Efficacy and safety of sofosbuvir/velpatasvir in a real-world chronic hepatitis C genotype 3 cohort

BACKGROUND AND AIM

Real-world data on sofosbuvir/velpatasvir with and without ribavirin (SOF/VEL ± RBV), particularly among patients with genotype 3 (GT3) decompensated cirrhosis, prior treatment, coinfection, and hepatocellular carcinoma (HCC), are scarce. We aimed to assess the efficacy and safety of SOF/VEL ± RBV in a real-world setting that included both community and incarcerated GT3 hepatitis C virus (HCV) patients.

METHODS

We included all GT3 HCV patients treated with SOF/VEL ± RBV in our institution. The primary outcome measure was the overall sustained virological response 12 weeks after treatment (SVR12), reported in both intention-to-treat (ITT) and per-protocol analyses. The secondary outcome measures were SVR12 stratified by the presence of decompensated cirrhosis, prior treatment, HCC, and HIV/hepatitis C virus coinfection and the occurrence rate of serious adverse events requiring treatment cessation or hospitalization.

RESULTS

A total of 779 HCV patients were treated with 12 weeks of SOF/VEL ± RBV, of which 85% were treated during incarceration. Among the 530 GT3 HCV patients, 31% had liver cirrhosis, and 6% were treatment-experienced. The overall SVR12 for GT3 was 98.7% (95% confidence interval: 97.3%, 99.5%) and 99.2% (95% confidence interval: 98.1%, 99.8%) in ITT and per-protocol analyses, respectively. High SVR12 was also seen in ITT analysis among GT3 HCV patients with decompensated cirrhosis (88%), prior treatment (100%), HCC (100%), and HIV/hepatitis B virus coinfection (100%). Apart from one patient who developed myositis, no other serious adverse events were observed.

CONCLUSION

The SOF/VEL ± RBV is a safe and efficacious treatment option for GT3 HCV patients in a real-world setting. SOF/VEL with RBV may be considered for decompensated GT3 HCV patients.

A risk prediction score to identify patients at low risk for COVID-19 infection

Introduction:

Singapore’s enhanced surveillance programme for COVID-19 identifies and isolates hospitalised patients with acute respiratory symptoms to prevent nosocomial spread. We developed risk prediction models to identify patients with low risk for COVID-19 from this cohort of hospitalised patients with acute respiratory symptoms.

Methods:

This was a single-centre retrospective observational study. Patients admitted to our institution’s respiratory surveillance wards from 10 February to 30 April 2020 contributed data for analysis. Prediction models for COVID-19 were derived from a training cohort using variables based on demographics, clinical symptoms, exposure risks and blood investigations fitted into logistic regression models. The derived prediction models were subsequently validated on a test cohort.

Results:

Of the 1,228 patients analysed, 52 (4.2%) were diagnosed with COVID-19. Two prediction models were derived, the first based on age, presence of sore throat, dormitory residence, blood haemoglobin level (Hb), and total white blood cell counts (TW), and the second based on presence of headache, contact with infective patients, Hb and TW. Both models had good diagnostic performance with areas under the receiver operating characteristic curve of 0.934 and 0.866, respectively. Risk score cut-offs of 0.6 for Model 1 and 0.2 for Model 2 had 100% sensitivity, allowing identification of patients with low risk for COVID-19. Limiting COVID-19 screening to only elevated-risk patients reduced the number of isolation days for surveillance patients by up to 41.7% and COVID-19 swab testing by up to 41.0%.

Conclusion:

Prediction models derived from our study were able to identify patients at low risk for COVID-19 and rationalise resource utilisation.

DNA markers in plant improvement: an overview

The progress made in DNA marker technology has been tremendous and exciting. DNA markers have provided valuable tools in various analyses ranging from phylogenetic analysis to the positional cloning of genes. The development of high-density molecular maps which has been facilitated by PCR-based markers, have made the mapping and tagging of almost any trait possible. Marker-assisted selection has the potential to deploy favorable gene combinations for disease control. Comparative studies between incompatible species using these markers has resulted in synteny maps which are useful not only in predicting genome organization and evolution but also have practical application in plant breeding. DNA marker technology has found application in fingerprinting genotypes, in determining seed purity, in systematic sampling of germplasm, and in phylogenetic analysis. This review discusses the use of this technology for the genetic improvement of plants.

Comparative analysis of genetic diversity among Indian populations of Scirpophaga incertulas by ISSR-PCR and RAPD-PCR

Genetic variation between 28 Indian populations of the rice pest, Scirpophaga incertulas was evaluated using inter-simple sequence repeats (ISSR)-PCR assay. Nine SSR primers gave rise to 79 amplification products of which 67 were polymorphic. A dendrogram constructed from this data indicates that there is no geographical bias to the clustering and that gene flow between populations appears to be relatively unrestricted, substantiating our earlier conclusion based on the RAPD (random amplified polymorphic DNA) data. The dendrograms obtained using each of these marker systems were poorly correlated with each other as determined by Mantel's test for matrix correlation. Estimates of expected heterozygosity and marker index for each of these marker systems suggests that both these marker systems are equally efficient in determining polymorphisms. Matrix correlation analyses suggest that reliable estimates of genetic variation among the S. incertulas pest populations can be obtained by using RAPDs alone or in combination with ISSRs, but ISSRs alone cannot be used for this purpose.

Genetic variation in Indian populations of Scirpophaga incertulas as revealed by RAPD-PCR analysis

Scirpophaga incertulas, commonly referred to as yellow stem borer, is a predominant pest of rice causing serious losses in its yield. Genetic variation among populations of Scirpophaga incertulas collected from 28 hotspot locations in India was examined using the randomly amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR). In all, 32 primers were used and 354 amplification products were observed. No RAPD-PCR bands diagnostic to the pest population from any specific region were identified. Cluster analysis using UPGMA showed that, with the exception of the pest population from Pattambi, all the populations cluster as one group with GD values in the range of 6-22%, suggesting that gene flow between populations is independent of geographic distance and appears to be unrestricted. The relatively high GD value of 48% exhibited by the pest population from Pattambi was the only exception.

Use of high resolution thermal denaturation approach in preliminary identification of plant DNAs

High resolution thermal denaturation (HRTD) profiles of the DNAs of six related millets, oat and rice showed several maxima and shoulders skewed towards the GC-rich side. Linear regression and correlation analyses exhibited no correlation between the repetitive DNA content/nuclear DNA content and the number of peaks, while there existed a very good correlation between delta T and repetitive DNA content/nuclear DNA content indicating that increase in repetitive DNA content has resulted in a greater sequence heterogeneity in these DNAs. In addition, specific melting characteristics of each of the eight plant DNAs were identified, which showed species specificity.