Towards an efficient computational mining approach to identify EST-SSR markers

Microsatellites are the markers of choice due to their high abundance reproducibility, degree of polymorphism and co-dominant nature. These are mainly used for studying the genetic variability in different species and Marker assisted selection. Expressed Sequence Tags (ESTs) serve as the main resource for Simple Sequence Repeats (SSRs). The computational approach for detecting SSRs and developing SSR markers from EST-SSRs is preferred over the conventional methods as it reduces time and cost to a great extent. The available EST sequence databases, various web interfaces and standalone tools provide the platform for an easy analysis of the EST sequences leading to the development of potential EST-SSR Markers. This paper is an overview of in silico approach to develop SSR Markers from the EST sequence using some of the most efficient tools that are available freely for academic purpose

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse

The clinical and economic assessment of the advanced breast biopsy instrument

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Dataset for: Metabolite assignment of Ultra-Filtered Synovial Fluid extracted from knee joints of Reactive Arthritis patients using High-Resolution NMR spectroscopy

Currently, there are no reliable clinical biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic profiling of synovial fluid (SF) –obtained from joints affected in ReA- holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of 1H and 13C resonances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal as well as on ultra-filtered (deproteinized) SF samples of eight ReA patients (n=8) using high resolution (800 MHz) 1H and 1H-13C NMR spectroscopy methods such as one-dimensional (1D) 1H CPMG and two-dimensional (2D) J-resolved1H NMR and homonuclear 1H-1H TOCSY and heteronuclear1H-13C HSQC correlation spectra. Compared to normal SF samples, several distinctive 1H NMR signals were identified and assigned to metabolites in the 1H NMR spectra of ultra-filtered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared to normal (un-filtered) SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites will serve to guide future metabolomics studies aiming to identify/evaluate the SF based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective

Evaluating LDL-C control in Indian acute coronary syndrome (ACS) patients- A retrospective real-world study LDL-C control in ACS

Background: Low-density lipoprotein-cholesterol (LDL-C) is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD) progression. Although lipid lowering therapies remain the cornerstone of secondary ACSVD prevention, there exists residual dyslipidemia. The current study aimed to evaluate the real-world experience related to the treatment patterns and LDL-C control in Indian Acute Coronary Syndrome (ACS) patients. Methods: This was a real-world, descriptive, retrospective, observational, and multicentric study conducted across India. The data was collected for 1 year following the ACS event. The change in the levels of LDL-C from the baseline to the follow-up visits and the control of LDL-C, the change in lipid profile, lipoprotein levels, treatment patterns for lipid-lowering, and tolerability of existing treatments were evaluated. Results: Overall, 575 patients were included from 11 centers across India. The mean age of the patients was 52.92 years, with male predominance (76.35%). Although there was a significant reduction in the mean levels of LDL-C from the baseline [(122.64 ± 42.01 mg/dl to 74.41 ± 26.45 mg/dl (p < 0.001)], it was observed that despite high-intensity statin therapy, only 20.87% patients managed to achieve target LDL-C of <55 mg/dL and 55.65% were unable to reach LDL-C levels of <70 mg/dl one year after the event. Six patients reported adverse events without treatment discontinuation. Conclusion: The majority of the patients received high-intensity statins and did not attain target LDL-C levels, suggesting LDL-C control after an ACS event requires management with novel therapies having better efficacy as recommended by international and national guidelines

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015–2020

Objectives We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India.Design A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data.Setting National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status.Participants Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district.Outcome measures We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015.Results The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra.Conclusion TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020