Tryptophan-Doped Poly(vinyl alcohol) Films with Ultralong-Lifetime Room-Temperature Phosphorescence and Color-Tunable Afterglow Under Ambient Conditions.

The development of a persistent luminescence system with long-lived phosphorescence and color-tunable afterglow at room temperature represents a challenge, largely due to the intensive non-radiative deactivation pathway. In this study, an ultralong-lived room temperature phosphorescence (RTP) system has been achieved using a hydrogen-bonding strategy where poly(vinyl alcohol) (PVA) matrices were doped with tryptophan (Trp) derivatives. The PVA film doped with N-α-(9-Fluorenylmethoxycarbonyl)-L-tryptophan (Fmoc-L-Trp) exhibited a long-lived phosphorescence emission of up to 3859.70 ms, and a blue afterglow for a duration greater than 34 s, under ambient conditions. The introduction of two other fluorescent dyes (i. e., Rhodamine B and Basicred14) to the PVA film facilitates adjustment to the color of the afterglow from blue to orange, and pink, by a triplet-to-singlet Förster-resonance energy transfer (TS-FRET) process. These films have been successfully applied in silk-screen printing and in multicolor afterglow light-emitting diode (LED) arrays.

[Mediator Complex Subunit 8:Expression in Gastric Cancer, Prognostic Significance,and Impact on Cell Cycle].

Objective To investigate the expression and prognostic significance of mediator complex subunit 8 (MED8) in gastric cancer and its impact on the cell cycle.Methods The expression of MED8 in gastric cancer and adjacent tissues and its correlation with patients' prognosis were analyzed using public databases.A validation cohort of 104 patients who underwent radical resection for gastric cancer in the First Affiliated Hospital of Bengbu Medical College from June 2012 to July 2017 was included.The receiver operating characteristic curve was established to evaluate the predictive value of MED8 for postoperative 5-year survival.Bioinformatics tools were used to predict the biological roles of MED8 in gastric cancer.The effect of the MED8 level on the G1/S phase transition of gastric cancer cells (MGC-803) was analyzed via lentivirus transduction and flow cytometry.Western blotting was carried out to assess the impact of MED8 expression on the protein levels of cyclin-dependent kinase 4(Cdk4) and G1/S-specific cyclin-D1(CyclinD1) in MGC-803 cells.Results The high expression of MED8 in the gastric cancer tissue was associated with poor prognosis (P<0.001) and had prognostic significance (area under curve=0.733,P<0.001).Gene enrichment analysis suggested that MED8 may participate in the cell cycle process.Flow cytometry results revealed that the upregulation of MED8 expression promoted the transition of MGC-803 cells from the G1 phase to the S phase (P<0.001),while the downregulation of MED8 had the opposite effect (P<0.001).Western blotting showed increases in the protein levels of Cdk4 and CyclinD1 in MGC-803 cells with upregulated MED8 expression (all P<0.001),and decreases in the cells with downregulated MED8 expression (all P<0.001).Conclusion MED8 is highly expressed in gastric cancer and may affect its progression and prognosis by regulating the G1/S phase transition of gastric cancer cells.

Advances in Skin Wound and Scar Repair by Polymer Scaffolds.

Scars, as the result of abnormal wound-healing response after skin injury, may lead to loss of aesthetics and physical dysfunction. Current clinical strategies, such as surgical excision, laser treatment, and drug application, provide late remedies for scarring, yet it is difficult to eliminate scars. In this review, the functions, roles of multiple polymer scaffolds in wound healing and scar inhibition are explored. Polysaccharide and protein scaffolds, an analog of extracellular matrix, act as templates for cell adhesion and migration, differentiation to facilitate wound reconstruction and limit scarring. Stem cell-seeded scaffolds and growth factors-loaded scaffolds offer significant bioactive substances to improve the wound healing process. Special emphasis is placed on scaffolds that continuously release oxygen, which greatly accelerates the vascularization process and ensures graft survival, providing convincing theoretical support and great promise for scarless healing.

Maize microRNA166 Inactivation Confers Plant Development and Abiotic Stress Resistance.

MicroRNAs are important regulators in plant developmental processes and stress responses. In this study, we generated a series of maize STTM166 transgenic plants. Knock-down of miR166 resulted in various morphological changes, including rolled leaves, enhanced abiotic stress resistance, inferior yield-related traits, vascular pattern and epidermis structures, tassel architecture, as well as abscisic acid (ABA) level elevation and indole acetic acid (IAA) level reduction in maize. To profile miR166 regulated genes, we performed RNA-seq and qRT-PCR analysis. A total of 178 differentially expressed genes (DEGs) were identified, including 118 up-regulated and 60 down-regulated genes. These DEGs were strongly enriched in cell and intercellular components, cell membrane system components, oxidoreductase activity, single organism metabolic process, carbohydrate metabolic process, and oxidation reduction process. These results indicated that miR166 plays important roles in auxin and ABA interaction in monocots, yet the specific mechanism may differ from dicots. The enhanced abiotic stress resistance is partly caused via rolling leaves, high ABA content, modulated vascular structure, and the potential changes of cell membrane structure. The inferior yield-related traits and late flowering are partly controlled by the decreased IAA content, the interplay of miR166 with other miRNAs and AGOs. Taken together, the present study uncovered novel functions of miR166 in maize, and provide insights on applying short tandem target mimics (STTM) technology in plant breeding.

Identification of waveguide mode and surface plasmon resonance mode using Fourier cross-correlation analysis.

The light reflected into the back focal plane of a microscope objective allows one to gather a great deal of information about the resonant modes excited on a sample. These dips represent modes excited on the sample, which are related to both the material properties and the structure. Automatic identification of these resonances is a vital stage in developing automated machine-learning techniques for high-throughput sample characterization. In previous work, identification of a single isolated mode was demonstrated; here we show how multiple modes can be separately identified using an automated centering procedure in a process we call radial thresholding. Once the center was determined, the radial thresholding process was modified and combined with interpolation to locate the precise modal positions. We show that this method is capable of resolving very closely spaced modes and is sensitive to nanometric changes in sample dimensions. The processing time for the method is sufficiently fast to ensure that it is suited for rapid sample identification.

A Modified Empirical Wavelet Transform for Acoustic Emission Signal Decomposition in Structural Health Monitoring.

The acoustic emission (AE) method is useful for structural health monitoring (SHM) of composite structures due to its high sensitivity and real-time capability. The main challenge, however, is how to classify the AE data into different failure mechanisms because the detected signals are affected by various factors. Empirical wavelet transform (EWT) is a solution for analyzing the multi-component signals and has been used to process the AE data. In order to solve the spectrum separation problem of the AE signals, this paper proposes a novel modified separation method based on local window maxima (LWM) algorithm. It searches the local maxima of the Fourier spectrum in a proper window, and automatically determines the boundaries of spectrum segmentations, which helps to eliminate the impact of noise interference or frequency dispersion in the detected signal and obtain the meaningful empirical modes that are more related to the damage characteristics. Additionally, both simulation signal and AE signal from the composite structures are used to verify the effectiveness of the proposed method. Finally, the experimental results indicate that the proposed method performs better than the original EWT method in identifying different damage mechanisms of composite structures.

Future Trend Forecast by Empirical Wavelet Transform and Autoregressive Moving Average.

In engineering and technical fields, a large number of sensors are applied to monitor a complex system. A special class of signals are often captured by those sensors. Although they often have indirect or indistinct relationships among them, they simultaneously reflect the operating states of the whole system. Using these signals, the field engineers can evaluate the operational states, even predict future behaviors of the monitored system. A novel method of future operational trend forecast of a complex system is proposed in this paper. It is based on empirical wavelet transform (EWT) and autoregressive moving average (ARMA) techniques. Firstly, empirical wavelet transform is used to extract the significant mode from each recorded signal, which reflects one aspect of the operating system. Secondly, the system states are represented by the indicator function which are obtained from those normalized and weighted significant modes. Finally, the future trend is forecast by the parametric model of ARMA. The effectiveness and practicality of the proposed method are verified by a set of numerical experiments.

Primary surveys on molecular epidemiology of bovine viral diarrhea virus 1 infecting goats in Jiangsu province, China.

BACKGROUND: Bovine viral diarrhea virus (BVDV) is a pathogen of domestic and wildlife animals worldwide and is associated with several diseases. In China, there are many reports about genotyping of BVDV strains originated from cattle and pigs, and some of them focused on the geographical distributions of BVDV. Currently, the goat industry in Jiangsu province of China is under going a rapid expansion. Most of these goat farms are backyard enterprises and in close proximity to pig and cattle farms. However, there was very limited information about BVDV infections in goats. The objective of this study was to assess the frequency of BVDV infections of goats, the relationship of these infections to clinical signs and determine what BVDV genotypes are circulating in Jiangsu province. RESULTS: From 236 goat sera collected from six regions in Jiangsu province between 2011 and 2013, BVDV-1 was identified in 29 samples from the five regions by RT-PCR. The BVDV-1 infections occurred with/without clinical signs. Eight different BVDV-1 strains were identified from these positive samples based on the 5'-untranslated region (5'-UTR) sequences, and further clustered into four BVDV-1 subtypes on the phylogenetic analysis. Three were BVDV-1b, two BVDV-1m, two BVDV-1o, and one BVDV-1p, respectively. CONCLUSIONS: To our knowledge, this is the first report to investigate the occurrence of BVDV and the genotypes of BVDV infecting goats in China. The results indicated that BVDV-1 infections were indeed present and the viruses were with genetic variations in Chinese goat herds. The information would be very useful for prevention and control of BVDV-1 infections in China.

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

[Establish and analyze the predictive model of early stage brain metastases in patients with breast cancer].

OBJECTIVE: To investigate the risk factors of cerebral metastasis of breast cancer and to provide guidance for the early diagnosis and treatment of brain metastases. METHODS: Clinical data of postoperative patients with breast cancer were collected in our hospital from 2005 to 2009. All the patients were divided into two groups, with or without brain metastasis. The risk factors of brain metastases of patients with breast cancer were analyzed by the logistic regression. RESULTS: Eight hundred and twenty four early postoperative patients with breast cancer were enrolled. The median follow-up time was 68 months and 199 cases had brain metastasis. The univariate logistic regression results showed that higher grade of tumor, <35 years, premenopausal, clinical stage Ⅲ, HER-2 positive and ER negative, no adjuvant chemotherapy, no adjuvant normal therapy were the risk factors of brain metastasis. The multivariate logistic regression result showed that higher grade of tumor, <35 years, premenopausal, clinical stage Ⅲ, HER-2 positive, ER negative were the risk factors. The mathematical model was used to predict the probability of occurrence of brain metastasis. ROC curve were draw by the value of predict probability as test variable and the brain metastasis status as state variables. The AUC value of this predictive model was 0.743±0.018. The specificity and sensitivity are relative high. CONCLUSION: Age<35 years, premenopausal, clinical stage Ⅲ, HER-2 positive and ER negative were independent risk factors for brain metastases. This model has the predictive value for the occurrence of brain metastases from breast cancer.

Development of a bioactive silk fibroin bilayer scaffold for wound healing and scar inhibition.

In cases of deep skin defects, spontaneous tissue regeneration and excessive collagen deposition lead to hyperplastic scars. Conventional remedial action after scar formation is limited with a high recurrence rate. In this study, we designed a new artificial skin bilayer using silk fibroin nanofibers films (SNF) as the epidermis, and silk fibroin (SF) / hyaluronic acid (HA) scaffold as the dermal layer. The regenerated SF film was used as a binder to form a functional SNF-SF-HA bilayer scaffold. The bilayer scaffold showed high porosity, hydrophilicity, and strength, and retained its shape over 30 days in PBS. In vitro, human umbilical vein endothelial cells were seeded into the bilayer scaffold and showed superior cell viability. In vivo analyses using the rabbit ear hypertrophic scar (HS) model indicated that the bilayer scaffold not only supported the reconstruction of new tissue, but also inhibited scar formation. The scaffold possibly achieved scar inhabitation by reducing wound contraction, weakening inflammatory reactions, and regulating collagen deposition and type conversion, which was partly observed through the downregulation of type I collagen, transforming growth factor-ß, and α-smooth muscle actin. This study describes a new strategy to expand the application of silk-based biomaterials for the treatment of hyperplastic skin scars.

Janus Nanofibrous Patch with In Situ Grown Superlubricated Skin for Soft Tissue Repair with Inhibited Postoperative Adhesion.

The patch with a superlubricated surface shows great potential for the prevention of postoperative adhesion during soft tissue repair. However, the existing patches suffer from the destruction of topography during superlubrication coating and lack of pro-healing capability. Herein, we demonstrate a facile and versatile strategy to develop a Janus nanofibrous patch (J-NFP) with antiadhesion and reactive oxygen species (ROS) scavenging functions. Specifically, sequential electrospinning is performed with initiators and CeO2 nanoparticles (CeNPs) embedded on the different sides, followed by subsurface-initiated atom transfer radical polymerization for grafting zwitterionic polymer brushes, introducing superlubricated skin on the surface of single nanofibers. The poly(sulfobetaine methacrylate) brush-grafted patch retains fibrous topography and shows a coefficient of friction of around 0.12, which is reduced by 77% compared with the pristine fibrous patch. Additionally, a significant reduction in protein, platelet, bacteria, and cell adhesion is observed. More importantly, the CeNPs-embedded patch enables ROS scavenging as well as inhibits pro-inflammatory cytokine secretion and promotes anti-inflammatory cytokine levels. Furthermore, the J-NFP can inhibit tissue adhesion and promote repair of both rat skin wounds and intrauterine injuries. The present strategy for developing the Janus patch exhibits enormous prospects for facilitating soft tissue repair.

Triune Nanomodulator Enables Exhausted Cytotoxic T Lymphocyte Rejuvenation for Cancer Epigenetic Immunotherapy.

Oncogene activation and epigenome dysregulation drive tumor initiation and progression, contributing to tumor immune evasion and compromising the clinical response to immunotherapy. Epigenetic immunotherapy represents a promising paradigm in conquering cancer immunosuppression, whereas few relevant drug combination and delivery strategies emerge in the clinic. This study presents a well-designed triune nanomodulator, termed ROCA, which demonstrates robust capabilities in tumor epigenetic modulation and immune microenvironment reprogramming for cancer epigenetic immunotherapy. The nanomodulator is engineered from a nanoscale framework with epigenetic modulation and cascaded catalytic activity, which self-assembles into a nanoaggregate with tumor targeting polypeptide decoration that enables loading of the immunogenic cell death (ICD)-inducing agent. The nanomodulator releases active factors specifically triggered in the tumor microenvironment, represses oncogene expression, and initiates the type 1 T helper (TH1) cell chemokine axis by reversing DNA hypermethylation. This process, together with ICD induction, fundamentally reprograms the tumor microenvironment and significantly enhances the rejuvenation of exhausted cytotoxic T lymphocytes (CTLs, CD8+ T cells), which synergizes with the anti-PD-L1 immune checkpoint blockade and results in a boosted antitumor immune response. Furthermore, this strategy establishes long-term immune memory and effectively prevents orthotopic colon cancer relapse. Therefore, the nanomodulator holds promise as a standalone epigenetic immunotherapy agent or as part of a combination therapy with immune checkpoint inhibitors in preclinical cancer models, broadening the array of combinatorial strategies in cancer immunotherapy.

Peiminine ameliorates Crohn's disease-like colitis by enhancing the function of the intestinal epithelial barrier through Nrf2/HO1 signal.

BACKGROUND AND AIMS: Impaired intestinal barrier function is key in maintaining intestinal inflammation in Crohn's disease (CD). However, no targeted treatment in clinical practice has been developed. Peiminine (Pm) strongly protects the epithelial barrier, the purpose of this study is to investigate whether Pm affects CD-like colitis and potential mechanisms for its action. METHODS: Trinitro-benzene-sulfonic acid (TNBS)-induced mice and Il-10-/- mice were used as CD animal models. Colitis symptoms, histological analysis, and intestinal barrier permeability were used to assess the Pm's therapeutic effect on CD-like colitis. The colon organoids were induced by TNF-α to evaluate the direct role of Pm in inhibiting apoptosis of the intestinal epithelial cells. Western blotting and small molecule inhibitors were used to investigate further the potential mechanism of Pm in inhibiting apoptosis of intestinal epithelial cells. RESULTS: Pm treatment reduced body weight loss, disease activity index (DAI) score, and inflammatory score, demonstrating that colonic inflammation in mice were alleviated. Pm decreased the intestinal epithelial apoptosis, improved the intestinal barrier function, and prevented the loss of tight junction proteins (ZO1 and claudin-1) in the colon of CD mice and TNF-α-induced colonic organoids. Pm activated Nrf2/HO1 signaling, which may protect intestinal barrier function. CONCLUSIONS: Pm inhibits intestinal epithelial apoptosis in CD mice by activating Nrf2/HO1 pathway. This partially explains the potential mechanism of Pm in ameliorating intestinal barrier function in mice and provides a new approach to treating CD.

Automatic segmentation of the tumor in nonsmall-cell lung cancer by combining coarse and fine segmentation.

OBJECTIVES: Radiotherapy plays an important role in the treatment of nonsmall-cell lung cancer (NSCLC). Accurate delineation of tumor is the key to successful radiotherapy. Compared with the commonly used manual delineation ways, which are time-consuming and laborious, the automatic segmentation methods based on deep learning can greatly improve the treatment efficiency. METHODS: In this paper, we introduce an automatic segmentation method by combining coarse and fine segmentations for NSCLC. Coarse segmentation network is the first level, identifing the rough region of the tumor. In this network, according to the tissue structure distribution of the thoracic cavity where tumor is located, we designed a competition method between tumors and organs at risk (OARs), which can increase the proportion of the identified tumor covering the ground truth and reduce false identification. Fine segmentation network is the second level, carrying out precise segmentation on the results of the coarse level. These two networks are independent of each other during training. When they are used, morphological processing of small scale corrosion and large scale expansion is used for the coarse segmentation results, and the outcomes are sent to the fine segmentation part as input, so as to achieve the complementary advantages of the two networks. RESULTS: In the experiment, CT images of 200 patients with NSCLC are used to train the network, and CT images of 60 patients are used to test. Finally, our method produced the Dice similarity coefficient of 0.78 ± 0.10. CONCLUSIONS: The experimental results show that the proposed method can accurately segment the tumor with NSCLC, and can also provide support for clinical diagnosis and treatment.

Flexible Bioactive Glass Nanofiber-Based Self-Expanding Cryogels with Superelasticity and Bioadhesion Enabling Hemostasis and Wound Healing.

Self-expanding cryogels hold unique prospects for treating uncontrollable hemorrhages. However, development of a mechanically robust, tissue-adhesive, and bioactive self-expanding cryogel enabling effective hemostasis and tissue repair has remained a great challenge. Herein, we report a superelastic cellular-structured bioactive glass nanofibrous cryogel (BGNC) composed of highly flexible BG nanofibers and citric acid-cross-linked poly(vinyl alcohol). These BGNCs exhibit high absorption capacity (3169%), fast self-expanding ability, near zero Poisson's ratio, injectability, high compressive recovery at a strain of 80%, robust fatigue resistance (almost no plastic deformation after 800 cycles at a strain of 60%), and good adhesion with diverse tissues. The BGNCs provide sustained release of Ca, Si, and P ions. Moreover, the BGNCs present better blood clotting and blood cell adhesion ability and superior hemostatic capacity in rabbit liver and femoral artery hemorrhage models as compared with commercial gelatin hemostatic sponges. In addition, BGNCs are able to stop bleeding in rat cardiac puncture injury in about 1 min. Furthermore, the BGNCs are capable of promoting rat full-thickness skin wound healing. The development of self-expanding BGNCs with superelasticity and bioadhesion provides a promising strategy for exploring multifunctional hemostatic and wound repair materials.

Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy.

Purpose: To introduce a model for automatic segmentation of thoracic organs at risk (OARs), especially the esophagus, in non-small cell lung cancer radiotherapy, using a novel two-step deep learning network. Materials and methods: A total of 59 lung cancer patients' CT images were enrolled, of which 39 patients were randomly selected as the training set, 8 patients as the validation set, and 12 patients as the testing set. The automatic segmentations of the six OARs including the esophagus were carried out. In addition, two sets of treatment plans were made on the basis of the manually delineated tumor and OARs (Plan1) as well as the manually delineated tumor and the automatically delineated OARs (Plan2). The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) of the proposed model were compared with those of U-Net as a benchmark. Next, two groups of plans were also compared according to the dose-volume histogram parameters. Results: The DSC, HD95, and ASD of the proposed model were better than those of U-Net, while the two groups of plans were almost the same. The highest mean DSC of the proposed method was 0.94 for the left lung, and the lowest HD95 and ASD were 3.78 and 1.16 mm for the trachea, respectively. Moreover, the DSC reached 0.73 for the esophagus. Conclusions: The two-step segmentation method can accurately segment the OARs of lung cancer. The mean DSC of the esophagus realized preliminary clinical significance (>0.70). Choosing different deep learning networks based on different characteristics of organs offers a new option for automatic segmentation in radiotherapy.

Hotspots and difficulties of biliary surgery in older patients.

ABSTRACT: With the accelerated aging society in China, the incidence of biliary surgical diseases in the elderly has increased significantly. The clinical characteristics of these patients indicate that improving treatment outcomes and realizing healthy aging are worthy of attention. How to effectively improve the treatment effect of geriatric biliary surgical diseases has attracted widespread attention. This paper reviews and comments on the hotspots and difficulties of biliary surgery in older patients from six aspects: (1) higher morbidity associated with an aging society, (2) prevention and control of pre-operative risks, (3) extending the indications of laparoscopic surgery, (4) urgent standardization of minimally invasive surgery, (5) precise technological progress in hepatobiliary surgery, and (6) guarantee of peri-operative safety. It is of great significance to fully understand the focus of controversy, actively make use of its favorable factors, and effectively avoid its unfavorable factors, for further improving the therapeutic effects of geriatric biliary surgical diseases, and thus benefits the vast older patients with biliary surgical diseases. Accordingly, a historical record with the highest age of 93 years for laparoscopic transcystic common bile duct exploration has been created by us recently.

Construction of a fecal immune-related protein-based biomarker panel for colorectal cancer diagnosis: a multicenter study.

Purpose: To explore fecal immune-related proteins that can be used for colorectal cancer (CRC) diagnosis. Patients and methods: Three independent cohorts were used in present study. In the discovery cohort, which included 14 CRC patients and 6 healthy controls (HCs), label-free proteomics was applied to identify immune-related proteins in stool that could be used for CRC diagnosis. Exploring potential links between gut microbes and immune-related proteins by 16S rRNA sequencing. The abundance of fecal immune-associated proteins was verified by ELISA in two independent validation cohorts and a biomarker panel was constructed that could be used for CRC diagnosis. The validation cohort I included 192 CRC patients and 151 HCs from 6 different hospitals. The validation cohort II included 141 CRC patients, 82 colorectal adenoma (CRA) patients, and 87 HCs from another hospital. Finally, the expression of biomarkers in cancer tissues was verified by immunohistochemistry (IHC). Results: In the discovery study, 436 plausible fecal proteins were identified. And among 67 differential fecal proteins (|log2 fold change| > 1, P< 0.01) that could be used for CRC diagnosis, 16 immune-related proteins with diagnostic value were identified. The 16S rRNA sequencing results showed a positive correlation between immune-related proteins and the abundance of oncogenic bacteria. In the validation cohort I, a biomarker panel consisting of five fecal immune-related proteins (CAT, LTF, MMP9, RBP4, and SERPINA3) was constructed based on the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. The biomarker panel was found to be superior to hemoglobin in the diagnosis of CRC in both validation cohort I and validation cohort II. The IHC result showed that protein expression levels of these five immune-related proteins were significantly higher in CRC tissue than in normal colorectal tissue. Conclusion: A novel biomarker panel consisting of fecal immune-related proteins can be used for the diagnosis of CRC.

Synthesis and in vitro antitumor activity of 1,3,4-oxadiazole derivatives based on benzisoselenazolone.

A series of novel 1,3,4-oxadiazole derivatives based on benzisoselenazolone has been prepared and tested for antiproliferative activity in vitro against the cells of human cancer cell lines: SSMC-7721 (human liver cancer cell), MCF-7 (human breast cancer cell) and A549 (human lung cancer cell). All the compounds obtained exhibited antiproliferative activity and showed selective cytotoxicity against different cancer cells. Compounds 7d and 7i showed significant antiproliferative activities against MCF-7 cells, with IC50 values of 1.07 and 1.76 µM respectively. Compound 7d were found to be the most potent compound against SSMC-7721 cells, with IC50 values 4.46 µM.