Personalizing the treatment of Parkinson’s disease using a multi-sensor integrated midbrain organoid-on-a-chip platform

Please click Download on the upper right corner to see the full descriptio

QSAR Analysis through the World-Wide Web

A WWW-based system for structure-activity analysis developed and used in Novartis Crop Protection in Basel is presented. The system enables easy calculation of important hydrophobic, electronic, and steric molecular properties, as well as interactive QSAR analysis. Based on generated models, predictions can be made with regard to the biological activities and environmental characteristics of new, as yet unsynthesized molecules. By bringing sophisticated and easy-to-use tools enabling analysis of structure-activity relationships directly to the desk of synthetic organic chemists, the system supports the efficient design of new, active, and environmentally acceptable agrochemicals

In silico generation of novel, drug-like chemical matter using the LSTM neural network

The exploration of novel chemical spaces is one of the most important tasks of cheminformatics when supporting the drug discovery process. Properly designed and trained deep neural networks can provide a viable alternative to brute-force de novo approaches or various other machine-learning techniques for generating novel drug-like molecules. In this article we present a method to generate molecules using a long short-term memory (LSTM) neural network and provide an analysis of the results, including a virtual screening test. Using the network one million drug-like molecules were generated in 2 hours. The molecules are novel, diverse (contain numerous novel chemotypes), have good physicochemical properties and have good synthetic accessibility, even though these qualities were not specific constraints. Although novel, their structural features and functional groups remain closely within the drug-like space defined by the bioactive molecules from ChEMBL. Virtual screening using the profile QSAR approach confirms that the potential of these novel molecules to show bioactivity is comparable to the ChEMBL set from which they were derived. The molecule generator written in Python used in this study is available on request.Comment: in this version fixed some reference number

Molecular structure input on the web

A molecule editor, that is program for input and editing of molecules, is an indispensable part of every cheminformatics or molecular processing system. This review focuses on a special type of molecule editors, namely those that are used for molecule structure input on the web. Scientific computing is now moving more and more in the direction of web services and cloud computing, with servers scattered all around the Internet. Thus a web browser has become the universal scientific user interface, and a tool to edit molecules directly within the web browser is essential

Evaluating the impact of perfusion on nanomaterial uptake rates and cytotoxicity using microfluidic in vitro & in silico cell cultures systems

In the last decade, the application of nanomaterials (NMs) in technical products and biomedicine has become a rapidly increasing market trend. As the safety and efficacy of NMs are of utmost importance, new methods are needed to study the dynamic interactions of NMs at the nano-biointerface. However, evaluation of NMs based on standard and static cell culture end-point detection methods does not provide information on the dynamics of living biological systems, which is crucial for the understanding of physiological responses. To gain a deeper understanding of nanomaterial – cell interactions under perfused conditions, we here present a combinatorial in vitro & in silico approach to describe shear-force dependent uptake of nanoparticles on vascular endothelial cells. Additionally, we present a microsensor-integrated microfluidic system capable of monitoring the enhanced cytotoxic effects of nanodrugs on lung cells following chronic and acute exposure scenarios. Result of our study demonstrate that both active uptake rates and cytotoxicity of nanomaterials are strongly modulated by flow velocity and local shear-force conditions. Please click Additional Files below to see the full abstract

Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

<p>Abstract</p> <p>Background</p> <p>A method to estimate ease of synthesis (synthetic accessibility) of drug-like molecules is needed in many areas of the drug discovery process. The development and validation of such a method that is able to characterize molecule synthetic accessibility as a score between 1 (easy to make) and 10 (very difficult to make) is described in this article.</p> <p>Results</p> <p>The method for estimation of the synthetic accessibility score (SAscore) described here is based on a combination of fragment contributions and a complexity penalty. Fragment contributions have been calculated based on the analysis of one million representative molecules from PubChem and therefore one can say that they capture historical synthetic knowledge stored in this database. The molecular complexity score takes into account the presence of non-standard structural features, such as large rings, non-standard ring fusions, stereocomplexity and molecule size. The method has been validated by comparing calculated SAscores with ease of synthesis as estimated by experienced medicinal chemists for a set of 40 molecules. The agreement between calculated and manually estimated synthetic accessibility is very good with <it>r</it>²= 0.89.</p> <p>Conclusion</p> <p>A novel method to estimate synthetic accessibility of molecules has been developed. This method uses historical synthetic knowledge obtained by analyzing information from millions of already synthesized chemicals and considers also molecule complexity. The method is sufficiently fast and provides results consistent with estimation of ease of synthesis by experienced medicinal chemists. The calculated SAscore may be used to support various drug discovery processes where a large number of molecules needs to be ranked based on their synthetic accessibility, for example when purchasing samples for screening, selecting hits from high-throughput screening for follow-up, or ranking molecules generated by various <it>de novo </it>design approaches.</p

Prediction contribution of the cranial collateral circulation to the clinical and radiological outcome of ischemic stroke

Background and Aim: The extent of penumbra tissue and outcome in stroke patients depend on the collateral cranial vasculature. To provide optimal individualized care for stroke patients in the emergency room setting we investigated the predictive capability of a stringent evaluation of the collateral vessels in ischemic stroke on clinical outcome and infarct size. Methods: We retrospectively studied uniform clinical and radiological data of 686 consecutive patients admitted to the emergency department with suspected acute ischemic stroke. Cranial collateral vasculature status was graded using the initial CT-angiography. Outcome was measured by mRS, NIHSS and final infarct size at hospital discharge. All data were used to build a linear regression model to predict the patients´ outcome. Results: Univariate and multivariate analyses showed significant effects of the whole brain collateral vessel score on all outcome variables. Atherosclerosis and piale collateral status were associated with the final infarct volume (FIV). Atherosclerosis and age were associated with the NIHSS at discharge. The presence of atherosclerosis, glucose level on admission and age were associated with the mRS at discharge. The multivariate models were able to predict 29% of the variance of the mRS at discharge, 24% of the variance in FIV and 17% of the variance of the NIHSS at discharge. The whole brain collateral status and the presence of atherosclerosis were the most relevant predictors for the clinical and radiological outcome. Conclusion: The whole brain collateral vasculature status is clearly associated with clinical and radiological outcome but in a multivariate model seems not sufficiently predictive for FIV, mRS and NIHSS outcome at discharge in non-preselected patients admitted to the emergency department with ischemic stroke

In Vivo Localization of the Human Velocity Storage Mechanism and Its Core Cerebellar Networks by Means of Galvanic-Vestibular Afternystagmus and fMRI.

Humans are able to estimate head movements accurately despite the short half-life of information coming from our inner ear motion sensors. The observation that the central angular velocity estimate outlives the decaying signal of the semicircular canal afferents led to the concept of a velocity storage mechanism (VSM). The VSM can be activated via visual and vestibular modalities and becomes manifest in ocular motor responses after sustained stimulation like whole-body rotations, optokinetic or galvanic vestibular stimulation (GVS). The VSM has been the focus of many computational modelling approaches; little attention though has been paid to discover its actual structural correlates. Animal studies localized the VSM in the medial and superior vestibular nuclei. A significant modulation by cerebellar circuitries including the uvula and nodulus has been proposed. Nevertheless, the corresponding neuroanatomical structures in humans have not been identified so far. The aim of the present study was to delineate the neural substrates of the VSM using high-resolution infratentorial fMRI with a fast T2* sequence optimized for infratentorial neuroimaging and via video-oculography (VOG). The neuroimaging experiment (n=20) gave first in vivo evidence for an involvement of the vestibular nuclei in the VSM and substantiate a crucial role for cerebellar circuitries. Our results emphasize the importance of cerebellar feedback loops in VSM most likely represented by signal increases in vestibulo-cerebellar hubs like the uvula and nodulus and lobule VIIIA. The delineated activation maps give new insights regarding the function and embedment of Crus I, Crus II, and lobule VII and VIII in the human vestibular system

Monitoring of metabolic parameters of mammal cells cultures in microfluidic devices using integrated optical chemical sensors

Optical chemical sensors are well established in the chemical industry, life science, biotechnology and research laboratories. They are operate non-invasive, do not need any reference elements and can be read-out via contactless measurement. Moreover, it is possible to miniaturize and integrate them into microfluidic systems. Due to their simple composition, optical sensors can be produced at low price and therefore represent a good alternative compared to electrochemical sensors for their application in disposable microfluidics. The various possibilities of integrated optical oxygen sensors have already shown their potential in different microfluidic applications [1]. However, monitoring of further metabolic parameters is important for a better understanding of biological processes. Therefore, our group develops, next to oxygen sensors, also optical sensors for monitoring pH, glucose, CO2, ammonia and various ions. Still, integration in a Lab-on-a-chip format is a challenging task due to the state-of-the-art performances in terms of signal brightness, response times, optoelectronic read-out systems, fabrication and integration. Please click Additional Files below to see the full abstrac

The MUSICA IASI {H2_{2}O, δD} pair product

We present a global and multi-annual space-borne dataset of tropospheric {H$_{2}$O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H$_{2}$O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H$_{2}$O and δD. Here, this standard MUSICA method for deriving {H$_{2}$O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H$_{2}$O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H$_{2}$O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H$_{2}$O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H$_{2}$O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021)