1,712 research outputs found
SILVR: Guided Diffusion for Molecule Generation
Computationally generating novel synthetically accessible compounds with high
affinity and low toxicity is a great challenge in drug design. Machine-learning
models beyond conventional pharmacophoric methods have shown promise in
generating novel small molecule compounds, but require significant tuning for a
specific protein target. Here, we introduce a method called selective iterative
latent variable refinement (SILVR) for conditioning an existing diffusion-based
equivariant generative model without retraining. The model allows the
generation of new molecules that fit into a binding site of a protein based on
fragment hits. We use the SARS-CoV-2 Main protease fragments from Diamond
X-Chem that form part of the COVID Moonshot project as a reference dataset for
conditioning the molecule generation. The SILVR rate controls the extent of
conditioning and we show that moderate SILVR rates make it possible to generate
new molecules of similar shape to the original fragments, meaning that the new
molecules fit the binding site without knowledge of the protein. We can also
merge up to 3 fragments into a new molecule without affecting the quality of
molecules generated by the underlying generative model. Our method is
generalizable to any protein target with known fragments and any
diffusion-based model for molecule generation.Comment: paper, 20 paper, 11 figure
Pengaruh Pemberian Pgpr (Plant Growth Promoting Rhizobacteria) Pada Pertumbuhan Bud Chip Tebu (Saccharum Officinarum L.)
Produksi tebu nasional yang rendah dapat ditingkatkan dengan menggunakan teknik bud chip untuk mendapatkan bibit yang berkualitas. Teknik bud chip tebu mempunyai kendala pada daya perkecambahan yang rendah. Upaya untuk mengatasi rendahnya daya kecambah ialah melalui pemberian PGPR (Plant Growth Promoting Rhizobacteria) sebagai pemacu pertumbuhan. Penelitian ini bertujuan untuk mendapatkan komposisi terbaik dari bakteri Pseudomonas fluorescens dan Bacillus subtilis pada PGPR yang dapat meningkatkan pertumbuhan bud chip tebu. Penelitian dilakukan pada bulan Januari hingga Mei 2015 di CV. Joyo Rosan, Gurah Kediri, Jawa Timur. Metode yang digunakan adalah Rancangan Acak Kelompok dengan komposisi bakteri Pseudomonas fluorescens dan Bacillus subtilis yang berbeda sebagai faktor yang ingin diketahui pengaruhnya. Hasil penelitian menunjukkan bahwa penggunaan PGPR sebagai zat pemacu tumbuh pada bud chip varietas PS 882 mampu mempercepat pertumbuhan tanaman
Toroidal grating astigmatism of high-harmonics characterized by EUV Hartmann sensor
The beam transport of single high-order harmonics in a monochromator arrangement is studied. A toroidal grating combines spectral filtering and focusing in order to produce a small individual spot for each harmonic. Here, the effect of small deviations from perfect alignment is investigated. Experimentally, a Hartmann sensor monitors the EUV wavefront while the grating is subjected to an online alignment procedure. The obtained results are confirmed by a simple theoretical description employing optical matrix methods
Advances in cardiovascular research. 15th Annual Meeting of the European Council for Cardiovascular Research (ECCR). La Colle sur Loup, France, 8-10 October 2010
The 15th Annual Meeting of the European Council of Cardiovascular Research brought together basic and clinical scientists working in the cardiovascular field in La Colle sur Loup, France. Upfront basic and clinical research addressing the mechanisms of disease, identification of biomarkers or development of new treatments was communicated in 101 presentations, 35 of them as a part of five on-topic oral sessions and three workshops. Three keynote lectures reviewed current knowledge and the latest data about mechanosensitive channels in pressure regulation, cell therapy in cardiovascular disease and mechanisms of cardiovascular risk associated with diabetic nephropathy. This article summarizes highlights of the oral sessions, workshops and keynote lectures
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Adaption of the MODIS aerosol retrieval algorithm using airborne spectral surface reflectance measurements over urban areas: A case study
MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It was shown that the operational MODIS AOD retrieval over land reproduces the AOD reference input of 0.85 for dark surface types (retrieved AOD = 0.87 (C5)). An overestimation of AOD = 0.99 is found for urban surfaces, whereas the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86
Factors Influencing Nutritional Intake and Interests in Educational Content of Athletes and Sport Professionals Toward the Development of a Clinician-Supported Mobile App to Combat Relative Energy Deficiency in Sport: Formative Research and a Description of App Functions
Background: Relative energy deficiency in sport (RED-S) as a consequence of athlete malnutrition remains a prominent issue. However, it remains underrecognized, in part due to the perceived outward health of athletes. The Eat2Win app was designed to combat RED-S and athlete malnutrition by providing education, behavior modification, and direct communication with expert sports dietitians to athletes and sport professionals (professionals who work with athletes, eg, sport coaches and athletic trainers). Objective: The purpose of this formative research was to gain critical insight on motivators and barriers to optimal nutritional intake from both the athletesâ and sport professionalsâ perspectives. Additionally, since these 2 groups represent the primary end users of an app aimed at improving athlete nutrition and reducing the risk of RED-S, a secondary objective was to gain insight on the preferences and perceptions of app-based educational content and functionality. Methods: An electronic survey was developed by an interdisciplinary team of experts. Survey questions were established based upon prevailing literature, professional dietetic field experience, and app design considerations to obtain respondent knowledge on key sports nutrition topics along with motivations and barriers to meal choices. Additionally, the survey included questions about the development of an integrative, clinician-support app aimed at addressing RED-S. These questions included preferences for educational content, modes of in-app information, and communication delivery for the target population (app end users: athletes and sport professionals). The survey was distributed through Research Electronic Data Capture (REDCap) to athletes and sport professionals using targeted email, social media, and community engagement campaigns. The electronic survey was available from May 4 to August 2, 2022. Results: Survey respondents (n=1352) included athletes and professionals who work with athletes from a variety of settings, like high school, collegiate, professional, and club sports. Respondents reported high interest in 8 core sports nutrition topics. The preferred modes of information and communication delivery were visual formats (eg, videos and infographics) and in-app alerts (eg, direct messaging and meal reminders). Only athlete respondents were asked about motivators and barriers that influence meal choices. âHealthâ and âsports performanceâ were the highest scoring motivators, while the highest scoring barriers were âcost of food,â âeasy access to unhealthy food,â and âtime to cook or prepare food.â Notably, survey respondents provided positive feedback and interest using a novel function of the app: real-time meal feedback through food photography. Conclusions: The Eat2Win app is designed to combat RED-S and athlete malnutrition. Results from this study provide critical information on end-user opinions and preferences and will be used to further develop the Eat2Win app. Future research will aim to determine whether the Eat2Win app can prevent RED-S and the risk of athlete malnutrition to improve both health and performance
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