37 research outputs found

    Enhancing productivity, soil health, and reducing global warming potential through diverse conservation agriculture cropping systems in India’s Western Indo-Gangetic Plains

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    Context The rice-wheat (RW) system, spanning 13.5 million hectares in South Asia, is crucial for food security and livelihoods. However, intensive conventional tillage-based practices have harmed soil and environmental health, decreased productivity trends and increased greenhouse gas emissions. Objective This study aims to develop resilient, climate-smart cropping systems within the RW system, focusing on soil and crop productivity, economic viability, and reduced greenhouse gas (GHG) emissions. Methods Over eight years, the study evaluated diverse parameters compared to farmer practices (FP) in seven scenarios (Sc), including one representing FP (Sc1) and six based on conservation agriculture (CA) principles. The study assessed system crop productivity, economic returns, soil quality (organic carbon; OC, nitrogen; N, phosphorus; P, potassium; K contents, bulk density; BD, soil aggregation, infiltration rates, microbial counts, and earthworm density), and GHG emissions. Results CA-based scenarios (Sc2 to Sc7) showed improved soil quality, lower bulk density, enhanced soil aggregation, and increased infiltration rates compared to Sc1. In the 0–15 cm layer, surface soil organic carbon (OC) and C stock were 63.7 % and 49.6 % higher, respectively, in CA-based scenarios. Additionally, available N, P and K contents in the surface layer increased by 10.2 %, 28.6 %, and 21.8 % under CA-based scenarios. Adoption of CA in intensified maize-based scenarios (Sc4 and Sc5) led to the increased system and economic yields, higher soil quality index (SQI), reduced GHG emissions and increased C stock compared to Sc1. Implications The study highlights that Conservation Agriculture (CA) practices and diversified crop rotations can address issues like falling crop productivity, reduced economic returns, soil degradation, and increasing environmental impacts in northwestern India's traditional rice-wheat system. However, widespread adoption requires government policies, including C credit payments and guaranteed markets with supportive pricing

    A two-stage association study identifies methyl-CpG-binding domain protein 2 gene polymorphisms as candidates for breast cancer susceptibility

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    Genome-wide association studies for breast cancer have identified over 40 single-nucleotide polymorphisms (SNPs), a subset of which remains statistically significant after genome-wide correction. Improved strategies for mining of genome-wide association data have been suggested to address heritable component of genetic risk in breast cancer. In this study, we attempted a two-stage association design using markers from a genome-wide study (stage 1, Affymetrix Human SNP 6.0 array, cases=302, controls=321). We restricted our analysis to DNA repair/modifications/metabolism pathway related gene polymorphisms for their obvious role in carcinogenesis in general and for their known protein–protein interactions vis-à-vis, potential epistatic effects. We selected 22 SNPs based on linkage disequilibrium patterns and high statistical significance. Genotyping assays in an independent replication study of 1178 cases and 1314 controls were attempted using Sequenom iPLEX Gold platform (stage 2). Six SNPs (rs8094493, rs4041245, rs7614, rs13250873, rs1556459 and rs2297381) showed consistent and statistically significant associations with breast cancer risk in both stages, with allelic odds ratios (and P-values) of 0.85 (0.0021), 0.86 (0.0026), 0.86 (0.0041), 1.17 (0.0043), 1.20 (0.0103) and 1.13 (0.0154), respectively, in combined analysis (N=3115). Of these, three polymorphisms were located in methyl-CpG-binding domain protein 2 gene regions and were in strong linkage disequilibrium. The remaining three SNPs were in proximity to RAD21 homolog (S. pombe), O-6-methylguanine-DNA methyltransferase and RNA polymerase II-associated protein 1. The identified markers may be relevant to breast cancer susceptibility in populations if these findings are confirmed in independent cohorts

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    Casemix, management, and mortality of patients receiving emergency neurosurgery for traumatic brain injury in the Global Neurotrauma Outcomes Study: a prospective observational cohort study

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    Assessing the performance of a demonstrative hydrogen fuel cell power train in the chassis of an internal combustion engine vehicle

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    Abstract In the present day in the global context, approximately 2 billion internal combustion engines (ICEs) are estimated to be in use. Nearly 7.3 billion metric tons of carbon dioxide (CO2) were released into the atmosphere as per the survey on the transportation sector in 2020, making up 41% of all emissions. To solve pollution challenges related to ICEs, recent advancements of alternatives to ICEs have pushed the globe to establish clean energy sources such as hydrogen fuel cells. The conversion of an ICE vehicle to a fuel cell vehicle is able to add further support to its development besides the 30% emission reduction since the old ICE vehicle would not be discarded. FCEVs are seen as a true replacement between BEVs and ICEs since more energy can be stored in less space as compared to BEVs. The objective of this paper is to analyse the energy consumption of a fuel cell-driven motor in the internal combustion engine vehicle chassis of Maruti 800, through mathematical modelling, then compare the specifications with that of an ICE-driven system. The analysis provides details on the optimization of drive system components to maximise the fuel cell energy consumption efficiency based on fuel cell power source requirements for a range of velocities and road gradients. The modifiable specifications of drive system components in the mathematical model ensure reproducibility for any drive cycles and system scenarios.</jats:p

    Germline Genetic and Treatment-Related Risk Factors for Diabetes Mellitus in Survivors of Childhood Cancer: A Report From the Childhood Cancer Survivor Study and St Jude Lifetime Cohorts

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    Purpose: To characterize germline genetic risk factors of diabetes mellitus among long-term survivors of childhood cancer. Methods: Adult survivors of childhood cancer from the Childhood Cancer Survivor Study (CCSS) Original Cohort (n = 5,083; 383 with diabetes) were used to conduct a discovery genome-wide association study. Replication was performed using the CCSS Expansion (n = 2,588; 40 with diabetes) and the St Jude Lifetime (SJLIFE; n = 3,351; 208 with diabetes) cohorts. Risk prediction models, stratified on exposure to abdominal radiation, were calculated using logistic regression including attained age, sex and body mass index, diagnosis, alkylating chemotherapy, age at cancer diagnosis, and a polygenic risk score (PRS) on the basis of 395 diabetes variants from the general population. Area under the receiver operating characteristic curve (AUC) was calculated for models on the basis of traditional risk factors, clinical risk factors, and PRS. Results: There was a genome-wide significant association of rs55849673-A with diabetes among survivors (odds ratio, 2.9; 95% CI, 2.0 to 4.2; P = 3.7 × 10-8), which is related to expression of ERCC6L2 in the Genotype-Tissue Expression project. The association of rs55849673-A was observed largely among survivors not exposed to abdominal radiation (odds ratio = 3.5, P = 1.1 × 10-7) and the frequency of rs55849673-A was consistently higher among diabetic survivors in the CCSS Expansion and SJLIFE cohorts. Risk prediction models including traditional diabetes risk factors, clinical risk factors and PRS had an optimism-corrected AUC of 0.801, with an AUC of 0.751 in survivors treated with abdominal radiation versus 0.813 in survivors who did not receive abdominal radiation. Conclusion: There is evidence for a novel locus of diabetes among survivors not exposed to abdominal radiation. Further refinement and validation of clinic-based risk prediction models for diabetes among long-term survivors of childhood cancer is warranted
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