancer patients. This retrospective study shows that a high expression of CXCR4 in breast cancer is associated with earlier distant metastasis and bone metastasis in breast cancer.

Many biological signalling pathways have evolved to produce responses to environmental signals that are robust to fluctuations in protein copy number and noise. Whilst beneficial for biology, this robustness can be problematic for synthetic biologists wishing to re-engineer and subsequently tune the response of a given system. Here we show that the well-characterized EnvZ/OmpR twocomponent signalling system from Escherichia coli possesses one such robust step response. However, the synthetic addition of just a single component into the system, an extra independently controllable phosphatase, can change this behaviour to become graded and tunable, and even show adaptation. Our approach introduces a new design principle which can be implemented simply in engineering and redesigning fast signal transduction pathways for synthetic biology.

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Using gene signature profiles to predict ACT benefit in NSCLC is feasible. The key to this analysis was identifying the pertinent genes and classification. This study maybe helps reduce the ineffective medical practices to avoid the waste of medical resources.

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Additive manufacturing, such as selective laser melting (SLM), can be used to manufacture cellular parts. In this study, cellular coupons of maraging steels are prepared through SLM by varying hatch distance. Air flow and permeability of porous maraging steel blocks are obtained for samples of different thickness based on the Darcy equation. By reducing hatch distance from 0.75 to 0.4 mm, the permeability decreases from 1.664 × 10−6 mm2 to 0.991 × 10−6 mm2 for 4 mm thick coupons. In addition, by increasing the thickness from 2 to 8 mm, the permeability increases from 0.741 × 10−6 mm2 to 1.345 × 10−6 mm2 at 16.2 J/mm3 energy density and 0.14 MPa inlet pressure. Simulation using ANSYS-Fluent is conducted to observe the pressure difference across the porous coupons and is compared with the experimental results. Surface artifacts and the actual morphology of scan lines can cause the simulated permeability to deviate from the experimental values. The measured permeability of maraging steel coupons is regression fit with both energy density and size of samples which provide a design guideline of porous mold inserts for industry applications such as injection molding.