Rapidly rotating neutron stars with very strong surface magnetic fields are observed to emit pulsed emission in the whole range of electromagnetic spectrum from radio to high energy gamma-rays. These so called pulsars are known for their exceptional rotational stability. The radio emission from pulsars is generally believed to be powered by the rotational energy of neutron stars. More than 3000 pulsars have been currently known from radio observations, however, it is observed that a large population of pulsars is also bright in optical, X-rays and gamma-rays. The Fermi-LAT observations in the energy range above 100 MeV have discovered about 300 pulsars. However, origin of high energy non-thermal radiation from pulsars is not completely understood and remains an active area of research. In this contribution, we report a summary of observational features of the gamma-ray pulsars and perform pulsar population study to predict their detectability for the MACE gamma-ray telescope, which has just started its regular science operation at Hanle in India.

Background: Ceramides are a new kind of lipid biomarkers and have already been demonstrated to be valuable risk predictors in coronary patients. Patients with peripheral artery disease (PAD) are a population with worse prognosis and higher mortality risk compared to coronary artery disease (CAD) patients. However, the value of ceramides for risk prediction in PAD patients is still vague and has been addressed in the present study. Methods: This observational study included 379 PAD patients. The primary endpoint was all-cause mortality at 10 years of follow-up. A set of ceramides was measured by LC-MS/MS and combined according to the coronary event risk test (CERT) score which categorizes patients into one of four risk groups (low risk, moderate risk, high risk, very high risk). Results: Kaplan Meier survival curves revealed that the overall survival of patients has decreased with the increasing risk predicted by the four CERT categories, advancing from low risk to very high risk. Cox regression analysis demonstrated that every 1-step increase in category resulted in a 35% rise in overall mortality risk (HR=1.35 [1.16-1.58]). Multivariable adjustment, including amongst others age, T2DM, and statin treatment before baseline, did not abrogate this significant association (HR=1.22 [1.04-1.43]). Moreover, we found that the beneficial effect of statin is significantly stronger in patients with a higher risk according to CERT. Conclusion: We conclude that the ceramide-based risk score CERT is a strong predictor of the 10-year mortality risk in patients with PAD.

Ageing is the strongest known risk factor for many of the neurodegenerative diseases causing cognitive decline and dementia. Identification of cognitive impairment may be a prelude to appropriate treatment, hopefully disease-modifying. Use of cognitive screening instruments may be an equitable way to identify cognitive impairment. This study examined the use of two such instruments, Free-Cog and Mini-Addenbrooke’s Cognitive Examination (MACE), in patient cohorts referred to a dedicated cognitive disorders clinic based at a tertiary neurosciences centre. Results showed that: (1) specificity and positive predictive value increased with patient age for both tests with some loss of sensitivity and negative predictive value. (2) In the oldest age groups (≥75 and ≥70 years respectively) where specificity was at maximum, a positive test result (i.e. below the specified test cut-off) rules in the diagnosis of cognitive impairment. (3) Values of an “Efficiency Index” for each test indicated qualitatively a moderate change in the probability of correct diagnosis and quantitatively an approximately 15-25% increase in the probability of correct diagnosis. These findings show that both Free-Cog and MACE may be used with confidence for the identification of cognitive impairment and dementia in older patient cohorts. These findings may have implications for public health policies directed to case-finding in clinical practice as opposed to population-based screening.