318 research outputs found
Structural and mechanistic basis of RNA processing by protein-only ribonuclease P enzymes
No full textRibonuclease P (RNase P) enzymes are responsible for the 5′ processing of tRNA precursors. In addition to the well-characterised ribozyme-based RNase P enzymes, an evolutionarily distinct group of protein-only RNase Ps exists. These proteinaceous RNase Ps (PRORPs) can be found in all three domains of life and can be divided into two structurally different types: eukaryotic and prokaryotic. Recent structural studies on members of both families reveal a surprising diversity of molecular architectures, but also highlight conceptual and mechanistic similarities. Here, we provide a comparison between the different types of PRORP enzymes and review how the combination of structural, biochemical, and biophysical studies has led to a molecular picture of protein-mediated tRNA processing
Mitochondrien: wie die Gene im Kraftwerk der Zelle aktiviert werden
No full textMitochondria contain an organellar genome that encodes for subunits of the respiratory chain. Its coordinated expression is essential for eukaryotic life and defects in this process lead to severe disease. How- ever, the molecular mechanisms underlying mitochondrial gene expression remain poorly understood. Recent structural and functional studies have provided the first mechanistic insights into mitochondrial gene expression and highlight the evolutionarily unique nature of this system
Precision Health and AI: improving health for everyone - Arjun Panesar (DDM Health)
No full textThis video is the twelfth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 14/09/2022.
Precision Health and AI: improving health for everyone - Arjun Panesar (DDM Health)
Bio: Arjun Panesar is the founder of DDM Health, providers of clinically-validated digital health solutions to over 1.8 million people. Benefiting from almost two decades of experience in big data, AI and AI ethics, Arjun leads the development of evidence-based digital innovations that harness the power of machine learning to provide precision medicine to patients, health services, and governments. Arjun’s work has received international recognition featuring in the Forbes, New Scientist, BBC and The Times. Arjun is a best-selling author on the topics of healthcare and AI, authoring two editions of Machine Learning and AI in Healthcare, and contributing to Handbook of Global Health, a major reference work. Arjun is an advisor to the Information School, University of Sheffield, Fellow to the NHS Innovation Accelerator, visiting lecturer at University of Warwick Medical School, and was recognised by Imperial College as an Alumni Leader for his contribution and impact to society.
Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/
This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1
YouTube Link: https://youtu.be/clPmdeLP5_
Structural basis of RNA processing by human mitochondrial RNase P
No full textHuman mitochondrial transcripts contain messenger and ribosomal RNAs flanked by transfer RNAs (tRNAs), which are excised by mitochondrial RNase (mtRNase) P and Z to liberate all RNA species. In contrast to nuclear or bacterial RNase P, mtRNase P is not a ribozyme but comprises three protein subunits that carry out RNA cleavage and methylation by unknown mechanisms. Here, we present the cryo-EM structure of human mtRNase P bound to precursor tRNA, which reveals a unique mechanism of substrate recognition and processing. Subunits TRMT10C and SDR5C1 form a subcomplex that binds conserved mitochondrial tRNA elements, including the anticodon loop, and positions the tRNA for methylation. The endonuclease PRORP is recruited and activated through interactions with its PPR and nuclease domains to ensure precise pre-tRNA cleavage. The structure provides the molecular basis for the first step of RNA processing in human mitochondria
Financial Management of Globalization of Developing Countries
No full texthuman development, economic growth, globalization, inequality, poverty
Molecular basis of human nuclear and mitochondrial tRNA 3′ processing
No full textAbstract Eukaryotic transfer RNA (tRNA) precursors undergo sequential processing steps to become mature tRNAs. In humans, ELAC2 carries out 3′ end processing of both nucleus-encoded (nu-tRNAs) and mitochondria-encoded (mt-tRNAs) tRNAs. ELAC2 is self-sufficient for processing of nu-tRNAs but requires TRMT10C and SDR5C1 to process most mt-tRNAs. Here we show that TRMT10C and SDR5C1 specifically facilitate processing of structurally degenerate mt-tRNAs lacking the canonical elbow. Structures of ELAC2 in complex with TRMT10C, SDR5C1 and two divergent mt-tRNA substrates reveal two distinct mechanisms of pre-tRNA recognition. While canonical nu-tRNAs and mt-tRNAs are recognized by direct ELAC2–RNA interactions, processing of noncanonical mt-tRNAs depends on protein–protein interactions between ELAC2 and TRMT10C. These results provide the molecular basis for tRNA 3′ processing in both the nucleus and the mitochondria and explain the organelle-specific requirement for additional factors. Moreover, they suggest that TRMT10C–SDR5C1 evolved as a mitochondrial tRNA maturation platform to compensate for the structural erosion of mt-tRNAs in bilaterian animals
Freedom of choice or force of circumstance? : Eastern European sex-workers in the Republic of Cyprus ; paper for the conference 'Alltag der Globalisierung. Perspektiven einer transnationalen Anthropologie', January 16-18, 2003, Institute of Cultural Anthropology and European Ethnology, Johann Wolfgang Goethe University, Frankfurt am Main
No full textThis paper focuses on Eastern European migrants who, since the beginning of the 1990s, are entering the Republic Cyprus as “artistes”. This is a visa permit status as well as an euphemism for short-term work permits in the local sex industry. In addition to exploring the migrational experiences of these women and their living and working conditions in the Republic of Cyprus, the paper reconstructs, empirically and analyt ically, the connection between immigration and the local sex industry. Here, several categories of social actors and institutions in Cyprus are actively involved. The rhetoric of government representatives, entrepreneurs and clients in the sex business on the one hand is contrasted with the discourse of local NGO representatives concerned with immigrants’ rights on the other hand. The paper comes to the conclusion that all of these discursive positions ultimately do not do justice to the complex process of decisionmaking that women undergo who migrate into the sex industry. Either, freedom of choice is emphasized – such as by entrepreneurs and the government – or the domination of women – as in the public statements of the NGO. In order to analyze the ambivalent tension between freedom of choice and submission to force by which the women’s decision is characterized, the author employs Michel Foucault’s concept of governmentality, which describes forms of political regulation that use the individual’s freedom of action as an instrument to exercise power
Fine-tuning generative models
No full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 73-76).Deep generative models have emerged as a powerful modeling paradigm for making sense of large amounts of unlabeled real-world data. In particular, the representations produced by these models have proven to be useful both in improving human understanding of the factors of variation in the original dataset and in downstream tasks such as classification. Most current algorithms, however, require training a bespoke model from scratch, which can be both expensive and time-consuming. Instead, we propose various methods of fine-tuning pre-trained generative models to achieve these goals, and evaluate these methods quantitatively on few-shot classification and interpretability tasks.by Arjun Khandelwal.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc
Improving parking garage efficiency using reservation optimization techniques
No full textParking in urban and suburban districts is becoming increasingly problematic due the information gap between the parking garages and the average commuter. This thesis describes and evaluates techniques that can be implemented by parking garages to augment parking garage efficiency. The issues studied in this thesis were i) Real-time tracking of car position ii) maximizing the number of reservations made for the parking garage by re-arrangement of existing reservations (Reservation Defragmentation) and iii) maximizing revenue for the parking garage through increased occupancy (Revenue Management). For the tracking problem, in order to be able to track the real-time position of the vehicle inside the parking garage, we have proposed two techniques. The first one involves a high accuracy algorithm that takes as input a higher number of sensor values (high accuracy) and the second one is a lower cost algorithm that takes as input fewer number of sensor values (low cost). We simulated various conditions of sensor failure rate and determined our metric to be number of tracked points as a percentage of the path to the destination. We determined limitations of these algorithms with respect to maximum speed of cars and inter-car distance. For the reservation defragmentation problem, we looked at increasing occupancy efficiency for i) Next day reservations and ii) Current day reservations. For this problem, we implemented three algorithms. For next day reservations, we established metrics to determine the efficiency of the algorithm including number of free parking spots created and reduction in lengths of free space in between the reservations. For current day reservations, our metric was the increase in maximum occupancy observed due to defragmentation. For increased revenue management, we suggested the application of two techniques: Booking limits and Overbooking. In booking limits, two-fare class of parking was suggested and the number of spots that need to be reserved for higher class (Capacity of garage - booking limit) was determined for probability distributions of customer arrival such as Poisson distribution. Since the practice of overbooking is done in order to compensate for the no-shows that occur despite reservations made, we have suggested an algorithm to determine the amount of overbooking based on a Gaussian distribution of customer ‘no-shows’. We obtained the following results for the algorithms implemented. In case of the tracking algorithm, as the sensor failure rate increased, the inaccuracy of the two proposed algorithms also increased. For 2% failure rate, we track 0.4% of the incoming cars inaccurately (given that a tracking is marked as correct if 75% or less of all sensors along the path of the car fail). In case of reservation defragmentation, we obtained best results for Recursive First-Fit algorithm. For next day reservation defragmentation, using a mean of 15% cancellation of reservations resulted in 14.6% decrease in occupied parking spots which can then lead to increased occupancy and 46.3% decrease in inter-reservation free space sizes for a 1000 arrival reservation system. The reservations were exponentially distributed with a mean of 20 reservations/hour. For current day reservations, we were able to increase maximum occupancy of the parking garage by 5.5% using Recursive First Fit algorithm. Among other conditions, we have evaluated Poisson arrival distribution with corporate arrival rate 100 cars/hour (Flintsch et al., 2006) [56] and corporate fare twice of leisure fare. For this condition, protection level (number of parking slots reserved for corporate class) is determined to be 20% of garage capacity. We also evaluated Binomial distribution with probability of incoming customer to be corporate customer as 0.5 and corporate fare twice of leisure fare. For this condition, protection level is determined to be 50% of garage capacity. We evaluated overbooking for several combinations of No-show rates, mean and standard deviation values and the highest amount of overbooking we obtained was 1.93 times maximum garage capacity and this implies that permitting this number of reservations for the parking garage would minimize the number of parking spots being under-utilized and increase the revenue of the parking garage operator due to effective use of parking spots. The algorithms have been simulated for different arrival distributions (for Revenue Management), different arrival rates (tracking) as well as variable durations of stay (reservation defragmentation). Besides the problems mentioned, there are certain other aspects, such as generalizing the tracking algorithms for parking garages of arbitrary layouts represents the work that needs to be done in the future.M.S.Includes bibliographical referencesby Arjun Ra
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