Current challenges and therapeutic advances of CAR-T cell therapy for solid tumors.

The application of chimeric antigen receptor (CAR) T cells in the management of hematological malignancies has emerged as a noteworthy therapeutic breakthrough. Nevertheless, the utilization and effectiveness of CAR-T cell therapy in solid tumors are still limited primarily because of the absence of tumor-specific target antigen, the existence of immunosuppressive tumor microenvironment, restricted T cell invasion and proliferation, and the occurrence of severe toxicity. This review explored the history of CAR-T and its latest advancements in the management of solid tumors. According to recent studies, optimizing the design of CAR-T cells, implementing logic-gated CAR-T cells and refining the delivery methods of therapeutic agents can all enhance the efficacy of CAR-T cell therapy. Furthermore, combination therapy shows promise as a way to improve the effectiveness of CAR-T cell therapy. At present, numerous clinical trials involving CAR-T cells for solid tumors are actively in progress. In conclusion, CAR-T cell therapy has both potential and challenges when it comes to treating solid tumors. As CAR-T cell therapy continues to evolve, further innovations will be devised to surmount the challenges associated with this treatment modality, ultimately leading to enhanced therapeutic response for patients suffered solid tumors.

BiPSTP: Sequence feature encoding method for identifying different RNA modifications with bidirectional position-specific trinucleotides propensities.

RNA modification, a posttranscriptional regulatory mechanism, significantly influences RNA biogenesis and function. The accurate identification of modification sites is paramount for investigating their biological implications. Methods for encoding RNA sequence into numerical data play a crucial role in developing robust models for predicting modification sites. However, existing techniques suffer from limitations, including inadequate information representation, challenges in effectively integrating positional and sequential information, and the generation of irrelevant or redundant features when combining multiple approaches. These deficiencies hinder the effectiveness of machine learning models in addressing the performance challenges associated with predicting RNA modification sites. Here, we introduce a novel RNA sequence feature representation method, named BiPSTP, which utilizes bidirectional trinucleotide position-specific propensities. We employ the parameter ξ to denote the interval between the current nucleotide and its adjacent forward or backward dinucleotide, enabling the extraction of positional and sequential information from RNA sequences. Leveraging the BiPSTP method, we have developed the prediction model mRNAPred using support vector machine classifier to identify multiple types of RNA modification sites. We evaluate the performance of our BiPSTP method and mRNAPred model across 12 distinct RNA modification types. Our experimental results demonstrate the superiority of the mRNAPred model compared to state-of-art models in the domain of RNA modification sites identification. Importantly, our BiPSTP method enhances the robustness and generalization performance of prediction models. Notably, it can be applied to feature extraction from DNA sequences to predict other biological modification sites.

Clustering analysis for the evolutionary relationships of SARS-CoV-2 strains.

To explore the differences and relationships between the available SARS-CoV-2 strains and predict the potential evolutionary direction of these strains, we employ the hierarchical clustering analysis to investigate the evolutionary relationships between the SARS-CoV-2 strains utilizing the genomic sequences collected in China till January 7, 2023. We encode the sequences of the existing SARS-CoV-2 strains into numerical data through k-mer algorithm, then propose four methods to select the representative sample from each type of strains to comprise the dataset for clustering analysis. Three hierarchical clustering algorithms named Ward-Euclidean, Ward-Jaccard, and Average-Euclidean are introduced through combing the Euclidean and Jaccard distance with the Ward and Average linkage clustering algorithms embedded in the OriginPro software. Experimental results reveal that BF.28, BE.1.1.1, BA.5.3, and BA.5.6.4 strains exhibit distinct characteristics which are not observed in other types of SARS-CoV-2 strains, suggesting their being the majority potential sources which the future SARS-CoV-2 strains' evolution from. Moreover, BA.2.75, CH.1.1, BA.2, BA.5.1.3, BF.7, and B.1.1.214 strains demonstrate enhanced abilities in terms of immune evasion, transmissibility, and pathogenicity. Hence, closely monitoring the evolutionary trends of these strains is crucial to mitigate their impact on public health and society as far as possible.

Efficacy and safety of immunotherapy combined with single-agent chemotherapy as second- or later-line therapy for metastatic non-small cell lung cancer.

Objective: This study sought to assess the efficacy and safety of immunotherapy combined with single-agent chemotherapy as a second- or later-line setting for metastatic non-small cell lung cancer (NSCLC) and to provide clinical evidence for this treatment regimen. The predictive value of extracellular vesicle (EV) membrane proteins was explored in patients who underwent this treatment. Methods: Clinical data from patients diagnosed with metastatic NSCLC who received immunotherapy plus single-agent chemotherapy as a second- or later-line setting were retrospectively collected between March 2019 and January 2022. A total of 30 patients met the inclusion criteria, and all were pathologically confirmed to have NSCLC. Short-term efficacy, progression-free survival (PFS), EV markers for response prediction, and adverse events were assessed. Results: Efficacy data were available for all 30 patients and included a partial response in 5 patients, stable disease in 18 patients, and disease progression in 7 patients. The objective response rate was 16.7%, the disease control rate was 76.7%, and the median PFS was 3.2 months. Univariate analysis showed that PFS was not associated with sex, age, smoking status, treatment lines, prior use of immunotherapy, or prior use of antiangiogenic drugs. The EV membrane proteins MET proto-oncogene, receptor tyrosine kinase (c-MET), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor receptor 2 (VEGFR2) at baseline were associated with poor prognosis and correlated with the efficacy of immunotherapy plus chemotherapy. According to the receiver operating characteristics and Kaplan-Meier curve analyses, patients with high c-MET, EGFR, and VEGFR2 expression at baseline had significantly shorter PFS than those with low expression. In addition, VEGFR2 expression was increased after combined immunotherapy in responders, which was decreased in non-responders. The most common grade 2 or higher adverse events were neutropenia, gastrointestinal reactions, and thyroid dysfunction, all of which were tolerated. Conclusions: Immunotherapy plus single-agent chemotherapy as a second- or later-line treatment is safe, effective, and tolerable for metastatic NSCLC. EV markers can be used as predictive markers of efficacy in patients with metastatic NSCLC treated with immunotherapy plus chemotherapy to help monitor treatment efficacy and guide treatment decisions.

Molecular characterization of MET fusions from a large real-world Chinese population: A multicenter study.

PURPOSE: MET is a notable driver gene in the diversity of aberrations with clinical relevance, including exon 14 skipping, copy number gain, point mutations, and gene fusions. Compared with the former two, MET fusions are severely under-reported, leaving a series of unanswered questions. In this study, we addressed this gap by characterizing MET fusions in a large, real-world Chinese cancer population. METHODS: We retrospectively included patients with solid tumors who had DNA-based genome profiles acquired through targeted sequencing from August 2015 to May 2021. MET fusion-positive (MET+) patients were subsequently selected for clinical and molecular characterization. RESULTS: We screened 79,803 patients across 27 tumor types and detected 155 putative MET fusions from 122 patients, resulting in an overall prevalence of 0.15%. Lung cancer comprised the majority of MET+ patients (92, 75.4%). Prevalence was markedly higher in liver cancer, biliary tract cancer, and renal cancer (range 0.52%-0.60%). It was lower in ovarian cancer (0.06%). A substantial proportion (48/58, 82.8%) of unique partners were reported for the first time. High heterogeneity was observed for partners, with ST7, HLA-DRB1, and KIF5B as the three most common partners. Mutational landscape analysis of lung adenocarcinoma (n = 32) revealed a high prevalence of TP53 in MET+ alterations, EGFR L858R, EGFR L861Q, and MET amplification. CONCLUSION: To our knowledge, this is currently the largest study in characterizing MET fusions. Our findings warrant that further clinical validation and mechanistic study may translate into therapeutic avenues for MET+ cancer patients.

The nnU-Net based method for automatic segmenting fetal brain tissues.

The magnetic resonance (MR) images of fetuses make it possible for doctors to detect out pathological fetal brains in early stages. Brain tissue segmentation is prerequisite for making brain morphology and volume analyses. nnU-Net is an automatic segmentation method based on deep learning. It can adaptively configure itself, so as to adapt to a specific task via preprocessing, network architecture, training, and post-processing. Therefore, we adapt nnU-Net to segment seven types of fetal brain tissues, including external cerebrospinal fluid, gray matter, white matter, ventricle, cerebellum, deep gray matter, and brainstem. With regard to the characteristics of the FeTA 2021 data, some adjustments are made to the original nnU-Net, so that it can segment seven types of fetal brain tissues precisely as far as possible. The average segmentation results on FeTA 2021 training data demonstrate that our advanced nnU-Net is superior to the peers including SegNet, CoTr, AC U-Net and ResUnet. Its average segmentation results are 0.842, 11.759 and 0.957 in terms of Dice, HD95 and VS criteria. Moreover, the experimental results on FeTA 2021 test data further demonstrate that our advanced nnU-Net has obtained good segmentation performance of 0.774, 14.699 and 0.875 in terms of Dice, HD95 and VS, ranked the third in FeTA 2021 challenge. Our advanced nnU-Net realized the task for segmenting the fetal brain tissues using MR images of different gestational ages, which can help doctors to make correct and seasonable diagnoses.

Efficacy and safety of osimertinib plus anlotinib in advanced non-small-cell lung cancer patients after drug resistance.

OBJECTIVE: To retrospectively analyze the efficacy and safety of osimertinib combined with anlotinib in the treatment of advanced non-small-cell lung cancer (NSCLC) after drug resistance, and to explore the related factors affecting the efficacy. METHODS: The clinical data of 34 patients with advanced NSCLC who received osimertinib combined with anlotinib as three or more lines of treatment in the Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College from June 2019 to March 2022 were collected, and the therapeutic efficacy and safety were analyzed. RESULTS: A total of 34 advanced NSCLC patients met the inclusion criteria. The objective response rate was 20.6%, the disease response rate was 88.2%, the median overall survival was 19.0 months, and the median progression-free survival was 6.0 months. The common adverse events were mainly grade 1-2, and only three cases (11.1%) of adverse events were grade 3, including hypertension, proteinuria, and vomiting. No grade 4 or above adverse events were observed. Multivariate Cox regression analysis showed that the Eastern Cooperative Oncology Group Performance Status score and bone metastasis were independent prognostic factors for osimertinib combined with anlotinib as three or more lines of treatment in advanced NSCLC. CONCLUSIONS: Osimertinib combined with anlotinib as three or more lines of treatment in advanced NSCLC was effective and adverse events were tolerable.

A Report of Pectobacterium carotovorum subsp. actinidiae Causing Kiwifruit Bacterial Canker in Guangxi, China.

A bacterial pathogen strain was isolated from susceptible tissue of Hongyang variety kiwifruit in Zhongfeng Town, Ziyuan County, Guilin City, Guangxi, China. Due to the relatively single variety of kiwifruit in Guangxi, the control technology of fruit farmers is backward, and the climate is humid, which is suitable for the growth of pathogenic bacteria, resulting in frequent occurrence of diseases. In this study, the pathogen strain was identified based on morphological, physiological, and biochemical tests; 16S rRNA gene; PCR detection with specific primers; and Biolog analysis. The results showed that a tobacco allergic reaction could be induced by inoculation with the pathogenic bacteria. Additionally, brown necrotic plaques appeared on kiwifruit leaves, necrotic phloem lesions appeared, and wounds on kiwifruit branches turned brown. The characteristics identified by morphological, physiological, biochemical, and Biolog identification were similar to those caused by Pectobacterium sp. Through 16S rRNA gene sequence analysis and PCR identification with specific primers, bands with a size corresponding to target bands indicated that the pathogen was Pectobacterium carotovorum subsp. actinidiae. This is the first report of kiwifruit canker disease caused by P. carotovorum subsp. actinidiae in Guangxi, China. In addition, through this study, a preliminary understanding of the pathogen has been obtained, which will lay the foundation for the prevention and control of the disease in the future.

The therapeutic effect and targets of cellulose polysaccharide on coronary heart disease (CHD) and the construction of a prognostic signature based on network pharmacology.

Cellulose is the first rich biological polysaccharide in nature and has many excellent properties, so it is being developed as a variety of drug carriers. Moreover, applications in drug delivery, biosensors/bioanalysis, immobilization of enzymes and cells, stem cell therapy, and skin tissue repair are also highlighted by many studies. Coronary heart disease, as one of the diseases with the highest incidence, is urgent to enhance the survival outcome and life quality of patients with coronary heart disease, whereas the mechanism of cellulose's interaction with the human body remains unclear. However, the mechanism of cellulose's interaction with the human body remains unclear. We obtained 92 genes associated with cellulose and coronary heart disease through the intersection of different databases. Ten key genes were identified: HRAS, STAT3, HSP90AA1, FGF2, VEGFA, CXCR4, TERT, IL2, BCL2L1, and CDK1. Molecular docking of the 10 genes revealed their association with their respective receptors. Analysis by KEGG and GO has discovered that these related targets were more enriched in metabolic- and activation-related functions, which further confirmed that cellulose polysaccharides can also interact with cardiovascular diseases as molecules. In the end, we screened out six key genes that were more associated with the prognosis (CDK1, HSP90AA1, CXCR4, IL2, VEGFA, and TERT) and constructed a signature, which has a good predictive effect and has significant statistical significance. Our study is the first study to explore the interaction targets of cellulose and CHD and to construct a prognostic model. Our findings provide insights for future molecular design, drug development, and clinical trials.

Necroptosis-Related Prognostic Signature and Nomogram Model for Predicting the Overall Survival of Patients with Lung Cancer.

Background: Necroptosis is a type of programmed cell death mode and it serves an important role in the tumorigenesis and tumor metastasis. The purpose of this study is to develop a prognostic model based on necroptosis-related genes and nomogram for predicting the overall survival of patients with lung cancer. Method: Differentially expressed necroptosis-related genes (NRDs) between lung cancer and normal samples were identified. Univariate and LASSO regression analyses were performed to establish a risk score (RS) model, followed by validation within TCGA and GSE37745. The correlation between RS model and tumor microenvironment, mutation status, or drug susceptibility was analyzed. By combining clinical factors, nomogram was developed to predict 1-, 3-, and 5-year survival probability of an individual. The biological function involved by different risk groups was conducted by GSEA. Results: A RS model containing six NRDs (FLNC, PLK1, ID1, MYO1C, SERTAD1, and LEF1) was constructed, and patients were divieded into low-risk (LR) and high-risk (HR) groups. Patients in HR group were associated with shorter survival time than those in the LR group; this model had better prognostic performance. Nomogram based on necroptosis score, T stage, and stage had been confirmed to predict survival of patients. The number of resting NK cells and M0 macrophages was higher in HR group. In addition, higher tumor mutational burden and drug sensitivity were observed in the HR group. Patients in HR group were involved in p53 signaling pathway and cell cycle. Conclusion: This study constructed a robust six-NRDs signature and established a prognostic nomogram for survival prediction of lung cancer.

PD-1 inhibitors plus chemotherapy in EGFR/ALK-positive NSCLC patients with brain metastases and disease progression after EGFR/ALK-TKIs therapy.

BACKGROUND: Resistance to epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK)-tyrosine kinase inhibitors (TKIs) is a pervasive barrier in TKIs therapy for EGFR/ALK-positive non-small cell lung cancer (NSCLC) patients. Immune checkpoint inhibitor (ICI) monotherapy has exhibited an encouraging anti-tumor activity in high-selected EGFR/ALK-positive NSCLC patients with acquired resistance to TKI therapy. However, the effect of ICI plus chemotherapy therapy on those with brain metastases in this subset of patients is still unknown. METHODS: From April 2019 to August 2021, EGFR-mutated or ALK-rearranged NSCLC patients who progressed after previous EGFR/ALK-TKIs with brain metastases and received ICI plus chemotherapy ± bevacizumab at Cancer Hospital of the Chinese Academy of Medical Sciences (CAMS) were included. We retrospectively analyzed the efficacy, toxicity and progression site after ICI treatment. RESULTS: A total of 19 patients were included in the study, including 16 (84.4%) patients with EGFR mutations, 2 (10.5%) with ALK translocations and 1 (5.3%) with RET rearrangement. All of the patients progressed after previous TKI therapy and had brain metastatic lesions when received ICI combination therapy. The overall response rate (ORR) and disease control rate (DCR) were 15.8 and 57.9%, respectively. The median progression-free survival (PFS) and overall survival (OS) were 4.7 months (95% confidence interval CI 0.43-8.96) and 19.2 months (95% CI 15.08-23.29), respectively. The intracranial ORR was 10.5% and extracranial ORR was 15.8%, and the intracranial and extracranial DCR were 68.4 and 63.2%, respectively. The most common progression pattern was extracranial failure, and primary lesions enlargement rather than new sites metastases accounted for the vast majority of progressions. The most common grade 3-4 adverse event (AE) was leukopenia (31.6%), followed by neutropenia (26.3%), thrombocytopenia (10.5%) and rash (5.3%) successively. No grade 5 AE and discontinuation of ICI therapy for severe AEs were observed. CONCLUSIONS: ICI combined with chemotherapy ± bevacizumab might be effective and safe for EGFR/ALK-positive NSCLC patients who progressed after previous TKI therapy, and synergistic anti-tumor activity for brain metastases was also observed.

Evaluation Analysis of the Nephrotoxicity of Tripterygium wilfordii Preparations with CONSORT Harms Statement Based on Deep Learning.

In this paper, the safety of Tripterygium wilfordii polyglycoside (TW) preparation was evaluated by combining literature research and evidence-based evaluation research, so as to provide evidence-based safety information of Tripterygium wilfordii polyglycoside preparation (nephroptosis) for government decision making and clinical application. In this paper, we propose a network structure inspired by the LSTM gate mechanism. All the research methods of the included references are evaluated by internationally recognized evaluation tools or standards. Prevalence was analyzed according to the type of intervention (e.g., time of administration) and route of administration. The results of this experiment provide methods and suggestions for the evaluation of traditional Chinese medicine nephroptosis in the future.

Adaptable Invisibility Management Using Kirigami-Inspired Transformable Metamaterials.

Many real-world applications, including adaptive radar scanning and smart stealth, require reconfigurable multifunctional devices to simultaneously manipulate multiple degrees of freedom of electromagnetic (EM) waves in an on-demand manner. Recently, kirigami technique, affording versatile and unconventional structural transformation, has been introduced to endow metamaterials with the capability of controlling EM waves in a reconfigurable manner. Here, we report for a kirigami-inspired sparse meta-architecture, with structural density of 1.5% in terms of the occupation space, for adaptive invisibility based on independent operations of frequency, bandwidth, and amplitude. Based on the general principle of dipolar management via structural reconstruction of kirigami-inspired meta-architectures, we demonstrate reconfigurable invisibility management with abundant EM functions and a wide tuning range using three enantiomers (A, B, and C) of different geometries characterized by the folding angle ß. Our strategy circumvents issues of limited abilities, narrow tuning range, extreme condition, and high cost raised by available reconfigurable metamaterials, providing a new avenue toward multifunctional smart devices.

M6A-BiNP: predicting N6-methyladenosine sites based on bidirectional position-specific propensities of polynucleotides and pointwise joint mutual information.

N6-methyladenosine (m6A) plays an important role in various biological processes. Identifying m6A site is a key step in exploring its biological functions. One of the biggest challenges in identifying m6A sites is how to extract features comprising rich categorical information to distinguish m6A and non-m6A sites. To address this challenge, we propose bidirectional dinucleotide and trinucleotide position-specific propensities, respectively, in this paper. Based on this, we propose two feature-encoding algorithms: Position-Specific Propensities and Pointwise Mutual Information (PSP-PMI) and Position-Specific Propensities and Pointwise Joint Mutual Information (PSP-PJMI). PSP-PMI is based on the bidirectional dinucleotide propensity and the pointwise mutual information, while PSP-PJMI is based on the bidirectional trinucleotide position-specific propensity and the proposed pointwise joint mutual information in this paper. We introduce parameters α and ß in PSP-PMI and PSP-PJMI, respectively, to represent the distance from the nucleotide to its forward or backward adjacent nucleotide or dinucleotide, so as to extract features containing local and global classification information. Finally, we propose the M6A-BiNP predictor based on PSP-PMI or PSP-PJMI and SVM classifier. The 10-fold cross-validation experimental results on the benchmark datasets of non-single-base resolution and single-base resolution demonstrate that PSP-PMI and PSP-PJMI can extract features with strong capabilities to identify m6A and non-m6A sites. The M6A-BiNP predictor based on our proposed feature encoding algorithm PSP-PJMI is better than the state-of-the-art predictors, and it is so far the best model to identify m6A and non-m6A sites.

The Unsupervised Feature Selection Algorithms Based on Standard Deviation and Cosine Similarity for Genomic Data Analysis.

To tackle the challenges in genomic data analysis caused by their tens of thousands of dimensions while having a small number of examples and unbalanced examples between classes, the technique of unsupervised feature selection based on standard deviation and cosine similarity is proposed in this paper. We refer to this idea as SCFS (Standard deviation and Cosine similarity based Feature Selection). It defines the discernibility and independence of a feature to value its distinguishable capability between classes and its redundancy to other features, respectively. A 2-dimensional space is constructed using discernibility as x-axis and independence as y-axis to represent all features where the upper right corner features have both comparatively high discernibility and independence. The importance of a feature is defined as the product of its discernibility and its independence (i.e., the area of the rectangular enclosed by the feature's coordinate lines and axes). The upper right corner features are by far the most important, comprising the optimal feature subset. Based on different definitions of independence using cosine similarity, there are three feature selection algorithms derived from SCFS. These are SCEFS (Standard deviation and Exponent Cosine similarity based Feature Selection), SCRFS (Standard deviation and Reciprocal Cosine similarity based Feature Selection) and SCAFS (Standard deviation and Anti-Cosine similarity based Feature Selection), respectively. The KNN and SVM classifiers are built based on the optimal feature subsets detected by these feature selection algorithms, respectively. The experimental results on 18 genomic datasets of cancers demonstrate that the proposed unsupervised feature selection algorithms SCEFS, SCRFS and SCAFS can detect the stable biomarkers with strong classification capability. This shows that the idea proposed in this paper is powerful. The functional analysis of these biomarkers show that the occurrence of the cancer is closely related to the biomarker gene regulation level. This fact will benefit cancer pathology research, drug development, early diagnosis, treatment and prevention.

Polarization-insensitive 3D conformal-skin metasurface cloak.

Electromagnetic metasurface cloaks provide an alternative paradigm toward rendering arbitrarily shaped scatterers invisible. Most transformation-optics (TO) cloaks intrinsically need wavelength-scale volume/thickness, such that the incoming waves could have enough long paths to interact with structured meta-atoms in the cloak region and consequently restore the wavefront. Other challenges of TO cloaks include the polarization-dependent operation to avoid singular parameters of composite cloaking materials and limitations of canonical geometries, e.g., circular, elliptical, trapezoidal, and triangular shapes. Here, we report for the first time a conformal-skin metasurface carpet cloak, enabling to work under arbitrary states of polarization (SOP) at Poincaré sphere for the incident light and arbitrary conformal platform of the object to be cloaked. By exploiting the foundry three-dimensional (3D) printing techniques to fabricate judiciously designed meta-atoms on the external surface of a conformal object, the spatial distributions of intensity and polarization of its scattered lights can be reconstructed exactly the same as if the scattering wavefront were deflected from a flat ground at any SOP, concealing targets under polarization-scanning detections. Two conformal-skin carpet cloaks working for partial- and full-azimuth plane operation are respectively fabricated on trapezoid and pyramid platforms via 3D printing. Experimental results are in good agreement with numerical simulations and both demonstrate the polarization-insensitive cloaking within a desirable bandwidth. Our approach paves a deterministic and robust step forward to the realization of interfacial, free-form, and full-polarization cloaking for a realistic arbitrary-shape target in real-world applications.

Deterministic Approach to Achieve Full-Polarization Cloak.

Achieving full-polarization (σ) invisibility on an arbitrary three-dimensional (3D) platform is a long-held knotty issue yet extremely promising in real-world stealth applications. However, state-of-the-art invisibility cloaks typically work under a specific polarization because the anisotropy and orientation-selective resonant nature of artificial materials made the σ-immune operation elusive and terribly challenging. Here, we report a deterministic approach to engineer a metasurface skin cloak working under an arbitrary polarization state by theoretically synergizing two cloaking phase patterns required, respectively, at spin-up (σ+) and spin-down (σ-) states. Therein, the wavefront of any light impinging on the cloak can be well preserved since it is a superposition of σ+ and σ- wave. To demonstrate the effectiveness and applicability, several proof-of-concept metasurface cloaks are designed to wrap over a 3D triangle platform at microwave frequency. Results show that our cloaks are essentially capable of restoring the amplitude and phase of reflected beams as if light was incident on a flat mirror or an arbitrarily predesigned shape under full polarization states with a desirable bandwidth of ~17.9%, conceiving or deceiving an arbitrary object placed inside. Our approach, deterministic and robust in terms of accurate theoretical design, reconciles the milestone dilemma in stealth discipline and opens up an avenue for the extreme capability of ultrathin 3D cloaking of an arbitrary shape, paving up the road for real-world applications.

MicroRNA-105 promotes epithelial-mesenchymal transition of nonsmall lung cancer cells through upregulating Mcl-1.

BACKGROUND: A growing number of microRNAs have been proved to play significant roles in limiting tumor growth and the epithelial-mesenchymal transition (EMT) process of nonsmall cell lung cancer (NSCLC). Present work aims to study the function of microRNA (miR)-105 in EMT of NSCLC cells, which is unrevealed yet. METHODS: Two NSCLC cell lines A549 and Calu-3 were transfected with miR-105 mimic, inhibitor, or scrambled control. And then the effects of miR-105 were evaluated by performing trypan blue staining, transwell assay, ANNEXIN-FITC/propidium iodide (PI) double staining and Western blot analysis. The expression levels of myeloid cell leukemia-1 (Mcl-1) after transfection were tested by real-time quantitative polymerase chain reaction and Western blot analysis. Whether Mcl-1 was a downstream effector of miR-105, and the involvement of mammalian target of Rapamycin (mTOR) and p38 mitogen-activated protein kinase (p38MAPK) signaling pathways were assessed. RESULTS: The overexpression of miR-105 significantly increased the viability and migration of A549 and Calu-3, but had no impacts on cell apoptosis. Meanwhile, E-cadherin was remarkably downregulated, and N-cadherin, Vimentin, ZEB1, and Snail were upregulated by miR-105 overexpression. Mcl-1 was positively regulated by miR-105, and the effects of miR-105 overexpression on A549 and Calu-3 cells viability, migration and EMT were all flattened by Mcl-1 silence. Both mTOR and p38MAPK pathways were activated in miR-105-overexpressing and Mcl-1-overexpressing cells. Besides, inhibition of mTOR and p38MAPK pathways by using Rapamycin and VX-702 abolished the regulatory effects of Mcl-1 on EMT. CONCLUSION: Our study underlines the importance of miR-105 in modulating NSCLC cells EMT. miR-105 promoted the EMT of NSCLC cells possibly via upregulation of Mcl-1 and thereby activation of mTOR and p38MAPK signaling.

A novel method detecting the key clinic factors of portal vein system thrombosis of splenectomy & cardia devascularization patients for cirrhosis & portal hypertension.

BACKGROUND: Portal vein system thrombosis (PVST) is potentially fatal for patients if the diagnosis is not timely or the treatment is not proper. There hasn't been any available technique to detect clinic risk factors to predict PVST after splenectomy in cirrhotic patients. The aim of this study is to detect the clinic risk factors of PVST for splenectomy and cardia devascularization patients for liver cirrhosis and portal hypertension, and build an efficient predictive model to PVST via the detected risk factors, by introducing the machine learning method. We collected 92 clinic indexes of splenectomy plus cardia devascularization patients for cirrhosis and portal hypertension, and proposed a novel algorithm named as RFA-PVST (Risk Factor Analysis for PVST) to detect clinic risk indexes of PVST, then built a SVM (support vector machine) predictive model via the detected risk factors. The accuracy, sensitivity, specificity, precision, F-measure, FPR (false positive rate), FNR (false negative rate), FDR (false discovery rate), AUC (area under ROC curve) and MCC (Matthews correlation coefficient) were adopted to value the predictive power of the detected risk factors. The proposed RFA-PVST algorithm was compared to mRMR, SVM-RFE, Relief, S-weight and LLEScore. The statistic test was done to verify the significance of our RFA-PVST. RESULTS: Anticoagulant therapy and antiplatelet aggregation therapy are the top-2 risk clinic factors to PVST, followed by D-D (D dimer), CHOL (Cholesterol) and Ca (calcium). The SVM (support vector machine) model built on the clinic indexes including anticoagulant therapy, antiplatelet aggregation therapy, RBC (Red blood cell), D-D, CHOL, Ca, TT (thrombin time) and Weight factors has got pretty good predictive capability to PVST. It has got the highest PVST predictive accuracy of 0.89, and the best sensitivity, specificity, precision, F-measure, FNR, FPR, FDR and MCC of 1, 0.75, 0.85, 0.92, 0, 0.25, 0.15 and 0.8 respectively, and the comparable good AUC value of 0.84. The statistic test results demonstrate that there is a strong significant difference between our RFA-PVST and the compared algorithms, including mRMR, SVM-RFE, Relief, S-weight and LLEScore, that is to say, the risk indicators detected by our RFA-PVST are statistically significant. CONCLUSIONS: The proposed novel RFA-PVST algorithm can detect the clinic risk factors of PVST effectively and easily. Its most contribution is that it can display all the clinic factors in a 2-dimensional space with independence and discernibility as y-axis and x-axis, respectively. Those clinic indexes in top-right corner of the 2-dimensional space are detected automatically as risk indicators. The predictive SVM model is powerful with the detected clinic risk factors of PVST. Our study can help medical doctors to make proper treatments or early diagnoses to PVST patients. This study brings the new idea to the study of clinic treatment for other diseases as well.

CUG-binding protein 1 (CUGBP1) expression and prognosis of brain metastases from non-small cell lung cancer.

BACKGROUND: The brain is a frequent site of metastases from non-small cell lung cancer (NSCLC). The purpose of this study was to detect the expression of CUG-binding protein 1 (CUGBP1) messenger ribonucleic acid (mRNA) and Ki-67 in metastasized brain tissue from NSCLC and determine the relationship between CUGBP1 and brain metastases. METHODS: The expression of CUGBP1 mRNA and Ki-67 in metastasized brain tissue from NSCLC was investigated by semiquantitative polymerase chain reaction and immunohistochemistry, respectively. The expression of CUGBP1 and Ki-67 in metastasized brain tissue from NSCLC was related to clinical characteristics, as assessed using the chi-square test. The prognostic significance was assessed by univariate and multivariate analyses using the Cox hazard model. RESULTS: The expression of CUGBP1 mRNA and Ki-67 was overexpressed in metastasized brain tissue from NSCLC and was correlated with differentiation. In addition, by both univariate and multivariate survival analyses, CUGBP1 expression, Ki-67 expression, and age were noted to be independent indicators of a shorter postsurgical survival. CONCLUSION: The expression of CUGBP1 is an important factor in the development of brain metastases from NSCLC.