Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept.

BACKGROUND AND AIM: 3D fusion model of cone-beam computed tomography (CBCT) and oral scanned data can be used for the accurate design of root canal access and guide plates in root canal therapy (RCT). However, the pose accuracy of the dental pulp and crown in data registration has not been investigated, which affects the precise implementation of clinical planning goals. We aimed to establish a novel registration method based on pulp horn mapping surface (PHMSR), to evaluate the accuracy of PHMSR versus traditional methods for crown-pulp registration of CBCT and oral scan data. MATERIALS AND METHODS: This vitro study collected 8 groups of oral scanned and CBCT data in which the left mandibular teeth were not missing, No. 35 and No. 36 teeth were selected as the target teeth. The CBCT and scanned model were processed to generate equivalent point clouds. For the PHMSR method, the similarity between the feature directions of the pulp horn and the surface normal vectors of the crown were used to determine the mapping points in the CBCT point cloud that have a great influence on the pulp pose. The small surface with adjustable parameters is reconstructed near the mapping point of the crown, and the new matching point pairs between the point and the mapping surface are searched. The sparse iterative closest point (ICP) algorithm is used to solve the new matching point pairs. Then, in the C + + programming environment with a point cloud library (PCL), the PHMSR, the traditional sparse ICP, ICP, and coherent point drift (CPD) algorithms are used to register the point clouds under two different initial deviations. The root square mean error (RSME) of the crown, crown-pulp orientation deviation (CPOD), and position deviation (CPPD) were calculated to evaluate the registration accuracy. The significance between the groups was tested by a two-tailed paired t-test (p < 0.05). RESULTS: The crown RSME values of the sparse ICP method (0.257), the ICP method (0.217), and the CPD method (0.209) were not significantly different from the PHMSR method (0.250). The CPOD and CPPD values of the sparse ICP method (4.089 and 0.133), the ICP method (1.787 and 0.700), and the CPD method (1.665 and 0.718) than for the PHMSR method, which suggests that the accuracy of crown-pulp registration is higher with the PHMSR method. CONCLUSION: Compared with the traditional method, the PHMSR method has a smaller crown-pulp registration accuracy and a clinically acceptable deviation range, these results support the use of PHMSR method instead of the traditional method for clinical planning of root canal therapy.

Current and Future Perspectives of Cell-Free DNA in Liquid Biopsy.

A liquid biopsy is a minimally invasive or non-invasive method to analyze a range of tumor material in blood or other body fluids, including circulating tumor cells (CTCs), cell-free DNA (cfDNA), messenger RNA (mRNA), microRNA (miRNA), and exosomes, which is a very promising technology. Among these cancer biomarkers, plasma cfDNA is the most widely used in clinical practice. Compared with a tissue biopsy of traditional cancer diagnosis, in assessing tumor heterogeneity, a liquid biopsy is more reliable because all tumor sites release cfDNA into the blood. Therefore, a cfDNA liquid biopsy is less invasive and comprehensive. Moreover, the development of next-generation sequencing technology makes cfDNA sequencing more sensitive than a tissue biopsy, with higher clinical applicability and wider application. In this publication, we aim to review the latest perspectives of cfDNA liquid biopsy clinical significance and application in cancer diagnosis, treatment, and prognosis. We introduce the sequencing techniques and challenges of cfDNA detection, analysis, and clinical applications, and discuss future research directions.

Ferroptosis assassinates tumor.

In 2020, nearly 20 million peoples got cancer and nearly 10 million peoples died of cancer, indicating the cancer remains a great threat to human health and life. New therapies are still in urgent demand. We here develop a novel cancer therapy named Ferroptosis ASsassinates Tumor (FAST) by combining iron oxide nanoparticles with cancer-selective knockdown of seven key ferroptosis-resistant genes (FPN, LCN2, FTH1, FSP1, GPX4, SLC7A11, NRF2). We found that FAST had notable anti-tumor activity in a variety of cancer cells but little effect on normal cells. Especially, FAST eradicated three different types of tumors (leukemia, colon cancer, and lung metastatic melanoma) from over 50% of cancer mice, making the mice survive up to 250 days without tumor relapse. FAST also significantly inhibited and prevented the growth of spontaneous breast cancer and improved survival in mice. FAST showed high pan anti-tumor efficacy, high cancer specificity, and in vivo safety. FAST defines a new form of advanced nanomaterials, advanced combinatorial nanomaterials, by combining two kinds of nanomaterials, a chemical nanomaterial (iron oxide nanoparticles) and a biochemical nanomaterial (adeno-associated virus), which successfully turns a general iron nanomaterial into an unprecedented assassin to cancer.

Automatic Liver Segmentation Using EfficientNet and Attention-Based Residual U-Net in CT.

This paper proposes a new network framework, which leverages EfficientNetB4, attention gate, and residual learning techniques to achieve automatic and accurate liver segmentation. First, we use EfficientNetB4 as the encoder to extract more feature information during the encoding stage. Then, an attention gate is introduced in the skip connection to eliminate irrelevant regions and highlight features of a specific segmentation task. Finally, to alleviate the problem of gradient vanishment, we replace the traditional convolution of the decoder with a residual block to improve the segmentation accuracy. We verified the proposed method on the LiTS17 and SLiver07 datasets and compared it with classical networks such as FCN, U-Net, attention U-Net, and attention Res-U-Net. In the Sliver07 evaluation, the proposed method achieved the best segmentation performance on all five standard metrics. Meanwhile, in the LiTS17 assessment, the best performance is obtained except for a slight inferior on RVD. The proposed method's qualitative and quantitative results demonstrated its applicability in liver segmentation and proved its good prospect in computer-assisted liver segmentation.

Alterations in Plasma Lipidomic Profiles in Adult Patients with Schizophrenia and Major Depressive Disorder.

Background and Objectives: Lipidomics is a pivotal tool for investigating the pathogenesis of mental disorders. However, studies qualitatively and quantitatively analyzing peripheral lipids in adult patients with schizophrenia (SCZ) and major depressive disorder (MDD) are limited. Moreover, there are no studies comparing the lipid profiles in these patient populations. Materials and Method: Lipidomic data for plasma samples from sex- and age-matched patients with SCZ or MDD and healthy controls (HC) were obtained and analyzed by liquid chromatography-mass spectrometry (LC-MS). Results: We observed changes in lipid composition in patients with MDD and SCZ, with more significant alterations in those with SCZ. In addition, a potential diagnostic panel comprising 103 lipid species and another diagnostic panel comprising 111 lipid species could distinguish SCZ from HC (AUC = 0.953) or SCZ from MDD (AUC = 0.920) were identified, respectively. Conclusions: This study provides an increased understanding of dysfunctional lipid composition in the plasma of adult patients with SCZ or MDD, which may lay the foundation for identifying novel clinical diagnostic methods for these disorders.

A random forest based computational model for predicting novel lncRNA-disease associations.

BACKGROUND: Accumulated evidence shows that the abnormal regulation of long non-coding RNA (lncRNA) is associated with various human diseases. Accurately identifying disease-associated lncRNAs is helpful to study the mechanism of lncRNAs in diseases and explore new therapies of diseases. Many lncRNA-disease association (LDA) prediction models have been implemented by integrating multiple kinds of data resources. However, most of the existing models ignore the interference of noisy and redundancy information among these data resources. RESULTS: To improve the ability of LDA prediction models, we implemented a random forest and feature selection based LDA prediction model (RFLDA in short). First, the RFLDA integrates the experiment-supported miRNA-disease associations (MDAs) and LDAs, the disease semantic similarity (DSS), the lncRNA functional similarity (LFS) and the lncRNA-miRNA interactions (LMI) as input features. Then, the RFLDA chooses the most useful features to train prediction model by feature selection based on the random forest variable importance score that takes into account not only the effect of individual feature on prediction results but also the joint effects of multiple features on prediction results. Finally, a random forest regression model is trained to score potential lncRNA-disease associations. In terms of the area under the receiver operating characteristic curve (AUC) of 0.976 and the area under the precision-recall curve (AUPR) of 0.779 under 5-fold cross-validation, the performance of the RFLDA is better than several state-of-the-art LDA prediction models. Moreover, case studies on three cancers demonstrate that 43 of the 45 lncRNAs predicted by the RFLDA are validated by experimental data, and the other two predicted lncRNAs are supported by other LDA prediction models. CONCLUSIONS: Cross-validation and case studies indicate that the RFLDA has excellent ability to identify potential disease-associated lncRNAs.

Cancer gene therapy by NF-κB-activated cancer cell-specific expression of CRISPR/Cas9 targeting telomeres.

The transcription factor NF-κB is an attractive target for cancer therapy due to its over-activation in all tumours; however, NF-κB inhibitors developed in the past decades rarely became drugs due to undesirable side effects. In this study, we developed a gene therapy strategy named NF-κB-activated gene expression (Nage), which could induce the death of cancer cells in vitro and in vivo by utilising NF-κB over-activity in cancer cells, but had no effects on normal cells. Nage was consisted of an NF-κB-specific promoter formed by fusing an NF-κB decoy sequence with a minimal promoter, which could be bound by the intracellular over-activated NF-κB and thus activated the expression of downstream effector genes in an NF-κB-specific manner. In this study, we first confirmed the cancer cell-specific over-activation of NF-κB and then tested the cancer cell specificity of the Nage vector by expressing the reporter gene ZsGreen in various in vitro cultivated cells. We next demonstrated that the Nage vector could be used to express CRISPR/Cas9 protein only in cancer cells. The Cas9 protein was then guided by a sgRNA targeting telomeric DNA and induced cancer cell death. The Nage vector expressing Cas9/sgRNA could be packaged into adeno-associated virus (AAV) and intravenously injected to inhibit tumour growth in mice without visible side effects and toxicity.

Upregulation of CASP9 through NF-κB and Its Target MiR-1276 Contributed to TNFα-promoted Apoptosis of Cancer Cells Induced by Doxorubicin.

：Under some conditions, nuclear factor-κB (NF-κB) has a pro-apoptotic role, but the mechanisms underlying this function remain unclear. This study demonstrated that NF-κB directly binds to CASP9 and miR1276 in tumor necrosis factor α (TNFα)-treated HeLa and HepG2 cells. NF-κB upregulated CASP9 expression, whereas downregulated miR1276 expression in the TNFα-treated cells. The miR1276 repressed CASP9 expression in both cells. As a result, a typical NF-κB-mediated coherent feed-forward loop was formed in the TNFα-treated cells. It was proposed that the NF-κB-mediated loop may contribute to cell apoptosis under certain conditions. This opinion was supported by the following evidence: TNFα promoted the apoptosis of HeLa and HepG2 cells induced by doxorubicin (DOX). CASP9 was significantly upregulated and activated by TNFα in the DOX-induced cells. Moreover, a known inhibitor of CASP9 activation significantly repressed the TNFα promotion of apoptosis induced by DOX. These findings indicate that CASP9 is a new mediator of the NF-κB pro-apoptotic pathway, at least in such conditions. This study therefore provides new insights into the pro-apoptotic role of NF-κB. The results also shed new light on the molecular mechanism underlying TNFα-promotion of cancer cells apoptosis induced by some anticancer drugs such as DOX.

Decoding genetic and epigenetic information embedded in cell free DNA with adapted SALP-seq.

Cell free DNA (cfDNA) in human plasma carries abundant information, which has therefore been the key sample for noninvasive prenatal testing (NIPT) and liquid biopsy. Especially by using the rapidly developed next-generation sequencing (NGS) techniques, the genetic and epigenetic information embedded in cfDNA has been effectively and extensively decoded. In this process, a key step is to construct the NGS library. Due to its high degradation, the single strand-based method was reported to be more qualified to construct the NGS library of cfDNA. In order to develop a new simple method for this application, this study adapted our recently developed single strand adaptor library preparation (SALP) method for constructing an NGS library of cfDNA. In the improved method, cfDNA was firstly denatured into single strands and then ligated with a single strand adaptor (SSA) that had a 3' overhang of 3 random bases by using T4 DNA ligase. The SSA-ligated DNA was converted into double-stranded DNA with an additional adenine at the other end by polymerizing with Taq polymerase. Next, a barcode T adaptor (BTA) was ligated to this end. Finally, the cfDNA ligated with two adaptors was amplified with the Illumina-compatible primers for NGS. Using the method, this study successfully sequenced 20 cfDNA samples from 16 esophageal cancer patients and 4 healthy people. By bioinformatics analysis, this study found the genetic and epigenetic difference between patients and healthy people and identified 23 epigenetic and 28 genetic altered esophageal cancer-specific genes.

A Highly Ionic Conductive, Healable, and Adhesive Polysiloxane-Supported Ionogel.

A new kind of polysiloxane-supported ionogel is successfully designed via locking ionic liquids (ILs), 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2 N]), into poly(aminopropyl-methylsiloxane) (PAPMS) grafted with [2-(methacryloyloxy)ethyl] trimethylammonium chloride (METAC) in the presence of tannic acid (TA). The novel ionogel exhibits good mechanical and recovery properties, as well as high ionic conductivity (1.19 mS cm-1 ) at 25 °C. In addition, the totally physical dual-crosslinked network based on ionic aggregates among METAC and the hydrogen bonds between PAPMS and TA provides excellent self-healing ability, which allows the damaged ionogel to almost completely heal (≈83%) in 12 h at room temperature. Interestingly, the obtained ionogel also shows satisfactory adhesive behavior to various solid materials. Moreover, this novel ionogel can maintain its high ionic conductivity and recovery property even at subzero temperatures. Therefore, this polysiloxane-supported ionogel is anticipated to be advantageous in flexible electronic devices such as sensors and supercapacitors, even at low temperatures.

SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states.

BACKGROUND: Next-generation sequencing (NGS) is fundamental to the current biological and biomedical research. Construction of sequencing library is a key step of NGS. Therefore, various library construction methods have been explored. However, the current methods are still limited by some shortcomings. RESULTS: This study developed a new NGS library construction method, Single strand Adaptor Library Preparation (SALP), by using a novel single strand adaptor (SSA). SSA is a double-stranded oligonucleotide with a 3' overhang of 3 random nucleotides, which can be efficiently ligated to the 3' end of single strand DNA by T4 DNA ligase. SALP can be started with any denatured DNA fragments such as those sheared by Tn5 tagmentation, enzyme digestion and sonication. When started with Tn5-tagmented chromatin, SALP can overcome a key limitation of ATAC-seq and become a high-throughput NGS library construction method, SALP-seq, which can be used to comparatively characterize the chromatin openness state of multiple cells unbiasly. In this way, this study successfully characterized the comparative chromatin openness states of four different cell lines, including GM12878, HepG2, HeLa and 293T, with SALP-seq. Similarly, this study also successfully characterized the chromatin openness states of HepG2 cells with SALP-seq by using 105 to 500 cells. CONCLUSIONS: This study developed a new NGS library construction method, SALP, by using a novel kind of single strand adaptor (SSA), which should has wide applications in the future due to its unique performance.

Correction to: SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states.

After publication of the original article [1] the authors noted that the additional files had not been uploaded correctly.

Detecting and typing target DNA with a novel CRISPR-typing PCR (ctPCR) technique.

This study develops a new method for detecting and typing the interested DNAs based on CRISPR, which was named as ctPCR3.0, representing CRISPR- or Cas9/sgRNA-typing PCR, version 3.0. This technique detects target DNA in just one homogeneous step: quantitative PCR (qPCR) amplifying the Cas9/sgRNA-cleaved DNA samples. By directly adding Cas9 and sgRNA into the qPCR reaction and giving an additional isothermal incubation before qPCR program, the target DNA can be homogeneously detected in as few as 2 h. Without opening the detecting tube in the whole detection process, ctPCR3.0 can be used to detect target DNA as the traditional qPCR detection. The technique was fully verified by detecting the cloned HPV L1 genes of 10 high-risk human papillomavirus (HPV) subtypes. The technique also successfully detected the L1 and E6-E7 genes of two highest-risk HPVs, HPV16 and HPV18, in the genomic DNA of two HPV-positive cervical carcinoma cells, HeLa and SiHa. Finally, the ctPCR3.0 method was validated by successfully detecting HPVs in many clinical samples. By performing these detections, this study thus provides a new CRISPR-based DNA detection and typing platform and a ready-to-use HPV clinical detection technique. The platform has wide application in clinical diagnosis.

Improving transcriptional activity of human cytomegalovirus major immediate-early promoter by mutating NF-κB binding sites.

Many mammalian gene expression vectors express the transferred genes under the control of the cytomegalovirus (CMV) major immediate-early promoter (MIEP). The human MIEP has been known as the strongest promoter in mammalian cells and utilized widely in mammalian expression systems. There are four NF-κB binding sites (named as κBs) in the human MIEP. In this study, we have constructed multiple mutated MIEPs by changing the natural κBs in the human MIEP into the high-affinity artificial sequences that were in vitro selected by using systematic evolution of ligands by exponential enrichment (SELEX) and predicted by bioinformatics. With various transcriptional activity evaluations, we found three mutated MIEPs with the transcriptional activity higher than the wild-type MIEP, which should be useful and widely applicable in many mammalian transgene expression fields such as gene engineering, gene therapy and gene editing. This study provides a useful approach for promoter engineering in biotechnology. This study also produced a series of mutated MIEPs with various transcriptional activities, which may be used for the fine control of gene expression output in the future synthetic biology.

Detection of target DNA with a novel Cas9/sgRNAs-associated reverse PCR (CARP) technique.

This study develops a new method for detecting target DNA based on Cas9 nuclease, which was named as CARP, representing CRISPR- or Cas9/sgRNAs-associated reverse PCR. This technique detects target DNA in three steps: (1) cleaving the detected DNA sample with Cas9 in complex with a pair of sgRNAs specific to target DNA; (2) ligating the cleaved DNA with DNA ligase; (3) amplifying target DNA with PCR. In the ligation step, the Cas9-cut target DNA was ligated into intramolecular circular or intermolecular concatenated linear DNA. In the PCR step, the ligated DNA was amplified with a pair of reverse primers. The technique was verified by detecting HPV16 and HPV18 L1 genes in nine different human papillomavirus (HPV) subtypes. The technique also detected the L1 and E6-E7 genes of two high-risk HPVs, HPV16 and HPV18, in the genomic DNA of two HPV-positive cervical carcinoma cells (HeLa and SiHa), in which no L1 and E6-E7 genes were detected in the HPV-negative cervical carcinoma cell, C-33a. By performing these proof-of-concept experiments, this study provides a new CRISPR-based DNA detection and typing method. Especially, the CARP method developed by this study is ready for the clinical HPV detection, which was supported by the final clinical sample detection. Graphical abstract CRISPR-associated reverse PCR (CARP) can be used to detect and type target DNA in a simple three-step procedure, cutting, ligation, and amplification.

On-nylon membrane detection of nucleic acid molecules by rolling circle amplification.

Positively-charged nylon membrane (NM) is a general solid-phase support for nucleic acid detection due to its convenient immobilization of nucleic acid materials by direct electrostatic adherence and simple UV crosslinking. Rolling circle amplification (RCA) is a widely used isothermal DNA amplification technique for nucleic acid detection. Near-infrared fluorescence (NIRF) is a new fluorescence technique with high sensitivity due to low background. This study developed a simple method for detecting nucleic acid molecules by combining the advantages of NM, RCA and NIRF, named NIRF-based solid phase RCA on nylon membrane (NM-NIRF-sRCA). The detection system of this method only need two kinds of nucleic acid molecules: target-specific probes with a RCA primer (P) at their 3' end and a rolling circle (RC). The detection procedure consists of four steps: (1) immobilizing detected nucleic acids on NM by UV crosslinking; (2) hybridizing NM with specific probes and RC; (3) amplifying by a RCA reaction containing biotin-dUTP; (4) incubating NM with NIRF-labeled streptavidin and imaging with a NIRF imager. The method was fully testified by detecting oligonucleotides, L1 fragments of various HPV subtypes cloned in plasmid, and E.coli genomic DNA. This study thus provides a new facile method for detecting nucleic acid molecules.

Identification of novel NF-κB transcriptional targets in TNFα-treated HeLa and HepG2 cells.

Identification of target genes of NF-κB is critical for deeply understanding its biological functions. Here, we identified five novel NF-κB target genes. Firstly, we found that 20 NF-κB potential target genes (PTGs) identified by ChIP-Seq and Genechip assay were enriched into the KEGG term of Pathways in cancer, 16 of them were enriched into the KEGG pathways of small cell lung cancer, chronic myeloid leukemia, basal cell carcinoma, pancreatic cancer, and colorectal cancer. Among these PTGs, there are many documented NF-κB target genes. Therefore, NF-κB may play important role in cancer progression by transcriptionally regulating these genes. Apart from the known target genes, we also found some novel PTGs including CYCS, MITF, FZD1, FZD8, and PIAS1. We subsequently demonstrated whether NF-κB transcriptionally control the five PTGs. The ChIP-Seq assay revealed that NF-κB/p65 bound to these genes in TNFα-treated HeLa. The bioinformatic analysis indicated that the NF-κB binding regions (i.e., ChIP-Seq peaks) contained κB sites and NF-κB/RelA DNA-binding motif. The ChIP-qPCR assay also confirmed that NF-κB bound to these regions in both TNFα-treated HeLa and HepG2 cells. The reporter construct showed that NF-κB could regulate luciferase expression via its binding region. Finally, qPCR and Western blot assay demonstrated that NF-κB indeed regulated the expression of these genes in the TNFα-treated HeLa and HepG2 cells. In a word, CYCS, MITF, FZD1, FZD8, and PIAS1 were identified as bona fide NF-κB target genes. These findings provide more insights into the role of NF-κB in cancers.

Automatic construction of statistical shape models using deformable simplex meshes with vector field convolution energy.

BACKGROUND: In the active shape model framework, principal component analysis (PCA) based statistical shape models (SSMs) are widely employed to incorporate high-level a priori shape knowledge of the structure to be segmented to achieve robustness. A crucial component of building SSMs is to establish shape correspondence between all training shapes, which is a very challenging task, especially in three dimensions. METHODS: We propose a novel mesh-to-volume registration based shape correspondence establishment method to improve the accuracy and reduce the computational cost. Specifically, we present a greedy algorithm based deformable simplex mesh that uses vector field convolution as the external energy. Furthermore, we develop an automatic shape initialization method by using a Gaussian mixture model based registration algorithm, to derive an initial shape that has high overlap with the object of interest, such that the deformable models can then evolve more locally. We apply the proposed deformable surface model to the application of femur statistical shape model construction to illustrate its accuracy and efficiency. RESULTS: Extensive experiments on ten femur CT scans show that the quality of the constructed femur shape models via the proposed method is much better than that of the classical spherical harmonics (SPHARM) method. Moreover, the proposed method achieves much higher computational efficiency than the SPHARM method. CONCLUSIONS: The experimental results suggest that our method can be employed for effective statistical shape model construction.

Targeting PSG1 to enhance chemotherapeutic efficacy: new application for anti-coagulant the dicumarol.

Chemotherapeutic response is critical for the successful treatment and good prognosis in cancer patients. In this study, we analysed the gene expression profiles of preoperative samples from oestrogen receptor (ER)-negative breast cancer patients with different responses to taxane-anthracycline-based (TA-based) chemotherapy, and identified a group of genes that was predictive. Pregnancy specific beta-1-glycoprotein 1 (PSG1) played a central role within signalling pathways of these genes. Inhibiting PSG1 can effectively reduce chemoresistance via a transforming growth factor-ß (TGF-ß)-related pathway in ER-negative breast cancer cells. Drug screening then identified dicumarol (DCM) to target the PSG1 and inhibit chemoresistance to TA-based chemotherapy in vitro, in vivo, and in clinical samples. Taken together, this study highlights PSG1 as an important mediator of chemoresistance, whose effect could be diminished by DCM.