Predictive and prognostic role of tumour-infiltrating lymphocytes in breast cancer patients with different molecular subtypes: a meta-analysis.

BACKGROUND: Whether tumour-infiltrating lymphocytes (TILs) play different roles in different molecular subtypes of breast cancer remains unknown. Additionally, their prognostic and predictive value in different molecular subtypes of breast cancer is still controversial. The aim of our meta-analysis was to assess the prognostic and predictive value of TILs in different molecular subtypes of breast cancer by summarizing all relevant studies performing multivariate analysis. METHODS: PubMed, Embase, EBSCO, ScienceDirect, the Cochrane Database and Web of Science were comprehensively searched (until March 2020). Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were used as effect measures to perform our meta-analysis. A random effect model was used. Stata software, version 15 (2017) (StataCorp, College Station, TX, USA) was used to perform the statistical analysis. RESULTS: Thirty-three studies including 18,170 eligible breast cancer patients were analysed. The meta-analysis showed that high TIL expression was significantly associated with increased pathological complete response (pCR) rates after neoadjuvant chemotherapy in patients with the HER2-enriched molecular subtype (OR = 1.137, 95% CI [1.061 ~ 1.218], p < 0.001) and triple-negative breast cancer (TNBC) subtype (OR = 1.120, 95% CI [1.061 ~ 1.182], p < 0.001). However, high TIL expression was not significantly associated with high pCR rates after neoadjuvant chemotherapy in patients with the luminal molecular subtype of breast cancer (OR = 1.154, 95% CI [0.789 ~ 1.690], p = 0.460). We carried out a meta-analysis on the HRs of overall survival (OS) and disease-free survival (DFS) to assess the prognostic value of TILs in breast cancer with different molecular subtypes more deeply. Our meta-analysis confirmed that high TILs were associated with significantly improved DFS in patients with the HER2-enriched molecular subtype [HR = 0.940, 95% CI (0.903 ~ 0.979), p = 0.003] and TNBC molecular subtype [HR = 0.907, 95% CI (0.862 ~ 0.954), p < 0.001]. However, high TILs were not associated with significantly better DFS in patients with the luminal molecular subtype of breast cancer [HR = 0.998, 95% CI (0.977 ~ 1.019), p = 0.840]. Furthermore, the results confirmed that high TILs were significantly related to better OS in patients with the HER2-enriched molecular subtype [HR = 0.910, 95% CI (0.866 ~ 0.957), p < 0.001] and TNBC molecular subtype [HR = 0.869, 95% CI (0.836 ~ 0.904), p < 0.001]. Conversely, the summarized results indicated that high TILs were significantly associated with poor OS in patients with the luminal molecular subtype of breast cancer [HR = 1.077, 95% CI (1.016 ~ 1.141), p = 0.012]. CONCLUSIONS: Our meta-analysis confirms that high TILs are associated with favourable survival and predicts pCR in breast cancer patients with the TNBC and HER2-enriched molecular subtypes.

Two-Way: A Novel Method for Identifying the Anatomy During Uniportal Thoracoscopic Segmentectomy.

Because the segmental bronchi and vessels are commonly variable and complicated, it is difficult to correctly identify them. Misidentification of the segmental anatomy could result in the failure of segmentectomy and conversion to other surgical procedures such as bisegmentectomy or lobectomy. We describe a novel method to identify the target segmental vessels and bronchi by exposing the adjacent segmental anatomy during uniportal video-assisted thoracoscopic segmentectomy, which could help to reduce the chance of misidentification.

Antibacterial Composite Film-Based Triboelectric Nanogenerator for Harvesting Walking Energy.

As a green and eco-friendly technology, triboelectric nanogenerator (TENG) can harvest energy from human motion to generate electricity, so TENGs have been widely applied in wearable electronic devices to replace traditional batteries. However, the surface of these TENGs is easily contaminated and breeds bacteria, which is a threat to human health. Here, we report an antibacterial composite film-based triboelectric nanogenerator (ACF-TENG) that uses Ag-exchanged zeolite (Ag-zeolite) and polypropylene (PP) composite film as the triboelectric layer. Adding a small amount of Ag-zeolite with excellent antibacterial properties can increase the dielectric permittivity and improve the surface charge density of composite films, which enhances the output performance of the ACF-TENG. The open-circuit voltage (VOC), short-circuit current (ISC), and transferred charge (QTr) of the ACF-TENG are about 193.3, 225.4, and 233.3% of those of a pure PP film-based TENG, respectively. Because of the silver in the Ag-zeolite, the ACF-TENG can effectively kill Escherichia coli and fungi. When used in insoles, the ACF-TENG can resist the athlete's foot fungus effectively and work as a power source to light up light-emitting diodes and charge capacitors. The ACF-TENG has wide application prospects in self-powered medical and healthcare electronics.

Detection of persistent organic pollutants binding modes with androgen receptor ligand binding domain by docking and molecular dynamics.

BACKGROUND: Persistent organic pollutants (POPs) are persistent in the environment after release from industrial compounds, combustion productions or pesticides. The exposure of POPs has been related to various reproductive disturbances, such as reduced semen quality, testicular cancer, and imbalanced sex ratio. Among POPs, dichlorodiphenyldichloroethylene (4,4'-DDE) and polychlorinated biphenyls (PCBs) are the most widespread and well-studied compounds. Recent studies have revealed that 4,4'-DDE is an antagonist of androgen receptor (AR). However, the mechanism of the inhibition remains elusive. CB-153 is the most common congener of PCBs, while the action of CB-153 on AR is still under debate. RESULTS: Molecular docking and molecular dynamics (MD) approaches have been employed to study binding modes and inhibition mechanism of 4,4'-DDE and CB-153 against AR ligand binding domain (LBD). Several potential binding sites have been detected and analyzed. One possible binding site is the same binding site of AR natural ligand androgen 5α-dihydrotestosterone (DHT). Another one is on the ligand-dependent transcriptional activation function (AF2) region, which is crucial for the co-activators recruitment. Besides, a novel possible binding site was observed for POPs with low binding free energy with the receptor. Detailed interactions between ligands and the receptor have been represented. The disrupting mechanism of POPs against AR has also been discussed. CONCLUSIONS: POPs disrupt the function of AR through binding to three possible biding sites on AR/LBD. One of them shares the same binding site of natural ligand of AR. Another one is on AF2 region. The third one is in a cleft near N-terminal of the receptor. Significantly, values of binding free energy of POPs with AR/LBD are comparable to that of natural ligand androgen DHT.

Evolving model of amino acid networks.

The three-dimensional structure of a protein can be treated as a complex network composed of amino acids, and the network properties can help us to understand the relationship between structure and function. Since the amino acid network of a protein is formed in the process of protein folding, it is difficult for general network models to explain its evolving mechanism. Based on the perspective of protein folding, we propose an evolving model for amino acid networks. In our model, the evolution starts from the amino acid sequence of a native protein and it is guided by two generic assumptions: i.e., the neighbor preferential rule and the energy preferential rule. We find that the neighbor preferential rule predominates the general network properties and the energy preferential rule predominates the specific biological structure characteristics. Applied to native proteins, our model mimics the features of amino acid networks well.

Protein unfolding behavior studied by elastic network model.

Experimental and theoretical studies have showed that the native-state topology conceals a wealth of information about protein folding/unfolding. In this study, a method based on the Gaussian network model (GNM) is developed to study some properties of protein unfolding and explore the role of topology in protein unfolding process. The GNM has been successful in predicting atomic fluctuations around an energy minimum. However, in the GNM, the normal mode description is linear and cannot be accurate in studying protein folding/unfolding, which has many local minima in the energy landscape. To describe the nonlinearity of the conformational changes during protein unfolding, a method based on the iterative use of normal mode calculation is proposed. The protein unfolding process is mimicked through breaking the native contacts between the residues one by one according to the fluctuations of the distance between them. With this approach, the unfolding processes of two proteins, CI2 and barnase, are simulated. It is found that the sequence of protein unfolding events revealed by this method is consistent with that obtained from thermal unfolding by molecular dynamics and Monte Carlo simulations. The results indicate that this method is effective in studying protein unfolding. In this method, only the native contacts are considered, which implies that the native topology may play an important role in the protein unfolding process. The simulation results also show that the unfolding pathway is robust against the introduction of some noise, or stochastic characters. Furthermore, several conformations selected from the unfolding process are studied to show that the denatured state does not behave as a random coil, but seems to have highly cooperative motions, which may help and promote the polypeptide chain to fold into the native state correctly and speedily.