Relationship between changes in the course of COVID-19 and ratio of neutrophils-to-lymphocytes and related parameters in patients with severe vs. common disease.

To assess the relationship between the neutrophil-to-lymphocyte ratio (NLR) and related parameters to the severity of coronavirus disease 2019 (COVID-19) symptoms. Clinical data from 38 COVID-19 patients who were diagnosed, treated and discharged from the Qishan Hospital in Yantai over the period from January to February 2020 were analysed. NLR and procalcitonin (PCT) were determined in the first and fourth weeks after their admission, along with the clinical characteristics and laboratory test results of these patients. Based on results as obtained on the first and fourth weeks after admission, five indices consisting of NLR, white blood cells, neutrophils, lymphocytes (LY) and monocytes (MON) were selected to generate receiver operating characteristic curves, while optimal cutoff values, sensitivities and specificities were obtained according to the Yuden index. Statistically significant differences in neutrophils, LY and the NLR were present in the severe vs. moderate COVID-19 group from the first to the fourth week of their hospitalisation. The cut-off value of NLR for predicting the severity of COVID-19 was 4.425, with a sensitivity of 0.855 and a specificity of 0.979. A statistically significant positive correlation was present between PCT and NLR in the severe group as determined within the first week of admission. NLR can serve as a predictor of COVID-19 disease severity as patients' progress from the first to the fourth week of their hospitalisation. The statistically significant positive correlation between levels of NLR and PCT in severe patients indicated that increases in NLR were accompanied with gradual increases in PCT.

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up.

BACKGROUND: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. METHODS: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. RESULTS: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. CONCLUSIONS: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

Hepatitis C Virus Genotype Analyses in Chronic Hepatitis C Patients and Individuals With Spontaneous Virus Clearance Using a Newly Developed Serotyping Assay.

BACKGROUND: We developed a novel HCV serotyping assay and detected the genotypes in chronic hepatitis C (CHC) patients and individuals with spontaneous viral clearance (SVC). METHODS: Nine hundred and ninety-seven patients were enrolled in a previous study; their samples were genotyped originally using the molecular assays. Among them, 190 patients achieved sustained virological response; the post-treatment samples were also serotyped. Moreover, 326 samples from follow-up cohorts were serotyped, among whom 66 were from SVC individuals, and 260 from CHC patients. RESULTS: Nine hundred and fifty-eight out of 997 samples were available for serotyping, among which 29 samples generated indeterminate serotyping results. The consistency between the genotyping and serotyping assays was 91.50% (850/929). The specificity and sensitivity were 98.45% and 88.77% for genotype 1, 96.42% and 93.97% for genotype 2, and 94.15% and 80.52% for non-genotype 1 or 2. However, only 41 of 60 genotype-6 samples were correctly serotyped. Little difference was found in the 190 paired serotyping results. No difference existed in the genotype distribution between the SVC and CHC groups (P = 0.08). CONCLUSIONS: The assay provides an accurate alternative for determining HCV genotypes, whereas it is not recommended for detecting genotype 6. Furthermore, it facilitates identifying the genotypes in SVC individuals. HCV genotype has little impact on SVC.

Asialoglycoprotein receptor facilitates infection of PLC/PRF/5 cells by HEV through interaction with ORF2.

Although the biological and epidemiological features of hepatitis E virus (HEV) have been studied extensively in recent years, the mechanism by which HEV infects cells is still poorly understood. In this study, coimmunoprecipitation, pull-down, and ELISA were used to show that the HEV ORF2 protein interacts directly with the ectodomain of both ASGR1 and ASGR2. Susceptibility to HEV correlated positively with the expression level of surface asialoglycoprotein receptor (ASGPR) in cell lines. ASGPR-directed small interfering RNA (siRNA) in HEV-infected PLC/PRF/5 cells had no significant effect on HEV release, suggesting that ASGPR mainly regulates the viral binding and entry steps. Both the purified ASGPR ectodomain and anti-ASGPR antibodies disturbed the binding of HEV to PLC/PRF/5 cells. The classic ASGPR ligands asialofetuin, asialoganglioside, and fibronectin competitively inhibited the binding of HEV to hepatocytes in the presence of calcium. HeLa cell lines stably expressing ASGPR displayed increased HEV-binding capacity, whereas ASGPR-knockout PLC/PRF/5 cell lines had lower HEV-binding capacity. Thus, our study demonstrates that ASGPR is involved in and facilitates HEV infection by binding to ORF2. J. Med. Virol. 88:2186-2195, 2016. © 2016 Wiley Periodicals, Inc.

Use of two gene panels for prostate cancer diagnosis and patient risk stratification.

Currently, no ideal prostate cancer (PCa) diagnostic or prognostic test is available due to the lack of biomarkers with high sensitivity and specificity. There is an unmet medical need to develop combinations of multiple biomarkers which may have higher accuracy in detection of PCa and stratification of aggressive and indolent cancer patients. The aim of this study was to test two biomarker gene panels in distinguishing PCa from benign prostate and high-risk, aggressive PCa from low-risk, indolent PCa, respectively. We identified a five-gene panel that can be used to distinguish PCa from benign prostate. The messenger RNA (mRNA) expression signature of the five genes was determined in 144 PCa and benign prostate specimens from prostatectomy. We showed that the five-gene panel distinguished PCa from benign prostate with sensitivity of 96.59 %, specificity of 92.86 %, and area under the curve (AUC) of 0.992 (p < 0.0001). The five-gene panel was further validated in a 137 specimen cohort and showed sensitivity of 84.62 %, specificity of 91.84 %, and AUC of 0.942 (p < 0.0001). To define subtypes of PCa for treatment guidance, we examined mRNA expression signature of an eight-gene panel in 87 PCa specimens from prostatectomy. The signature of the eight-gene panel was able to distinguish aggressive PCa (Gleason score >6) from indolent PCa (Gleason score ≤6) with sensitivity of 90.28 %, specificity of 80.00 %, and AUC of 0.967 (p < 0.0001). This panel was further validated in a 158 specimen cohort and showed significant difference between aggressive PCa and indolent PCa with sensitivity of 92.57 %, specificity of 70.00 %, and AUC of 0.962 (p < 0.0001). Our findings in assessing multiple biomarkers in combination may provide new tools to detect PCa and distinguish aggressive and indolent PCa for precision and personalized treatment. The two biomarker panels may be used in clinical settings for accurate PCa diagnosis and patient risk stratification for biomarker-guided treatment.

Vitronectin: a promising breast cancer serum biomarker for early diagnosis of breast cancer in patients.

Breast cancer is the most common cancer in women worldwide, identification of new biomarkers for early diagnosis and detection will improve the clinical outcome of breast cancer patients. In the present study, we determined serum levels of vitronectin (VN) in 93 breast cancer patients, 30 benign breast lesions, 9 precancerous lesions, and 30 healthy individuals by enzyme-linked immunosorbent assays. Serum VN level was significantly higher in patients with stage 0-I primary breast cancer than in healthy individuals, patients with benign breast lesion or precancerous lesions, as well as those with breast cancer of higher stages. Serum VN level was significantly and negatively correlated with tumor size, lymph node status, and clinical stage (p < 0.05 in all cases). In addition, VN displayed higher area under curve (AUC) value (0.73, 95 % confidence interval (CI) [0.62-0.84]) than carcinoembryonic antigen (CEA) (0.64, 95 % CI [0.52-0.77]) and cancer antigen 15-3 (CA 15-3) (0.69, 95 % CI [0.58-0.81]) when used to distinguish stage 0-I cancer and normal control. Importantly, the combined use of three biomarkers yielded an improvement in receiver operating characteristic curve with an AUC of 0.83, 95 % CI [0.74-0.92]. Taken together, our current study showed for the first time that serum VN is a promising biomarker for early diagnosis of breast cancer when combined with CEA and CA15-3.

Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy.

The present study aims to identify distinctive Raman spectrum metabolic peaks to predict hepatocellular carcinoma (HCC). We performed a label-free, non-invasive surface-enhanced Raman spectroscopy (SERS) test on 230 serum samples including 47 HCC, 60 normal controls (NC), 68 breast cancer (BC) and 55 lung cancer (LC) by mixing Au@AgNRs with serum directly. Based on the observed SERS spectra, discriminative metabolites including tryptophan, phenylalanine, and etc. were found in HCC, when compared with BC, LC, and NC (P<0.05 in all). Common metabolites-proline, valine, adenine and thymine were found in HCC, BC and LC with compared to NC group (P<0.05). Importantly, Raman spectra of HCC serum biomarker AFP were firstly detected to analyze the HCC prominent peak. Orthogonal partial least squares discriminant analysis was adopted to assess the diagnostic accuracy; area under curve value of HCC is 0.991. This study provides new insights into the HCC metabolites detection through Raman spectroscopy.

IgG, IgM and IgA antibodies against the novel polyprotein in active tuberculosis.

BACKGROUND: The present study was aimed to evaluate whether IgG, IgM and IgA antibodies levels detected against a novel Mycobacterium tuberculosis polyprotein 38 F-64 F (with 38 F being the abbreviation for 38kD-ESAT6-CFP10 and 64 F for Mtb8.4-MPT64-TB16.3-Mtb8) are suitable for diagnosing active tuberculosis, and for monitoring the efficacy of chemotherapy on TB patients. METHODS: In this study, a total of 371 active TB patients without treatment were selected and categorized into S+/C+group (n=143), S-/C+group (n=106) or S-/C- group (n=122). A series of serum samples were collected from 82 active TB patients who had undergone anti-TB chemotherapy for 0-6 months at one month interval. Humoral responses (IgG, IgM and IgA) were determined for the novel Mycobacterium tuberculosis polyprotein using indirect ELISA methods in all of serum samples. RESULTS: For S+/C+, S-/C+and S-/C- active tuberculosis patients before anti-TB chemotherapy, the sensitivities of tests based on IgG were 65.7%, 46.2% and 52.5% respectively; the sensitivities based on IgM were 21.7%, 24.5% and 18.9%; and the sensitivities based on IgA were 25.2%, 17.9% and 23.8%. By combination of three isotypes, for all active tuberculosis patients, the test sensitivity increased to 70.4% with the specificity being 91.5%. After anti-TB chemotherapy, there were no significant differences between groups with different courses of anti-TB chemotherapy. CONCLUSIONS: The novel Mycobacterium tuberculosis polyprotein 38 F-64 F represents potential antigen suitable for measuring IgG, IgM and IgA antibodies. However, the serodiagnostic test based on the 38 F-64 F polyprotein appears unsuitable for monitoring the efficacy of chemotherapy.

A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis.

BACKGROUND: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. METHODS: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. RESULTS: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. CONCLUSIONS: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.

Use of immuno-dominant epitope derived from genotype 4 as a diagnostic reagent for detecting the antibodies against Hepatitis E Virus.

BACKGROUND: Despite the genotype 4 has become the dominant cause of hepatitis E disease in China, none antigen derived from genotype 4 of hepatitis E virus (HEV) was used in current commercial anti-HEV immunoassay, and the serological reactivity of antigen derive from genotype 4 is not well-charactered. METHODS: We expressed and purified the 4 main immuno-dominant epitopes derived from genotype 1 and 4 including ORF2 (410-621aa) of genotype 4, ORF3 (47-114aa) of genotype 4, ORF2 (396-606aa) of genotype 1 and ORF3 (56-123aa) of genotype 4. RESULTS: The ORF2 of genotype 4 displayed good diagnostics performance according to ROC analysis using in-house panel, and the immunoassays based the ORF2 of genotype 4 was then developed to detect the anti-HEV IgG antibodies and evaluated further in 530 anti-HEV IgG positive specimens and 380 negative specimens. The sensitivity and the specificity is 98.1% (520/530) and 94.7% (360/380) for immunoassay based on ORF2 of genotype 4, 96.6% (512/530) and 92.6% (352/380) for commercial immunoassay based on genotype 1. It is noted that all of the positive samples will be detected by combing two assays together. The anti-HEV immunoassays based on genotype 4 are in accordance with Chinese anti-HEV national standard,and show an good agreement of 95.8% with commercial assay (kappa=0.913, P=0.014). CONCLUSIONS: The immunoassay based on ORF2G4 displays good performance, and combining assay based on genotype 1 together with genotype 4 will benefit the HEV diagnosis in large scale samples.

Hepatitis E virus ORF3 antigens derived from genotype 1 and 4 viruses are detected with varying efficiencies by an anti-HEV enzyme immunoassay.

The function of the hepatitis E virus (HEV) open reading frame 3 (ORF3) protein product remains unclear but it is able to induce a strong antibody response following HEV infection. Therefore, it has been used in some enzyme immunoassays (EIAs) for detecting anti-HEV antibody. In order to evaluate the difference in antigenicity of HEV ORF3 polypeptides derived from genotypes 1 and 4, two EIAs were developed, based on ORF3 polypeptides from genotypes 1 and 4 HEV. Serial weekly serum samples from two rhesus monkeys vaccinated with ORF3 antigens derived from the genotype 4 ORF3 protein and nine rhesus monkeys experimentally infected with genotypes 1 and 4 HEV were tested for anti-HEV using the assays. HEV ORF3 antigens derived from viruses of genotypes 1 and 4 showed different patterns of reactivity with sera obtained from monkeys immunized with ORF3 antigens or infected experimentally with HEV. The genotype 1 ORF3 polypeptide exhibited stronger reactivity with the sera from monkeys infected with genotype 1 than the genotype 4 ORF3 polypeptide. The genotype 4 ORF3 polypeptide demonstrated stronger reactivity with the sera from monkeys infected with genotype 4 than did the genotype 1 ORF3 polypeptide. The HEV ORF3 polypeptide contains genotype-specific antigens and the antigen-antibody reactions between the same genotypes were stronger than those between different genotypes.

[Pulmonary pathology in fatal human influenza A (H1N1) infection].

OBJECTIVE: To study the pulmonary pathology in patients died of fatal human influenza A(H1N1) infection. METHODS: Eight cases of fatal human influenza A (H1N1) infection, including 2 autopsy cases and 6 paramortem needle puncture biopsies, were enrolled into the study. Histologic examination, immunohistochemitry, flow cytometry and Western blotting were carried out. RESULTS: The major pathologic changes included necrotizing bronchiolitis with surrounding inflammation, diffuse alveolar damage and pulmonary hemorrhage. Influenza viral antigen expression was detected in the lung tissue by Western blotting. Immunohistochemical study demonstrated the presence of nuclear protein and hemagglutinin virus antigens in parts of trachea, bronchial epithelium and glands, alveolar epithelium, macrophages and endothelium. Flow cytometry showed that the apoptotic rate of type II pneumocytes (32.15%, 78.15%) was significantly higher than that of the controls (1.93%, 3.77%). CONCLUSION: Necrotizing bronchiolitis, diffuse alveolar damage and pulmonary hemorrhage followed by pulmonary fibrosis in late stage are the major pathologic changes in fatal human influenza A (H1N1) infection.

Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients.

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available. Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups. Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups. Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

An effective hydroxylation route for a highly sensitive glucose sensor using APTES/GOx functionalized AlGaN/GaN high electron mobility transistor.

A highly sensitive glucose sensor based on AlGaN/GaN high electron mobility transistor (HEMT) has been fabricated. The hydroxyl groups on the GaN surface were achieved by the decomposition of hydrogen peroxide solution (H2O2) under UV irradiation for the production of hydroxyl radicals. The self-assembled monolayers (SAMs) of 3-aminopropyltriethoxysilane (APTES) with terminal amino groups formed on the hydroxylation surface were used as substrates for glucose oxidase (GOx) immobilization. The chemical groups on the GaN surface after hydroxylation were confirmed by X-ray photoelectron spectroscopy. From the analysis of current signals, the biosensor constructed with APTES/GOx exhibited good current response to glucose over a linear range from 10 to 100 µM with a sensitivity of 3.15 × 104 µA mM-1 cm-2 and a detection limit of 10 nM. Meanwhile, the anticipated idea about the hydroxylation of GaN surface, can be an efficient approach for the design of AlGaN/GaN HEMT based biosensors in the future.

Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification.

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939-0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964-0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879-0.763) for PSA and 0.860 (95% CI 0.910-0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968-0.878) than PSA [AUC of 0.773 (95% CI 0.852-0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854-0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892-0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706-0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.

Identification and characterization of mammaglobin-A epitope in heterogenous breast cancers for enhancing tumor-targeting therapy.

Although targeted therapy has been extensively investigated for breast cancers, a molecular target with broad application is currently unavailable due to the high heterogeneity of these cancers. Mammaglobin-A (Mam-A), which is overexpressed in most breast carcinomas, has been proposed as a promising target. However, the lack of specific targeting moieties due to uncertain binding epitopes hampers further translational study. Here, seven potential epitopes of Mam-A were disclosed, and a unique epitope was then identified in most types of breast cancers, despite the genotypic heterogeneity. With phage display technology, the epitope was determined to be N-terminal amino acids 42-51 of Mam-A (N42-51). Then, the N42-51 epitope-specific monoclonal antibody, mAb785, was conjugated to poly lactic-co-glycolic acid (PLGA) nanoparticles loaded with therapeutic agents, thereby enhancing the drug uptake and therapeutic efficacy in different genotypes of breast cancers. The computer simulation of the N42-51 epitope and the mAb785 structures, as well as their interactions, further revealed the specific targeting mechanism of the mAb785-conjugated nanoparticles to breast cancers.

Varying abilities of recombinant polypeptides from different regions of hepatitis E virus ORF2 and ORF3 to detect anti-HEV immunoglobulin M.

Following infection with hepatitis E virus (HEV), anti-HEV immunoglobulin (Ig) M is thought to develop before anti-HEV IgG and to be a better marker for differentiating between the acute and convalescent phases of infection. In order to select polypeptides for improved detection of anti-HEV IgM, six and three overlapping polypeptides from open reading frames (ORFs) 2 and 3, respectively, of HEV genotypes 1 and 4 were expressed as fusion proteins in Escherichia coli. The reactivities of the polypeptides with anti-HEV IgM were evaluated using immunoblotting and enzyme immunoassays (EIAs). The data indicated that polypeptides from the N-terminus of ORF3 and middle region of ORF2 were weakly or not reactive with anti-HEV IgM, while those from the remaining regions of ORF2 and ORF3 contained reactive epitopes. Anti-HEV IgM against the N- or C-terminus of ORF2 appeared earlier and disappeared faster than that against polypeptides from the C-terminus of ORF3, based on serum samples from rhesus monkeys infected experimentally, and from patients infected naturally, with HEV. The N- and C-terminal polypeptides from ORF2 complemented one another in detecting anti-HEV IgM and EIA sensitivity was improved significantly with a combination of these polypeptides. The reactivities of ORF2 polypeptides from genotypes 1 and 4 were similar but that of ORF3 differed with sera from monkeys infected by the two genotypes. Thus, a combination of N- and C-terminal polypeptides of ORF2 from one genotype may be effective in EIAs to detect anti-HEV IgM.

Immunogenicity and efficacy of a bacterially expressed HEV ORF3 peptide, assessed by experimental infection of primates.

A 12.4-kDa peptide, corresponding to the entire ORF3 protein of hepatitis E virus (HEV), derived from human HEV genotype 4 and expressed in Escherichia coli as a fusion protein with a 17.5-kDa fragment of interleukin (IL)-1beta at the N-terminus, was recognized by HEV-reactive sera. Eight monkeys were immunized with the purified peptide, and seven were used as non-immunized controls. All 15 monkeys were challenged with HEV genotype 1 or 4. All control animals developed infection and hepatitis, and all but one vaccinated monkey became infected. Nevertheless, the vaccine was effective in reducing the virus titer and shortening the duration of viremia and fecal shedding. Furthermore, the vaccine provided some protection against hepatitis (1 of 2 monkeys in the two-dose regimen and 4 of 6 in the three-dose regimen did not develop severe hepatitis) compared to the controls. These results suggest that immunization with the bacterially expressed peptide may partially prevent experimental hepatitis, and even infection, in primates, following intravenous challenge with high doses of two HEV genotypes.

The adjuvant effect of C60(OH)22 nanoparticles promoting both humoral and cellular immune responses to HCV recombinant proteins.

Hepatitis c virus (HCV) infection is one of major causes for chronic liver diseases worldwide and could lead to death. Development of effective HCV vaccines is a powerful auxiliary method of existing treatments. Adjuvants are necessary for modern vaccines to promote immune responses. Among the various nanomaterials that have been developed, multihydroxylated fullerene (C60(OH)22) has been proved as an efficient adjuvant for human immunodeficiency virus DNA vaccine. Here, we utilized three types of HCV recombinant proteins as antigens to investigate the activity of C60(OH)22 as a protein vaccine adjuvant. The proteins were carried by C60(OH)22 in a way of surface adsorption and self-assemble encapsulation. C60(OH)22 at a relatively low dose was sufficient to promote both humoral and cellular immune responses to HCV protein antigens and reduce the usage of antigen. These results demonstrated the positive adjuvant properties of C60(OH)22 when applied to protein vaccines.

Enhancing performance of Ag-ZnO-Ag UV photodetector by piezo-phototronic effect.

In this work, an ultraviolet (UV) photodetector based on a ZnO nanowires (NWs) array with metal-semiconductor-metal Schottky junction structure was successfully fabricated on a flexible polyester fibre substrate by a low-temperature hydrothermal method. Subjected to a 0.2% tensile strain at -1 V, the I light and sensitivity of the as-prepared UV photodetector are lifted by 82% and 130%, respectively. Furthermore, the response speed and recovery speed are significantly raised under the same tensile strain. The working principle can be explained as that the Schottky barrier height (SBH) is effectively improved by the negative strain-induced polarization at the metal-ZnO interface which is favorable for the separation of photogenerated electron-hole pairs. This work not only provides a facile and promising means to optimize the performance of a ZnO based MSM photodetector by applying a tensile strain but also opens up the way for fabrication and integration of ZnO photodetectors on flexible polyester fiber substrates.