MiR-378 is an independent prognostic factor and inhibits cell growth and invasion in colorectal cancer.

BACKGROUND: MicroRNAs(miRNAs) are small non-coding RNAs that participate in a variety of biologic processes, and dysregulation of miRNA is always associated with cancer development and progression. Aberrant expression of miR-378 has been found in some types of cancer. However, effects and potential mechanisms of miR-378 in colorectal cancer (CRC) have not been explored. METHODS: Quantitative RT-PCR was performed to evaluate miR-378 levels in CRC cell lines and 84 pairs of CRC cancer and normal adjacent mucosa. Kaplan-Meier and Cox proportional regression analyses were utilized to determine the association of miR-378 expression with survival of patients. MTT and invasion assays were used to determine the role of miR-378 in regulation of CRC cancer cell growth and invasion, respectively. Tumor growth was assessed by subcutaneous inoculation of cells into BALB/c nude mice. Luciferase assay was performed to assess miR-378 binding to vimentin gene. RESULTS: In this study, we confirmed that miR-378 significantly down-regulated in CRC cancer tissues and cell lines. Moreover, patients with low miR-378 expression had significantly poorer overall survival, and miR-378 expression was an independent prognostic factor in CRC. Over-expression of miR-378 inhibited SW620 cell growth and invasion, and resulted in down-regulation of vimentin expression. However, miR-378 knock-down promoted these processes and enhanced the expression of vimentin. In addition, we further identified vimentin as the functional downstream target of miR-378 by directly targeting the 3'-UTR of vimentin. CONCLUSIONS: In conclusion, miR-378 may function as a tumor suppressor and plays an important role in inhibiting tumor growth and invasion. Our present results implicate the potential effects of miR-378 on prognosis and treatment of CRC cancer.

[Calibration transfer without standards for spectral analysis based on stability competitive adaptive reweighted sampling].

A novel calibration transfer method based on stability competitive adaptive reweighted sampling (SCARS) was proposed in the present paper. An informative criterion, i. e. the stability index, defined as the absolute value of regression coefficient divided by its standard deviation was used. And the root mean squared error of prediction (RMSEP) after transfer was also used. The wavelength variables which were important and insensitive to influence of measurement parameters were selected. And then the differences in responses of different instruments or measurement conditions for a specific sample were eliminated or reduced to improve the calibration transfer results. Moreover, in the proposed method, the spectral variables were compressed, making calibration transfer more stable. The application of the proposed method to calibration transfer of NIR analysis was evaluated by analyzing the corn with different NIR spectrometers. The results showed that this method can well correct the difference between instruments and improve the analytical accuracy. The transfer results obtained by the proposed method, orthogonal signal correction (OSC), Monte Carlo uninformative variable elimination (MCUVE) and competitive adaptive reweighted sampling (CARS), respectively, for corn with different NIR spectrometers indicated that the former gave the best analytical accuracy, and was effective for the spectroscopic data compression which can simplify and optimize the transfer process.

Up-regulation of miR-224 promotes cancer cell proliferation and invasion and predicts relapse of colorectal cancer.

BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNAs that can function as oncogenes or tumor suppressors in human cancer. Abnormally expressed miR-224 was found to play a fundamental role in several types of cancer. The aim of this study was to investigate the prognostic and biological values of miR-224 in colorectal cancer (CRC). METHODS: Quantitative RT-PCR (qRT-PCR) was used to evaluate expression levels of miR-224. The postoperative survival rate was analyzed with Kaplan-Meier method. The roles of miR-224 in cell proliferation, migration and invasion were analyzed with pre-miR-224 transfected cells. In addition, the regulation of SMAD4 by miR-224 was evaluated by qRT-PCR, Western blotting and luciferase reporter assays. RESULTS: In the present study, we demonstrated that miR-224 was significantly up-regulated in CRC tissue samples and associated with disease relapse and a relative poorer disease-free survival rate. Moreover, ectopic expression of miR-224 potently promoted tumor cell proliferation, migration and invasion in vitro. Furthermore, the over-expression of miR-224 in CRC cell lines decreased SMAD4 expression at the translational level and decreased SMAD4-driven luciferase-reporter activity. CONCLUSIONS: Our data suggest that miR-224 could play an oncogenic role in the cellular processes of CRC and represent a novel biomarker for tumor relapse of CRC patients.

Identification of colitis and cancer in colon biopsies by Fourier Transform Infrared spectroscopy and chemometrics.

Cancer is a disease that does great harms to the health of human beings. FT-IR spectroscopy could identify variability at the molecular level in biological specimens. It is a rapid and noninvasive method, which could be used intraoperatively to modify surgical procedures. The aim of this paper is to identify and separate cancer from colitis in endoscopic colon biopsies through the use of FT-IR spectroscopy. A total of 88 endoscopic colon samples, including 41 cases of colitis and 47 cases of colon cancer, were obtained. Specimens were placed on an ATR accessory linked to FT-IR spectrometer with a MCT detector for greater stability and sensitivity. Later, specimens were sent for the histological examination as the reference in the spectral analysis. 41 colitis and 47 cancer specimens were compared. Spectra preprocessed with smoothing and normalization were used for discrimination analysis. PCA was processed to simplify the spectrum data set. Naive Bayes classifier model was constructed for diagnostic classification. Leave-one-out cross-validation method was utilized to assess the discrimination results. The sensitivity of FT-IR detection for cancer achieves 97.6%. The results showed that colon cancer could be distinguished from colitis with high accuracy using FT-IR spectroscopy and chemometrics.

[Research on continuum power regression in noninvasive measurement of human blood glucose].

Accurate measurement of human blood glucose concentration is very significant for the treatment of diabetes. In the present paper, the method of continuum power regression can improve the predictive accuracy of noninvasive measurement of human blood glucose concentration with near infrared spectroscopy. This method is the expansion of the traditional method of partial least squares (PLS). It can achieve simpleness, and can significantly improve predictive accuracy when the power coefficient is fit. Using the method, quantitative analysis models of four ingredient experiment and noninvasive experiment of body were established, and these models can be used to predict the predictive samples. Experimental results show that compared with the PLS, the quantitative analysis models of this method not only can improve predictive accuracy, but also can set different power coefficient for different individuals to achieve the best results of models. According to different individuals, the power coefficient can be selected flexibly, which is of great value to the research on noninvasive measurement of human blood glucose concentration with near infrared spectroscopy.

MicroRNA-23b-3p targets non-SMC condensing I complex subunit G to promote proliferation and inhibit apoptosis of colorectal cancer cells via regulation of the PI3K/AKT signaling pathway.

Colorectal cancer (CRC) is one of the most common types of malignancy worldwide and has a poor prognosis. Non-SMC condensing I complex subunit G (NCAPG) has been reported to be upregulated in numerous types of malignant tumor. However, to the best of our knowledge, its clinicopathological and biological significance in CRC remain to be elucidated. The results of the present study revealed that NCAPG expression levels were upregulated in human CRC tissues and cell lines. The upregulated expression of NCAPG was positively associated with patient clinicopathological characteristics, such as differentiation and tumor size, and independently associated with poor survival. Consistent with the clinical observations, NCAPG was discovered to promote the proliferation and inhibit the apoptosis of CRC cells. Moreover, NCAPG-knockdown inhibited CRC cell proliferation by regulating the PI3K/AKT signaling pathway. Furthermore, NCAPG was identified as a potential target of microRNA (miR)-23b-3p, which was subsequently demonstrated to negatively regulate NCAPG expression. In conclusion, the findings of the current study indicated that the miR-23b-3p/NCAPG/PI3K/AKT signaling axis may play an important role in CRC carcinogenesis, and the status of the molecule may represent a promising prognostic marker for the disease.

[A path-length correction method on biochemical parameter nondestructive measuring of folium].

Vis/NIR spectroscopy technology is capable of analyzing the content of biochemical parameter in folium rapidly and nondestructively. In the process of spectrum analysis, the variations in path-length between different samples exist, with the random light scattering and leaf thickness perturbations, which influence the precision of quantitative analysis model. In order to resolve this problem, an improved path-length correction method based on Extended Multiplicative Scattering Correction is presented. In this paper, firstly the theory of EMSC algorithm is deduced. EMSC method incorporates both chemical terms and wavelength functions to help realize the efficient separation of path-length and interest concentration. Secondly two experiments were implemented to demonstrate the validity of the method. In Experiment 1, sixteen samples of different thickness but almost the same chlorophyll content were selected, and how the path-length affects the spectrum was compared, after EMSC preprocessing, the variable coefficient of spectrum could approach the repeatability error of spectrometer. In Experiment 2, thirty-two samples of different thickness and chlorophyll content were selected. PLS model established using cross validation was employed to evaluate the efficiency of the presented algorithm. Before the preprocessing, the root mean squared error of prediction is 3.9 SPAD with 5 principal components. After preprocessing, the predicted root mean squared error is 2.2 SPAD with 12 principal components. The results indicate that the improved EMSC preprocessing method could exactly eliminate the spectrum difference caused by the path-length variations between different foliums, enhance the sensitivity of concentration and spectral data, and increase the precision of calibrated model.

[A principal components selection method based on the modified randomization test for avoiding over-fit and under-fit in spectra calibration].

More or less principal components often give an over-fit or under-fit quantitative calibration model. In order to avoid over-fit or under-fit in spectra calibration, a principal components selection method based on a modified randomization test is proposed. Three near infrared spectra experiments (the complexity of the sample components in each experiment is increasing by degrees) are introduced in this paper for evaluating the proposed method. The method is compared with the cross-validation method. And the spectra model complexity of how to affect the prediction performance of calibration is discussed. Then the adaptability of this modified randomization test to the uncertainty complex spectra model is also discussed. The results indicate that the proposed method has no process of leaving some samples out like cross-validation does, and all the training samples are considered when selecting principal components, so the problem of over-fit or under-fit can be avoided, which is benefit to improve prediction performance of calibration in spectral analysis. And the modified randomization test method is different with the commonly used randomization test that a simplified criterion is introduced here and it is easy to implement. With the proposed method, the authors can have a visualized and interactive process when selecting principal components. For these three experiments, 4, 5 and 8 selected principal components are employed in calibration respectively and the prediction result is the best for the independent external prediction sets. It is also implied that the proposed method is adaptable to the complex samples with more variables and little samples.

[Application of partial robust M-regression in noninvasive measurement of human blood glucose concentration with near-infrared spectroscopy].

In the study of non-invasive measurement of human blood glucose concentration with near-infrared spectroscopy, the partial robust M-regression (PRM) is proposed in the present paper to solve the robustness of calibration model affected by outliers existing in the spectra data set. While keeping the good properties of M-estimators if an appropriate weighting scheme is chosen, PRM inherits the speed of computation and easy realization of the iterative reweighted partial least squares (IRPLS) algorithm, but is robust to all types of outliers. With the pretreatment of spectra based on PRM, the root mean square error of prediction (RMSEP) of calibration model was presented and compared with partial least squares (PLS). Experimental results show that the robust calibration model PRM produces better prediction of glucose than the model of PLS when the components of the samples increase which is significant for non-invasive prediction of blood glucose levels.

Cytochrome C Oxidase Assembly Factor 1 Homolog Predicts Poor Prognosis and Promotes Cell Proliferation in Colorectal Cancer by Regulating PI3K/AKT Signaling.

PURPOSE: Colorectal cancer (CRC) is one of the most common malignancies in the world. The prognosis of advanced CRC is still poor. The purpose of this study was to identify a gene expression profile associated with CRC that may contribute to the early diagnosis of CRC and improve patient prognosis. PATIENTS AND METHODS: Five pairs of CRC tissues and paracancerous tissues were used to identify causative genes using microarray assays. The prognostic value of Cytochrome C Oxidase Assembly Factor 1 Homolog (COA1) in CRC was assessed in 90 CRC patients. Loss-of-function assays, cell proliferation assays using Celigo and MTT, colony formation assays, a subcutaneous xenograft mouse model, and apoptosis assays were used to define the effects of downregulation of COA1 in CRC cells in vitro and in vivo. The underlying molecular mechanisms of COA1 in CRC were also investigated. RESULTS: The causative gene COA1 was identified through microarray analysis. COA1 expression in CRC was notably associated with pathologic differentiation, tumor size, and tumor depth. COA1 expression may act as an independent prognostic factor for overall survival of CRC. Knockdown of COA1 inhibited the proliferation of CRC cells in vitro and the tumorigenicity of CRC cells in vivo. Decreased COA1 expression induced apoptosis of CRC cells. Based on the microarray assay results comparing HCT116 cells transfected with lentivirus encoding anti-COA1 shRNA or negative control shRNA, ingenuity pathway analysis (IPA) revealed that the PI3K/AKT signaling pathway was significantly enriched. Moreover, CCND1, mTOR, AKT1, and MDM2 were identified as the downstream genes of COA1. CONCLUSION: These findings demonstrate that COA1 promotes CRC cell proliferation and inhibits apoptosis by regulating the PI3K/AKT signaling pathway. Our results implicate COA1 as a potential oncogene involved in tumor growth and progression of CRC.

[A hyperspectral subpixel target detection method based on inverse least squares method].

In the present paper, an inverse least square (ILS) method combined with the Mahalanobis distance outlier detection method is discussed to detect the subpixel target from the hyperspectral image. Firstly, the inverse model for the target spectrum and all the pixel spectra was established, in which the accurate target spectrum was obtained previously, and then the SNV algorithm was employed to preprocess each original pixel spectra separately. After the pretreatment, the regressive coefficient of ILS was calculated with partial least square (PLS) algorithm. Each point in the vector of regressive coefficient corresponds to a pixel in the image. The Mahalanobis distance was calculated with each point in the regressive coefficient vector. Because Mahalanobis distance stands for the extent to which samples deviate from the total population, the point with Mahalanobis distance larger than the 3sigma was regarded as the subpixel target. In this algorithm, no other prior information such as representative background spectrum or modeling of background is required, and only the target spectrum is needed. In addition, the result of the detection is insensitive to the complexity of background. This method was applied to AVIRIS remote sensing data. For this simulation experiment, AVIRIS remote sensing data was free downloaded from the NASA official websit, the spectrum of a ground object in the AVIRIS hyperspectral image was picked up as the target spectrum, and the subpixel target was simulated though a linear mixed method. The comparison of the subpixel detection result of the method mentioned above with that of orthogonal subspace projection method (OSP) was performed. The result shows that the performance of the ILS method is better than the traditional OSP method. The ROC (receive operating characteristic curve) and SNR were calculated, which indicates that the ILS method possesses higher detection accuracy and less computing time than the OSP algorithm.

[Study on resistance to motion artifact in pulse oximetry measurement using segment filter method].

The authors proposed a method which combined the differential threshold segment with median filter to eliminate abrupt artifact motion interference in the use of pulse oximeter, and further more, by adding the window moving average filter, this method could reduce the periodic artifact motion interrupt in some way. In the experiment, the authors intently simulated the common finger motion to get the artifact motion "corrupted" signal with our self-made reflectance oximeter system. The comparison of the original PPG signal and processed PPG signal shows that the method we proposed performed well in an effort to reduce the common artifact motion interrupt. Finally, in order to figure out what effort this method can make for the accuracy of oxygen saturation measurement, the ration of AC and DC component in the red and infrared signal directly associated with the pulse oxygen saturation was calculated. The result indicates that this method can reduce the error caused by the artifact motion and stabilize the rate of false reading of pulse oximeter under the finger motion state. More importantly, this method needs only a small calculation cost, so it could be applied in the real-time PPG signal processing without the need of powerful hardware.

[Development of chlorophyll concentration nondestructive measurement instrument based on spectral analysis technology].

A portable nondestructive measuring instrument for plant chlorophyll was developed, which can perform real-time, quick and nondestructive measurement of chlorophyll. The instrument is mainly composed of four parts, including leaves clamp, driving circuit of light source, photoelectric detection and signal conditioning circuit and micro-control system. A new scheme of light source driving was proposed, which can not only achieve constant current, but also control the current by digital signal. The driving current can be changed depending on different light source and measurement situation by actual operation, which resolves the matching problem of output intensity of light source and input range of photoelectric detector. In addition, an integrative leaves clamp was designed, which simplified the optical structure, enhanced the stability of apparatus, decreased the loss of incident light and improved the signal-to-noise ratio and precision. The photoelectric detection and signal conditioning circuit achieve the conversion between optical signal and electrical signal, and make the electrical signal meet the requirement of AD conversion, and the photo detector is S1133-14 of Hamamatsu Company, with a high detection precision. The micro-control system mainly achieves control function, dealing with data, data storage and so on. As the most important component, microprocessor MSP430F149 of TI Company has many advantages, such as high processing speed, low power, high stability and so on. And it has an in-built 12 bit AD converter, so the data-acquisition circuit is simpler. MSP430F149 is suitable for portable instrument. In the calibration experiment of the instrument, the standard value was measured by chlorophyll meter SPAD-502, multiple linear calibration models were built, and the instrument performance was evaluated. The correlation coefficient between chlorophyll prediction value and standard value is 0.97, and the root mean square error of prediction is about 1.3 SPAD. In the evaluation experiment of the instrument repeatability, the root mean square error is 0.1 SPAD. Results of the calibration experiment show that the instrument has high measuring precision and high stability.

[Application of probabilistic neural networks method to gastric endoscope samples diagnosis based on FTIR spectroscopy].

In the present paper, probabilistic neural network method was applied to the classification of gastric endoscope samples based on FTIR spectroscopy for higher discrimination correctness than the conventional linear discriminant analysis algorithm. The probabilistic neural network (PNN) is a kind of radial basis network suitable for discriminant analysis. There are several advantages of PNN method: less time is needed to train the model, higher correctness could be achieved, global optimal solution could be obtained and so on. In this paper, PNN method was utilized to classify gastric endoscopic biopsies into healthy, gastritis, and malignancy. Firstly, principal component analysis was carried out for the pretreated sample spectra. Principal components analysis is a quantitatively rigorous method for achieving the simplification. The method generates a new set of variables, called principal components. Each principal component is a linear combination of the original variables. All the principal components are orthogonal to each other, so there is no redundant information. The principal components as a whole form an orthogonal basis for the space of the data. And then, the scores of principal components were selected as input to train the PNN model. Finally, PNN model was established. In this experiment, a total of 118 gastric endoscopic biopsies, including 35 cases of cancer, 64 cases of gastritis, and 19 healthy tissue samples, were obtained at the First Hospital of Xi'an Jiaotong University, China. Fifty nine samples were selected to establish the PNN classification model. The rest of the samples were used as the test set to valid the discriminant analysis model. The total discrimination correctness of normal, inflammation and gastric cancer achieved 81.4%.

[Chlorophyll content nondestructive measurement method based on Vis/NIR spectroscopy].

In the present paper a method based on Vis/NIR spectral analysis technology was applied to the nondestructive measurement of plant chlorophyll content. Firstly, the Vis/NIR spectra in the wavelength range from 500 to 900 nm of the plant leaves were acquired from 35 samples by transmittance and reflectance method, and then three different mathematical treatments were used in original spectra data pretreatment to decrease the noise: moving average smoothing with the segment size 5, first Savitzky-Golay derivative, and wavelet transform (WT) way. Secondly, a total of 35 samples were examined in the test, in which 23 samples were selected randomly for model building and the other 12 for model prediction, then partial least squares (PLS) method was used to develop the quantitative analysis model for chlorophyll content with absorbance spectroscopy, and 7 principal components (PCs) were selected. Finally, this model was used to predict the chlorophyll content of 12 unknown leaf samples in prediction collection. The experiment result indicated that the better prediction performance was achieved with the correlation coefficient between the prediction values and the truth values being 0.93, and the root mean squared error of prediction is about 1.1 SPAD. It could be concluded that it is feasible to measure plant chlorophyll content based on visible/near infrared (Vis/NIR) spectroscopy. And it is also significant in realizing rapid and nondestructive measurement of chlorophyll content in the future.

[A hyperspectral small target detection method based on outlier detection].

In the present paper, a new method was discussed, which used outlier detection algorithms of spectral analytical technology to tell the small target from background. First, continuum removal and standard normal variate were employed to pretreat the AVIRIS remotely-sensed data. It could be regarded that continuum is the absorption of background, and the characteristic absorptions are superposed on the continuum. So the continuum removal is frequently applied to remotely-sensed hyperspectral data to eliminate the contribution of background absorption and separate the characteristic absorption of concerned objects from background. SNV corrects each spectrum by subtracting the mean and dividing by the standard deviation for that spectrum. After the pretreatment, spectral angle mapping was used to reduce the dimension of hyperspectral data. Since this mapping process calculated the similarity between the spectra of each pixel and the average spectrum, no prior information such as standard spectrum library is required. And then, Mahalanobis distances were calculated. As Mahalanobis distance shows the extent to which samples deviate from the total population, the points whose Mahalanobis distance are larger than adaptive threshold were regarded as small target. The adaptive threshold was determined by data mean value and maximum value. Applying the algorithm above to a set of AVIRIS remotely-sensed hyperspectral data which was free downloaded from the NASA official website, small target on the concerned area was picked out correctly. In addition, the above mentioned took about 1/8 time as much as the traditional Mahalanobis distance method without prior reducing dimension of hyperspectral data. Compared with traditional algorithm, no prior information is needed, and less calculating work and time is required. Still, it has got a satisfying accuracy.

The prognostic value of proliferating cell nuclear antigen expression in colorectal cancer: A meta-analysis.

BACKGROUND: A number of studies have attempted to determine the prognostic significance of proliferating cell nuclear antigen (PCNA) in patients with colorectal cancer (CRC), but the reports are controversial and inconsistent. Thus, we conducted a meta-analysis to clarify the value of PCNA in CRC prognosis. METHODS: A systematic search of relevant studies was performed in 4 electronic databases including PubMed, Cochrane Library, Embase, and Web of Science until February 2018. Hazard ratios (HRs) combined with 95% confidence intervals (95% CIs) were used to evaluate the relationship of PCNA expression with overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS). RESULTS: A total of 1372 CRC patients in 14 studies were identified eventually in our meta-analysis. The pooled HRs demonstrated that CRC patients with high PCNA expression was significantly correlated with poor OS (HR = 1.81; 95% CI: 1.51-2.17; P = .000), CSS (HR = 1.99; 95% CI: 1.04-3.79; P = .037); but not significantly with DFS (HR = 2.48; 95% CI: 0.98-6.26; P = .055). Sensitivity analysis showed the pooled HRs for OS, CSS, and DFS were stable when the included studies were removed one by one. CONCLUSION: Our meta-analysis suggested that high PCNA expression was associated with poor prognosis, and it could serve as a reliable and prognostic biomarker in CRC patients. More large-scale studies are needed to further support the conclusion.

[Application of DS algorithm to the calibration transfer in near-infrared spectroscopy].

Calibration transfer in multivariate calibration is one of the most important and key issues in near-infrared spectral analysis technology. The model was transferred by means of finding the transformation relation between two instruments of the same type, so that the model established on one instrument could be used on the other to predict the spectral response. In this paper, direct standardization (DS) algorithm was investigated for resolving calibration transfer in multivariate calibration of chemometrics. In addition, the selection method for the transfer set samples was studied in this paper. The experiment of model transfer was carried out between two AOTF near-infrared spectrometers. Firstly, the Kennard/Stone algorithm was adopted to select the transfer set samples, and then DS algorithm was applied to the calibration transfer. The experimental results showed that DS algorithm was effective for model transfer. DS algorithm is applicable to not only instrument standardization, but also the correction of the spectral differences induced by baseline drift for a long time or the replacement of measurement modules for the same instrument.

[Application of KNN method to cancer diagnosis using Fourier-transform infrared spectroscopy].

Early diagnosis and early medical treatments are the keys to save the patients' lives and improve their living quality. Fourier transform infrared (FTIR) spectroscopy can be used to distinguish malignant from normal tissues at the molecular level. In the present paper, programs were made with chemometrics method of pattern recognition to classify unknown tissue samples. Spectral data were pretreated by using smoothing, SNV and RHM method. Cross validation was used to test the discrimination effect of KNN method. A total of 63 gastric tissue samples were employed in this study, including 26 cases of normal tissue samples and 37 cases of cancerous tissue samples. The recognition results of the KNN method showed that the correctness of classification achieved 91.7%.

Adenoviral E4 34K protein interacts with virus packaging components and may serve as the putative portal.

Studies on dsDNA bacteriophages have revealed that a DNA packaging complex assembles at a special vertex called the 'portal vertex' and consists of a portal, a DNA packaging ATPase and other components. AdV protein IVa2 is presumed to function as a DNA packaging ATPase. However, a protein that functions as a portal is not yet identified in AdVs. To identify the AdV portal, we performed secondary structure analysis on a set of AdV proteins and compared them with the clip region of the portal proteins of bacteriophages phi29, SPP1 and T4. Our analysis revealed that the E4 34K protein of HAdV-C5 contains a region of strong similarity with the clip region of the known portal proteins. E4 34K was found to be present in empty as well as mature AdV particles. In addition, E4 34K co-immunoprecipitates and colocalizes with AdV packaging proteins. Immunogold electron microscopy demonstrated that E4 34K is located at a single site on the virus surface. Finally, tertiary structure prediction of E4 34K and its comparison with that of single subunits of Phi29, SPP1 and T4 portal proteins revealed remarkable similarity. In conclusion, our results suggest that E4 34K is the putative AdV portal protein.