Methods: An observational study was conducted among 3935 patients presenting with acute upper respiratory illnesses in the ambulatory settings between 2012 and 2014.
Results: The VP4/VP2 gene was genotyped from all 976 RV-positive specimens, where the predominance of RV-A (49%) was observed, followed by RV-C (38%) and RV-B (13%). A significant regression in median nasopharyngeal viral load (VL) (P < .001) was observed, from 883 viral copies/µL at 1-2 days after symptom onset to 312 viral copies/µL at 3-4 days and 158 viral copies/µL at 5-7 days, before declining to 35 viral copies/µL at ≥8 days. In comparison with RV-A (median VL, 217 copies/µL) and RV-B (median VL, 275 copies/µL), RV-C-infected subjects produced higher VL (505 copies/µL; P < .001). Importantly, higher RV VL (median, 348 copies/µL) was associated with more severe respiratory symptoms (Total Symptom Severity Score ≥17, P = .017). A total of 83 phylogenetic-based transmission clusters were identified in the population. It was observed that the relative humidity was the strongest environmental predictor of RV seasonality in the tropical climate.
Conclusions: Our findings underline the role of VL in increasing disease severity attributed to RV-C infection, and unravel the factors that fuel the population transmission dynamics of RV.
METHODS: In this study, conducted in Malaysia, we evaluated the seven-gene biomarker panel validated in a North American population using blood samples collected from local patients. The panel employs quantitative RT-PCR (qRT-PCR) to analyze gene expression of the seven biomarkers (ANXA3, CLEC4D, TNFAIP6, LMNB1, PRRG4, VNN1 and IL2RB) that are differentially expressed in CRC patients as compared with controls. Blood samples from 210 patients (99 CRC and 111 controls) were collected, and total blood RNA was isolated and subjected to quantitative RT-PCR and data analysis.
RESULTS: The logistic regression analysis of seven-gene panel has an area under the curve (AUC) of 0.76 (95% confidence interval: 0.70 to 0.82), 77% specificity, 61% sensitivity and 70% accuracy, comparable to the data obtained from the North American investigation of the same biomarker panel.
CONCLUSIONS: Our results independently confirm the results of the study conducted in North America and demonstrate the ability of the seven biomarker panel to discriminate CRC from controls in blood samples drawn from a Malaysian population.
Methods: The OACs were expanded from passage 0 (P0) to P3, and cells in each passage were analyzed for gross morphology, growth rate, RNA expression and immunochemistry (IHC). The harvested OACs were assigned into two groups: low (1×10[7] cells/ml) and high (3×10[7] cells/ml) cell density. Three-dimensional (3D) constructs for each group were created using polymerised fibrin and cultured for 7, 14 and 21 days in vitro using chondrocyte growth medium. OAC constructs were analyzed with gross assessments and microscopic evaluation using standard histology, IHC and immunofluorescence staining, in addition to gene expression and biochemical analyses to evaluate tissue development.
Results: Constructs with a high seeding density of 3×10[7] cells/ml were associated with better quality cartilage-like tissue than those seeded with 1×10[7] cells/ml based on overall tissue formation, cell association and extracellular matrix distribution. The chondrogenic properties of the constructs were further confirmed by the expression of genes encoding aggrecan core protein and collagen type II.
Interpretation & conclusions: Our results confirmed that cell density was a significant factor affecting cell behaviour and aggregate production, and this was important for establishing good quality cartilage.
METHODOLOGY: We conducted a longitudinal observational study in gut microbiota profile in a group of paediatric patients diagnosed with ALL using 16 s ribosomal RNA sequencing and compared these patients' microbiota pattern with age and ethnicity-matched healthy children. Temporal changes of gut microbiota in these patients with ALL were also examined at different time-points in relation to chemotherapy.
RESULTS: Prior to commencement of chemotherapy, gut microbiota in children with ALL had larger inter-individual variability compared to healthy controls and was enriched with bacteria belonging to Bacteroidetes phylum and Bacteroides genus. The relative abundance of Bacteroides decreased upon commencement of chemotherapy. Restitution of gut microbiota composition to resemble that of healthy controls occurred after cessation of chemotherapy. However, the microbiota composition (beta diversity) remained distinctive and a few bacteria were different in abundance among the patients with ALL compared to controls despite completion of chemotherapy and presumed restoration of normal health.
CONCLUSION: Our findings in this pilot study is the first to suggest that gut microbiota profile in children with ALL remains marginally different from healthy controls even after cessation of chemotherapy. These persistent microbiota changes may have a role in the long-term wellbeing in childhood cancer survivors but the impact of these changes in subsequent health perturbations in these survivors remain unexplored.