Biology subjects

Khera, R.

Publications and source records attributed to Khera, R..

5 recordsLinked to original sources

bioRxiv2024

Fe starvation induces a second LHCI tetramer to photosystem I in green algae

Iron (Fe) availability limits photosynthesis at a global scale where Fe-rich photosystem (PS) I abundance is drastically reduced in Fe-poor environments. We used single-particle cryo-electron microscopy to reveal a unique Fe starvation-dependent arrangement of light-harvesting chlorophyll (LHC) proteins where Fe starvation-induced TIDI1 is found in an additional tetramer of LHC proteins associated with PSI in Dunaliella tertiolecta and Dunaliella salina. These cosmopolitan green algae are resilient to poor Fe nutrition. TIDI1 is a distinct LHC protein that co- occurs in diverse algae with flavodoxin (an Fe-independent replacement for the Fe-containing ferredoxin). The antenna expansion in eukaryotic algae we describe here is reminiscent of the iron-starvation induced (isiA-encoding) antenna ring in cyanobacteria, which typically co-occurs with isiB, encoding flavodoxin. Our work showcases the convergent strategies that evolved after the Great Oxidation Event to maintain PSI capacity.

plant biology↗

bioRxiv2021

Cryo-EM structures of pentameric autoinducer-2 exporter from E. coli reveal its transport mechanism

Bacteria utilize small extracellular molecules to communicate in order to collectively coordinate their behaviors in response to the population density. Autoinducer-2 (AI-2), a universal molecule for both intra- and inter-species communication, is involved in the regulation of biofilm formation, virulence, motility, chemotaxis and antibiotic resistance. While many studies have been devoted to understanding the biosynthesis and sensing of AI-2, very little information is available on its export. The protein TqsA from E. coli, which belongs to a large underexplored membrane transporter family, the AI-2 exporter superfamily, has been shown to export AI-2. Here, we report the cryogenic electron microscopic structures of two AI-2 exporters (TqsA and YdiK) from E. coli at 3.35 [A] and 2.80 [A] resolutions, respectively. Our structures suggest that the AI-2 exporter exists as a homo-pentameric complex. In silico molecular docking and native mass spectrometry experiments were employed to demonstrate the interaction between AI-2 and TqsA, and the results highlight the functional importance of two helical hairpins in substrate binding. We propose that each monomer works as an independent functional unit utilizing an elevator-type transport mechanism. This study emphasizes the structural distinctiveness of this family of pentameric transporters and provides fundamental insights for the ensuing studies.

biophysics↗

bioRxiv2019

Machine-learning to Improve Prediction of Mortality following Acute Myocardial Infarction: An Assessment in the NCDR-Chest Pain-Myocardial Infarction Registry

IntroductionAccurate prediction of risk of death following acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making. Contemporary machine-learning may improve risk-prediction by identifying complex relationships between predictors and outcomes. Methods and ResultsWe studied 993,905 patients in the American College of Cardiology Chest Pain-MI Registry hospitalized with AMI (mean age 64 {+/-} 13 years, 34% women) between January 2011 and December 2016. We developed and validated three machine learning models to predict in-hospital mortality and compared the performance characteristics with a logistic regression model. In an independent validation cohort, we compared logistic regression with lasso regularization (c-statistic, 0.891 [95% CI, 0.890-0.892]), gradient descent boosting (c-statistic, 0.902 [0.901-0.903]), and meta-classification that combined gradient descent boosting with a neural network (c-statistic, 0.904 [0.903-0.905]) with traditional logistic regression (c-statistic, 0.882 [0.881-0.883]). There were improvements in classification of individuals across the spectrum of patient risk with each of the three methods; the meta-classifier model - our best performing model - reclassified 20.9% of individuals deemed high-risk for mortality in logistic regression appropriately as low-to-moderate risk, and 8.2% of deemed low-risk to moderate-to-high risk based consistent with the actual event rates. ConclusionsMachine-learning methods improved the prediction of in-hospital mortality for AMI compared with logistic regression. Machine learning methods enhance the utility of risk models developed using traditional statistical approaches through additional exploration of the relationship between variables and outcomes.

bioinformatics↗

bioRxiv2018

National Population and Cost Implications of Treatment with Icosapentyl Ethyl in the United States: An Assessment Based on the REDUCE-IT trial

Icosapent ethyl, an omega-3-fatty acid, was associated with improved cardiovascular outcomes in individuals with elevated levels of serum triglycerides and at a high-risk of adverse cardiovascular events in the recently completed REDUCE-IT trial. We applied the eligibility criteria of the REDUCE-IT trial to a nationally representative sample of individuals in the United States captured in the National Health and Nutrition Examination Survey (NHANES) for a 6-year period (2009-2014) and estimated the number of individuals nationally that would be potentially eligible for treatment with icosapentyl ethyl. We found that nearly 3 million US adults would potentially be candidates for this therapy. Further, based on the list cost of the drug, if all eligible individuals are treated, the additional cost to the US healthcare system will be almost $9 billion a year.

epidemiology↗

bioRxiv2017

The Impact of 2017 ACC/AHA Guidelines on the Prevalence of Hypertension and Eligibility for Anti-Hypertensive Therapy in the United States and China

BACKGROUNDThe 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guideline recommendations for hypertension include major changes to the diagnosis of hypertension as well as suggested treatment targets for blood pressure management. To better guide future health policy interventions in the management of hypertension, we examined the effect of these guidelines on the prevalence as well as the eligibility for initiation and intensification of therapy in nationally-representative populations from the US and China.\n\nMETHODSIn the National Health and Nutrition Examination Survey (NHANES) for the most recent 2 cycles (2013-2014 and 2015-2016), and the China Health and Retirement Longitudinal Study (CHARLS) (2011-2012), we identified all adults 45 to 75 years of age who would have a diagnosis of hypertension, and would be candidates for initiation and intensification of anti-hypertensive therapy based on the 2017 ACC/AHA guidelines, compared with current guidelines.\n\nRESULTSThe adoption of the 2017 ACC/AHA guidelines for hypertension in the US would label 70.1 million individuals in the 45-75-year age group with hypertension, representing 63% of the population in this age-group. The adoption of these guidelines in China would lead to labeling of 267 million or 55% individuals in the same age-group with hypertension. This would represent a relative increase in the prevalence of hypertension by 26.8% in the US and 45.1% in China with the adoption of the new guidelines. Further, based on observed treatment patterns and current guidelines, 8.1 million Americans with hypertension are currently untreated. However, this number is expected to increase to 15.6 million after the implementation of the 2017 ACC/AHA guidelines. In China, based on current treatment patterns, 74.5 million patients with hypertension are untreated, and is estimated to increase to 129.8 million if the 2017 ACC/AHA guidelines are adopted by China. In addition, the new ACC/AHA guidelines will label 8.7 million adults in the US, and 51 million in China with hypertension who would not require treatment with an anti-hypertensive agent, compared with 1.5 million and 23.4 million in the current guidelines. Finally, even among those treated with anti-hypertensive therapy, the proportion of undertreated individuals, i.e. those above target blood pressures despite receiving anti-hypertensive therapy and candidates for intensification of therapy, is estimated to increase by 13.9 million (from 24.0% to 54.4% of the treated patients) in the US, and 30 million (41.4% to 76.2% of patients on treatment) in China, if the 2017 ACC/AHA treatment targets are adopted into clinical practice in the respective countries.\n\nConclusionsAdopting the new 2017 ACC/AHA hypertension guidelines would be associated with a substantial increase in the prevalence of hypertension in both US and China accompanied with a marked increase in the recommendation to initiate and intensify treatment in several million patients. There would be a 26.8% and 45.1% increase in those labeled with hypertension in the US and China, respectively. Further, 7.5 million and 55.3 million will be newly recommended for therapy, and 13.9 million and 30 million newly recommended for intensification of existing therapy in the US and China, respectively.

epidemiology↗