Effect modification by sex of genetic associations of vitamin C related metabolites in the Canadian Longitudinal study on aging.

Introduction: Vitamin C is an essential nutrient. Sex differences in serum vitamin C concentrations have been observed but are not fully known. Investigation of levels of metabolites may help shed light on how dietary and other environmental exposures interact with molecular processes. O-methylascorbate and ascorbic acid 2-sulfate are two metabolites in the vitamin C metabolic pathway. Past research has found genetic factors that influence the levels of these two metabolites. Therefore, we investigated possible effect modification by sex of genetic variant-metabolite associations and characterized the biological function of these interactions. Methods: We included individuals of European descent from the Canadian Longitudinal Study on Aging with available genetic and metabolic data (n = 9004). We used linear mixed models to tests for genome-wide associations with O-methylascorbate and ascorbic acid 2-sulfate, with and without a sex interaction. We also investigated the biological function of the important genetic variant-sex interactions found for each metabolite. Results: Two genome-wide statistically significant (p value < 5 × 10-8) interaction effects and several suggestive (p value < 10-5) interaction effects were found. These suggestive interaction effects were mapped to several genes including HSD11B2, associated with sex hormones, and AGRP, associated with hunger drive. The genes mapped to O-methylascorbate were differently expressed in the testis tissues, and the genes mapped to ascorbic acid 2-sulfate were differently expressed in stomach tissues. Discussion: By understanding the genetic factors that impact metabolites associated with vitamin C, we can better understand its function in disease risk and the mechanisms behind sex differences in vitamin C concentrations.

Stronger EPR-steering criterion based on inferred Schrödinger-Robertson uncertainty relation.

Steering is one of the three in-equivalent forms of nonlocal correlations intermediate between Bell nonlocality and entanglement. Schrödinger-Robertson uncertainty relation (SRUR), has been widely used to detect entanglement and steering. However, the steering criterion in earlier works, based on SRUR, did not involve complete inferred-variance uncertainty relation. In this paper, by considering the local hidden state model and Reid's formalism, we derive a complete inferred-variance EPR-steering criterion based on SRUR in the bipartite scenario. Furthermore, we check the effectiveness of our steering criterion with discrete variable bipartite two-qubit and two-qutrit isotropic states.

Blood group phenotype frequencies in blood donors from a tertiary care hospital in north India

BACKGROUND: Knowledge about the frequency of red blood cell-antigen phenotypes in a population can be helpful in the creation of a donor data bank for the preparation of indigenous cell panels and for providing antigen-negative compatible blood to patients with multiple alloantibodies. METHODS: ABO and RhD blood grouping was performed on 9,280 continuous voluntary and replacement donors. For other rare blood groups, 508 ACD blood samples were obtained from the donors at the Blood Bank of the Department of Transfusion Medicine, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Blood group antigens were determined by tube method using anti-sera (Bio-Rad, USA), and the phenotype frequencies were expressed as percentages. RESULTS: Group B (37.39%) was the most common, followed by group O (31.85%). R1R1 and rr were the most common phenotypes amongst Rh positive and Rh negative groups, respectively. A rare phenotype R2Rz was found in one donor. For Kidd and Duffy blood group systems, Jk (a+b+) and Fy (a+b+) were the most common phenotypes (46.06% and 48.03%, respectively). The most common phenotypes for MNSs, Lu, and Kell blood groups were M+N+, S-s+, Lu (a-b+), and K-k+, respectively. A very rare case of Fy (a-b-) and Jk (a-b-) was found in a single donor. CONCLUSION: This study is the first small step to create a rare donor data bank and to prepare indigenous cell panels to provide compatible blood to all multi-transfused alloimmunized patients.

Blood group phenotype frequencies in blood donors from a tertiary care hospital in north India

BACKGROUND: Knowledge about the frequency of red blood cell-antigen phenotypes in a population can be helpful in the creation of a donor data bank for the preparation of indigenous cell panels and for providing antigen-negative compatible blood to patients with multiple alloantibodies. METHODS: ABO and RhD blood grouping was performed on 9,280 continuous voluntary and replacement donors. For other rare blood groups, 508 ACD blood samples were obtained from the donors at the Blood Bank of the Department of Transfusion Medicine, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Blood group antigens were determined by tube method using anti-sera (Bio-Rad, USA), and the phenotype frequencies were expressed as percentages. RESULTS: Group B (37.39%) was the most common, followed by group O (31.85%). R1R1 and rr were the most common phenotypes amongst Rh positive and Rh negative groups, respectively. A rare phenotype R2Rz was found in one donor. For Kidd and Duffy blood group systems, Jk (a+b+) and Fy (a+b+) were the most common phenotypes (46.06% and 48.03%, respectively). The most common phenotypes for MNSs, Lu, and Kell blood groups were M+N+, S-s+, Lu (a-b+), and K-k+, respectively. A very rare case of Fy (a-b-) and Jk (a-b-) was found in a single donor. CONCLUSION: This study is the first small step to create a rare donor data bank and to prepare indigenous cell panels to provide compatible blood to all multi-transfused alloimmunized patients.

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.