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Background: Triple negative breast cancer (TNBC) occurs in approximately 10% to 25% of all patients with breast cancer and is associated with poor prognosis. Neo-adjuvant chemotherapy has been reported to produce a higher pathologic complete response (pCR) rate in TNBC. If pCR is achieved, patients with TNBC had a similar survival with non-TNBC patients. The aim of our study was to investigate the protein expression of epithelial growth factor receptor (EGFR) and response to neo-adjuvant chemotherapy and clinical outcome in patients with TNBC compared with non-TNBC. Methods: A total of 198 locally advanced breast cancer patients who received neo-adjuvant chemotherapy were studied. Immunohistochemistry (IHC) was carried out to detect the protein expression of EGFR in tumor samples. Clinical and pathological parameters, pCR rate and survival data were compared between 40 TNBCs and 158 non- TNBCs. Results: In 198 cases who received neo-adjuvant chemotherapy, significant differences exist in surgical therapy (P=0.005) and pCR rate (P=0.012) between patients with TNBCs and non-TNBCs. Overexpression of EGFR was significantly associated with pCR rate in patients with TNBCs (P < 0.001). Survival analysis revealed that patients with TNBCs had worse DFS and OS than those with non-TNBCs (P = 0.001, P < 0.001 respectively). Furthermore, for patients with non-TNBCs, those who acheived pCR had better DFS and OS than those who acheived RD (both P < 0.001). Conclusions: Our results suggested that patients with TNBCs had increased pCR rates compared with non-TNBC. Overexpression of EGFR predicted better response to neo-adjuvant chemotherapy in patients with TNBCs. [ABSTRACT FROM AUTHOR]

Background: The study of DNA methylation quantitative trait loci (meQTLs) helps dissect regulatory mechanisms underlying genetic associations of human diseases. In this study, we conducted the first genome-wide examination of genetic drivers of methylation variation in response to a triglyceride-lowering treatment with fenofibrate (response-meQTL) by using an efficient analytic approach. Methods: Subjects (n = 429) from the GAW20 real data set with genotype and both pre- (visit 2) and post- (visit 4) fenofibrate treatment methylation measurements were included. Following the quality control steps of removing certain cytosine-phosphate-guanine (CpG) probes, the post−/premethylation changes (post/pre) were log transformed and the association was performed on 208,449 CpG sites. An additive linear mixed-effects model was used to test the association between each CpG probe and single nucleotide polymorphisms (SNPs) around ±1 Mb region, with age, sex, smoke, batch effect, and principal components included as covariates. Bonferroni correction was applied to define the significance threshold (p < 5.6 × 10− 10, given a total of 89,217,303 tests). Finally, we integrated our response-meQTL (re-meQTL) findings with the published genome-wide association study (GWAS) catalog of human diseases/traits. Results: We identified 1087 SNPs as cis re-meQTLs associated with 610 CpG probes/sites located in 351 unique gene loci. Among these 1087 cis re-meQTL SNPs, 229 were unique and 6 were co-localized at 8 unique disease/trait loci reported in the GWAS catalog (enrichment p = 1.51 × 10− 23). Specifically, a lipid SNP, rs10903129, located in intron regions of gene TMEM57, was a re-meQTL (p = 3.12 × 10− 36) associated with the CpG probe cg09222892, which is in the upstream region of the gene RHCE, indicating a new target gene for rs10903129. In addition, we found that SNP rs12710728 has a suggestive association with cg17097782 (p = 1.77 × 10− 4), and that this SNP is in high linkage disequilibrium (LD) (R2 > 0.8) with rs7443270, which was previously reported to be associated with fenofibrate response (p = 5.00 × 10− 6). Conclusions: By using a novel analytic approach, we efficiently identified thousands of cis re-meQTLs that provide a unique resource for further characterizing functional roles and gene targets of the SNPs that are most responsive to fenofibrate treatment. Our efficient analytic approach can be extended to large response quantitative trait locus studies with large sample sizes and multiple time points data. [ABSTRACT FROM AUTHOR]

The preparation of nanocages with unprecedented architectures may lead to new functions. Here the authors report the self-assembly of organic cages featuring twin cavities; the geometry and pocket size determine the molecular packing and the proton conductivity performance.

Periphyton sampling in hydrologically flexible regions is costly because of diverse substrates and fluctuating inundation time. It remains an open question whether periphytic algae samples in floodplain lakes may be obtained by sampling some representative natural substrates instead. To obtain the answer, algal biomass, richness, diversity, and community compositions were compared on 9 types of substrates in two investigations: in a small concrete pond and in the Poyang Lake, a large floodplain lake. Results in the pond showed that the algal Shannon index and species number on Potamogeton crispus and withered Typha orientalis were substantially higher than those on T. orientalis in March; the algal biomass on T. orientalis was considerably lower than that on the other substrates in June. Conversely, no significant differences in periphyton communities were found between substrate types in the Poyang Lake. However, the redundancy analysis revealed that water depth (positively related to the colonization time) plays a key role in shifting the algal community in the Lake. Thus, our results suggest that for a precise estimation of primary production, species richness, community composition, and ecological status assessment in large floodplain ecosystems, periphytic algae must be sampled not only on adequate substrate types but also on different depth gradients. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this study was to investigate the changes of tumor infiltrating lymphocytes (TILs) between core needle biopsy (CNB) and surgery removed sample (SRS) in early stage breast cancer patients and to identify the correlating factors and prognostic significance of TILs changes. Materials and Methods A retrospective study was carried out on 255 patients who received CNB and underwent surgical resection for invasive breast cancer. Stromal TILs levels of CNB and SRS were evaluated respectively. Tumors with ≥50% stromal TILs were defined as lymphocyte-predominant breast cancer (LPBC). Clinicopathological variables were analyzed to determine whether there were factors associated with TILs changes. Log-rank tests and Cox proportional hazards models were used to analyze the influences of TILs and TILs changes on survival. Results SRS-TILs (median, 10.0%) were significant higher than CNB-TILs (median, 5.0%; p<0.001). Younger age (<60 years, p=0.016) and long surgery time interval (STI, ≥4 days; p=0.003) were independent factors correlating with higher TILs changes. CNB-LPBC patients showed better breast cancer-free interval (BCFI, p=0.021) than CNB-non-LPBC (CNB-nLPBC) patients. Patients were categorized into four groups according to the LPBC change pattern from CNB to SRS: LPBC→LPBC, LPBC→nLPBC, nLPBC→LPBC, and nLPBC→nLPBC, with estimated 5-year BCFI 100%, 100%, 69.7%, and 86.0% (p=0.016). nLPBC→LPBC pattern was an independent prognostic factor of worse BCFI (hazard ratio, 2.19; 95% confidence interval, 1.06 to 4.53; p=0.035) compared with other patterns. Conclusion TILs were significantly higher in SRS than in CNB. Higher TILs changes were associated with younger age and long STI. Changing from nLPBC to LPBC after CNB indicated a worse BCFI, which needs further validation. [ABSTRACT FROM AUTHOR]

The NLR family apoptosis inhibitory proteins (NAIPs) bind conserved bacterial ligands, such as the bacterial rod protein PrgJ, and recruit NLR family CARD-containing protein 4 (NLRC4) as the inflammasome adapter to activate innate immunity. We found that the PrgJ-NAIP2-NLRC4 inflammasome is assembled into multisubunit disk-like structures through a unidirectional adenosine triphosphatase polymerization, primed with a single PrgJ-activated NAIP2 per disk. Cryo-electron microscopy (cryo-EM) reconstruction at subnanometer resolution revealed a ~90° hinge rotation accompanying NLRC4 activation. Unlike in the related heptameric Apaf-1 apoptosome, in which each subunit needs to be conformationally activated by its ligand before assembly, a single PrgJ-activated NAIP2 initiates NLRC4 polymerization in a domino-like reaction to promote the disk assembly. These insights reveal the mechanism of signal amplification in NAIP-NLRC4 inflammasomes. [ABSTRACT FROM AUTHOR]

Liver cancer stem cells (CSCs) have been identified and shown to have self-renewal and differentiation properties; however, the biology of these hepatic CSCs remains largely unknown. Here, we analyzed transcriptome gene expression profiles of liver CSCs and non-CSCs from hepatocellular carcinoma (HCC) cells lines and found that the transcription factor (TF) ZIC2 is highly expressed in liver CSCs. ZIC2 was required for the self-renewal maintenance of liver CSCs, as ZIC2 depletion reduced sphere formation and xenograft tumor growth in mice. We determined that ZIC2 acts upstream of the TF OCT4 and that ZIC2 recruits the nuclear remodeling factor (NURF) complex to the OCT4 promoter, thereby initiating OCT4 activation. In HCC patients, expression levels of the NURF complex were consistent with clinical severity and prognosis. Moreover, ZIC2 and OCT4 levels positively correlated to the clinicopathological stages of HCC patients. Altogether, our results indicate that levels of ZIC2, OCT4, and the NURF complex can be detected and used for diagnosis and prognosis prediction of HCC patients. Moreover, these factors may be potential therapeutic targets for eradicating liver CSCs. [ABSTRACT FROM AUTHOR]

According to the factors that influence flexible material processing (FMP), the deformation compensation modeling method based on T-S fuzzy neural network is proposed. This method combines T-S fuzzy reasoning with a fuzzy neural network. Firstly, fuzzy clustering is introduced to extract fuzzy membership functions and the fitness of fuzzy rules of T-S fuzzy neural network antecedent from the past processing data. Secondly, with the steepest descent method, back-propagation iteration is used to calculate the connection weights of the network. The processing of experiments shows that T-S fuzzy neural network modeling is superior to typical T-S model. The angle error and the straightness error processed by NTS-FNN is 40.4 %, 28.8 % lower than those of STS-FNN. The minimum processing time processed by NTS-FNN is lower by 46.1 % than that of STS-FNN. [ABSTRACT FROM AUTHOR]

Mechanical instrumentation preparation alone is insufficient to completely remove root canal infection, and chemical irrigation is essential to eliminate infected remnants. An ideal root canal irrigant should completely remove the smear layer, lubricate the root canal, efficiently kill bacteria, induce mild or no inflammatory response in the tissues, and avoid damaging the dentin structure. However, a commercial irrigant that meets all these requirements is currently lacking. QMix is a root canal irrigation mixture of ethylenediamine tetraacetic acid (EDTA), chlorhexidine (CHX) and surfactant. This mixture can remove the smear layer efficiently, and it possesses strong antibacterial effect and good biocompatibility with minimal cytotoxicity. Furthermore, the influence of QMix on the color and micro-hardness of dentin is low, and it can improve the wettability of root canal sealant without affecting its adhesive properties. This review compares the efficiencies of QMix with other irrigants (sodium hypochlorite, CHX, EDTA, SmearClear, and MTAD) in term of smear layer removal, dentine and root canal sealing, cell cytotoxicity, and bacterial growth inhibition.

Microaneurysms are regarded as the first signs of diabetic retinopathy (DR), but the microaneurysms are not clear in the color retinal images, and many researches were studied to detect and locate these lesions. In this paper, a new hierarchical computing-aided diagnosis approach is proposed for the microaneurysms detection by using the multi-scale and multi-orientation sum of matched filter (MMMF) and machine learning, where 37 dimensional features are extracted from each candidate. Furthermore, several classifiers such as the k-nearest neighbor (kNN), local linear discrimination analysis (LLDA) and support vector machine (SVM) are modified to distinguish the true microaneurysms from the false ones, which is a typical unbalanced classification problem. The effectiveness of the proposed method is verified through the training set of a publicly available database, and the experiment results show that the proposed method has better detection performance including the receiver operating characteristic (ROC) curve and the free-response receiver operating characteristic (FROC) curve. Moreover, the proposed method with 37 dimensional features outperforms that with other features and has a sensitivity from 1/8 to 8 with the average of all seven points being 0.286 tested on the same database.