We present a generative long short-term memory (LSTM) recurrent neural network (RNN) for combinatorial de novo peptide design. RNN models capture patterns in sequential data and generate new data ...instances from the learned context. Amino acid sequences represent a suitable input for these machine-learning models. Generative models trained on peptide sequences could therefore facilitate the design of bespoke peptide libraries. We trained RNNs with LSTM units on pattern recognition of helical antimicrobial peptides and used the resulting model for de novo sequence generation. Of these sequences, 82% were predicted to be active antimicrobial peptides compared to 65% of randomly sampled sequences with the same amino acid distribution as the training set. The generated sequences also lie closer to the training data than manually designed amphipathic helices. The results of this study showcase the ability of LSTM RNNs to construct new amino acid sequences within the applicability domain of the model and motivate their prospective application to peptide and protein design without the need for the exhaustive enumeration of sequence libraries.
Aerosol black carbon is a unique primary tracer for combustion emissions. It affects the optical properties of the atmosphere and is recognized as the second most important anthropogenic forcing ...agent for climate change. It is the primary tracer for adverse health effects caused by air pollution. For the accurate determination of mass equivalent black carbon concentrations in the air and for source apportionment of the concentrations, optical measurements by filter-based absorption photometers must take into account the "filter loading effect". We present a new real-time loading effect compensation algorithm based on a two parallel spot measurement of optical absorption. This algorithm has been incorporated into the new Aethalometer model AE33. Intercomparison studies show excellent reproducibility of the AE33 measurements and very good agreement with post-processed data obtained using earlier Aethalometer models and other filter-based absorption photometers. The real-time loading effect compensation algorithm provides the high-quality data necessary for real-time source apportionment and for determination of the temporal variation of the compensation parameter k.
Generative artificial intelligence models present a fresh approach to chemogenomics and de novo drug design, as they provide researchers with the ability to narrow down their search of the chemical ...space and focus on regions of interest. We present a method for molecular de novo design that utilizes generative recurrent neural networks (RNN) containing long short‐term memory (LSTM) cells. This computational model captured the syntax of molecular representation in terms of SMILES strings with close to perfect accuracy. The learned pattern probabilities can be used for de novo SMILES generation. This molecular design concept eliminates the need for virtual compound library enumeration. By employing transfer learning, we fine‐tuned the RNN′s predictions for specific molecular targets. This approach enables virtual compound design without requiring secondary or external activity prediction, which could introduce error or unwanted bias. The results obtained advocate this generative RNN‐LSTM system for high‐impact use cases, such as low‐data drug discovery, fragment based molecular design, and hit‐to‐lead optimization for diverse drug targets.
•Aujeszky’s disease (AD) vaccination has pioneered novel strategies in animal disease control by the first use of marker vaccines.•AD was the first animal disease where the concept of DIVA ...(differentiating vaccinated from infected animals) was used.•Pseudorabies virus has been developed into a powerful vector system for integration and expression of foreign proteins.•Modern PrV vector vaccines offer novel perspectives for advancing preventive medicine through vaccination against several animal diseases.
Aujeszkýs disease (AD, pseudorabies) is a notifiable herpesvirus infection of pigs causing substantial economic losses to swine producers. AD in pigs is controlled by the use of vaccination with inactivated and attenuated live vaccines. Starting with classically attenuated live vaccines derived from low virulent field isolates, AD vaccination has pioneered novel strategies in animal disease control by the first use of genetically engineered live virus vaccines lacking virulence-determining genes, and the concept of DIVA, i.e. the serological differentiation of vaccinated from field-virus infected animals by the use of marker vaccines and respective companion diagnostic tests. The basis for this concept has been the molecular characterization of PrV and the identification of so-called nonessential envelope glycoproteins, e.g. glycoprotein E, which could be eliminated from the virus without harming viral replication or immunogenicity. Eradication of AD using the strategy of vaccination-DIVA testing has successfully been performed in several countries including Germany and the United States. Furthermore, by targeted genetic modification PrV has been developed into a powerful vector system for expression of foreign genes to vaccinate against several infectious diseases of swine, while heterologous vector systems have been used for expression of major immunogens of PrV. This small concise review summarizes the state-of-the-art information on PrV vaccines and provides an outlook for the future.
In the last two decades we have witnessed sizable progress in defining the role of gastrointestinal signals in the control of glucose and energy homeostasis. Specifically, the molecular basis of the ...huge metabolic benefits in bariatric surgery is emerging while novel incretin-based medicines based on endogenous hormones such as glucagon-like peptide 1 and pancreas-derived amylin are improving diabetes management. These and related developments have fostered the discovery of novel insights into endocrine control of systemic metabolism, and in particular a deeper understanding of the importance of communication across vital organs, and specifically the gut-brain-pancreas-liver network. Paradoxically, the pancreatic peptide glucagon has reemerged in this period among a plethora of newly identified metabolic macromolecules, and new data complement and challenge its historical position as a gut hormone involved in metabolic control. The synthesis of glucagon analogs that are biophysically stable and soluble in aqueous solutions has promoted biological study that has enriched our understanding of glucagon biology and ironically recruited glucagon agonism as a central element to lower body weight in the treatment of metabolic disease. This review summarizes the extensive historical record and the more recent provocative direction that integrates the prominent role of glucagon in glucose elevation with its under-acknowledged effects on lipids, body weight, and vascular health that have implications for the pathophysiology of metabolic diseases, and the emergence of precision medicines to treat metabolic diseases.
Single photons and entangled photon pairs are a key resource of many quantum secure communication and quantum computation protocols, and non-Poissonian sources emitting in the low-loss wavelength ...region around 1,550 nm are essential for the development of fibre-based quantum network infrastructure. However, reaching this wavelength window has been challenging for semiconductor-based quantum light sources. Here we show that quantum dot devices based on indium phosphide are capable of electrically injected single photon emission in this wavelength region. Using the biexciton cascade mechanism, they also produce entangled photons with a fidelity of 87 ± 4%, sufficient for the application of one-way error correction protocols. The material system further allows for entangled photon generation up to an operating temperature of 93 K. Our quantum photon source can be directly integrated with existing long distance quantum communication and cryptography systems, and provides a promising material platform for developing future quantum network hardware.
The response of Arabidopsis thaliana to low-oxygen stress (hypoxia), such as during shoot submergence or root waterlogging, includes increasing the levels of ~50 hypoxia-responsive gene transcripts, ...many of which encode enzymes associated with anaerobic metabolism. Upregulation of over half of these mRNAs involves stabilization of five group VII ethylene response factor (ERF-VII) transcription factors, which are routinely degraded via the N-end rule pathway of proteolysis in an oxygen- and nitric oxide-dependent manner. Despite their importance, neither the quantitative contribution of individual ERF-VIIs nor the cis-regulatory elements they govern are well understood. Here, using single- and double-null mutants, the constitutively synthesized ERF-VIIs RELATED TO APETALA2.2 (RAP2.2) and RAP2.12 are shown to act redundantly as principle activators of hypoxia-responsive genes; constitutively expressed RAP2.3 contributes to this redundancy, whereas the hypoxia-induced HYPOXIA RESPONSIVE ERF1 (HRE1) and HRE2 play minor roles. An evolutionarily conserved 12-bp cis-regulatory motif that binds to and is sufficient for activation by RAP2.2 and RAP2.12 is identified through a comparative phylogenetic motif search, promoter dissection, yeast one-hybrid assays, and chromatin immunopurification. This motif, designated the hypoxia-responsive promoter element, is enriched in promoters of hypoxia-responsive genes in multiple species.
PDF
