METHODS: Mice were intraperitoneally-infected with a mouse-adapted EV-A71 strain and treated with a dose of monoclonal antibody (MAb) daily for 3 days on day 1, 2 and 3 post-infection or for 3 days on 3, 4 and 5 post-infection. Treatment effectiveness was evaluated by signs of infection and survival rate. Histopathology and qPCR analyses were performed on mice sacrificed a day after completing treatment.
RESULTS: In mock-treated mice, CNS infection was established from day 3 post-infection. All mice treated before established CNS infection, survived and recovered completely without CNS infection. All mice treated after established CNS infection survived with mild paralysis, and viral load and antigens/RNA at day 6 post-infection were significantly reduced.
CONCLUSIONS: Passive immunization with our MAb could prevent CNS infection in mice if given early before the establishment of CNS infection. It could also ameliorate established CNS infection if optimal and repeated doses were given.
METHODS: This questionnaire development study involved four phases: (i) exploring and understanding the subject matter, (ii) questionnaire development, (iii) content validity testing, and lastly, (iv) field-testing of the questionnaire. For the field-testing phase, a cross-sectional self-administered survey of JoinCT was conducted among cancer patients with various socio-demographic backgrounds and medical conditions. Besides content validity, Cronbach's alpha was used to evaluate the internal consistency of domains, and confirmatory factor analysis was used to evaluate the model fit of the JoinCT framework.
RESULTS: A total of 389 respondents participated in the survey. Based on the results obtained from a field data collection phase, JoinCT consisted of four independent variables domains, namely "knowledge", "perception of benefits", "perception of risks", and "confidence". The only dependent variable was the willingness to participate in a clinical trial. The minimum Cronbach's alpha was 0.937, and the model fit for the overall framework of JoinCT is also excellent with Comparative Fit Index (> 0.90), root mean square error approximation (
METHODS: Patients with advanced solid cancers were randomized 1:1 to 3-weekly docetaxel 75 mg/m2, with or without sunitinib 12.5 mg daily for 7 days prior to docetaxel, stratified by primary tumour site. Primary endpoints were objective-response (ORR:CR + PR) and clinical-benefit rate (CBR:CR + PR + SD); secondary endpoints were toxicity and progression-free-survival (PFS).
RESULTS: We enrolled 68 patients from 2 study sites; 33 received docetaxel-sunitinib and 35 docetaxel alone, with 33 breast, 25 lung and 10 patients with other cancers. There was no difference in ORR (30.3% vs 28.6%, p = 0.432, odds-ratio [OR] 1.10, 95% CI 0.38-3.18); CBR was lower in the docetaxel-sunitinib arm (48.5% vs 71.4%, p = 0.027 OR 0.37, 95% CI 0.14-1.01). Median PFS was shorter in the docetaxel-sunitinib arm (2.9 vs 4.9 months, hazard-ratio [HR] 2.00, 95% CI 1.15-3.48, p = 0.014) overall, as well as in breast (4.2 vs 5.6 months, p = 0.048) and other cancers (2.0 vs 5.3 months, p = 0.009), but not in lung cancers (2.9 vs 4.1 months, p = 0.597). Median OS was similar in both arms overall (9.9 vs 10.5 months, HR 0.92, 95% CI 0.51-1.67, p = 0.789), and in the breast (18.9 vs 25.8 months, p = 0.354), lung (7.0 vs 6.7 months, p = 0.970) and other cancers (4.5 vs 8.8 months, p = 0.449) subgroups. Grade 3/4 haematological toxicities were lower with docetaxel-sunitinib (18.2% vs 34.3%, p = 0.132), attributed to greater discretionary use of prophylactic G-CSF (90.9% vs 63.0%, p = 0.024). Grade 3/4 non-haematological toxicities were similar (12.1% vs 14.3%, p = 0.792).
CONCLUSIONS: The addition of sunitinib to docetaxel was well-tolerated but did not improve outcomes. The possible negative impact in metastatic breast cancer patients is contrary to results of adding sunitinib to neoadjuvant AC. These negative results suggest that the intermittent administration of sunitinib in the current dose and schedule with docetaxel in advanced solid tumours, particularly breast cancers, is not beneficial.
TRIAL REGISTRATION: The study was registered ( NCT01803503 ) prospectively on clinicaltrials.gov on 4th March 2013.
RESULTS: All HPs of B. lehensis G1 were grouped according to their predicted functions based on the presence of functional domains in their sequences. From the metal-binding group of HPs of the cluster, an HP termed Bleg1_2507 was discovered to contain a thioredoxin (Trx) domain and highly-conserved metal-binding ligands represented by Cys69, Cys73 and His159, similar to all prokaryotic and eukaryotic Sco proteins. The built 3D structure of Bleg1_2507 showed that it shared the βαβαββ core structure of Trx-like proteins as well as three flanking β-sheets, a 310 -helix at the N-terminus and a hairpin structure unique to Sco proteins. Docking simulations provided an interesting view of Bleg1_2507 in association with its putative cytochrome c oxidase subunit II (COXII) redox partner, Bleg1_2337, where the latter can be seen to hold its partner in an embrace, facilitated by hydrophobic and ionic interactions between the proteins. Although Bleg1_2507 shares relatively low sequence identity (47%) to BsSco, interestingly, the predicted metal-binding residues of Bleg1_2507 i.e. Cys-69, Cys-73 and His-159 were located at flexible active loops similar to other Sco proteins across biological taxa. This highlights structural conservation of Sco despite their various functions in prokaryotes and eukaryotes.
CONCLUSIONS: We propose that HP Bleg1_2507 is a Sco protein which is able to interact with COXII, its redox partner and therefore, may possess metallochaperone and redox functions similar to other documented bacterial Sco proteins. It is hoped that this scientific effort will help to spur the search for other physiologically relevant proteins among the so-called "orphan" proteins of any given organism.
METHODS: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF.
RESULTS: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-β binding protein-4, and follistatin-related protein-3, as well.
CONCLUSIONS: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.