CRISPRedict: a CRISPR-Cas9 web tool for interpretable efficiency predictions.

The development of the CRISPR-Cas9 technology has provided a simple yet powerful system for genome editing. Current gRNA design tools serve as an important platform for the efficient application of the CRISPR systems. However, most of the existing tools are black-box models that suffer from limitations, such as variable performance and unclear mechanism of decision making. Here, we introduce CRISPRedict, an interpretable gRNA efficiency prediction model for CRISPR-Cas9 gene editing. Its strength lies in the fact that it can accurately predict efficient guide RNAs-with equivalent performance to state-of-the-art tools-while being a simple linear model. Implemented as a user-friendly web server, CRISPRedict offers (i) quick and accurate predictions across various experimental conditions (e.g. U6/T7 transcription); (ii) regression and classification models for scoring gRNAs and (iii) multiple visualizations to explain the obtained results. Given its performance, interpretability, and versatility, we expect that it will assist researchers in the gRNA design process and facilitate genome editing research. CRISPRedict is available for use at http://www.crispredict.org/.

CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning.

The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system has become a successful and promising technology for gene-editing. To facilitate its effective application, various computational tools have been developed. These tools can assist researchers in the guide RNA (gRNA) design process by predicting cleavage efficiency and specificity and excluding undesirable targets. However, while many tools are available, assessment of their application scenarios and performance benchmarks are limited. Moreover, new deep learning tools have been explored lately for gRNA efficiency prediction, but have not been systematically evaluated. Here, we discuss the approaches that pertain to the on-target activity problem, focusing mainly on the features and computational methods they utilize. Furthermore, we evaluate these tools on independent datasets and give some suggestions for their usage. We conclude with some challenges and perspectives about future directions for CRISPR-Cas9 guide design.

Delayed recurrent enhancing white matter lesions complicating coiling of intracranial aneurysm.

BACKGROUND AND PURPOSE: In recent years, the use of coiling has gained increased popularity for the treatment of intracranial aneurysms, and stroke physicians are confronted with rare pathologies associated with this relatively new and evolving treatment method, such as embolization of pieces of the polymeric filaments from the coils and a subsequent inflammatory response. In particular, white matter enhancing lesions are a rare complication after aneurysm endovascular therapy (EVT), suggesting a foreign body reaction to shedding of hydrophilic coating from the endovascular devices into the blood stream. The description of such a case aims to raise the clinicians' awareness of the symptomatic delayed and recurring inflammatory changes that may occur after endovascular aneurysmal treatment with the use of coiling devices. CASE DESCRIPTION: A 64-year-old woman underwent coiling of a ruptured right posterior communicating artery aneurysm. She was asymptomatic after EVT. One year later, she presented with headache, acoustic hallucinations, paresthesias and left arm weakness. Brain magnetic resonance imaging (MRI) revealed multiple enhancing white matter lesions in the right hemisphere. She was treated with pulse intravenous methylprednisolone, followed by oral prednisolone; all clinical symptoms resolved and imaging findings improved substantially. Two years after tapering the steroids, follow-up symptoms recurred and repeat brain MRI revealed new enhancing white matter lesions. DISCUSSION AND CONCLUSIONS: There is an increasing number of similar reports of enhancing white matter lesions after coiling of intracranial aneurysms, with the incidence estimated to be between 0.5% and 2.3% in different cohort studies. Close monitoring for the appearance of new neurologic symptoms that could suggest delayed brain reactivity should be recommended.

Sensitivity of movement features to fatigue during an exhaustive treadmill run.

HIGHLIGHTS: Trunk frontal plane kinematics is the most sensitive parameter to fatigue. Practitioners should consider this finding during endurance training.Kinetics exhibit a stable linear increase in mean values but a non-linear increase in variance during an exhaustive incremental treadmill run. This may affect training at a submaximal fatigued state.Specific areas in the joint distributions of kinetics and kinematics during treadmill running exhibit increased sensitivity in predicting fatigue state.

A Multi-Label Classifier for Predicting the Most Appropriate Instrumental Method for the Analysis of Contaminants of Emerging Concern.

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) and gas chromatography-high resolution mass spectrometry (GC-HRMS) have revolutionized analytical chemistry among many other disciplines. These advanced instrumentations allow to theoretically capture the whole chemical universe that is contained in samples, giving unimaginable opportunities to the scientific community. Laboratories equipped with these instruments produce a lot of data daily that can be digitally archived. Digital storage of data opens up the opportunity for retrospective suspect screening investigations for the occurrence of chemicals in the stored chromatograms. The first step of this approach involves the prediction of which data is more appropriate to be searched. In this study, we built an optimized multi-label classifier for predicting the most appropriate instrumental method (LC-HRMS or GC-HRMS or both) for the analysis of chemicals in digital specimens. The approach involved the generation of a baseline model based on the knowledge that an expert would use and the generation of an optimized machine learning model. A multi-step feature selection approach, a model selection strategy, and optimization of the classifier's hyperparameters led to a model with accuracy that outperformed the baseline implementation. The models were used to predict the most appropriate instrumental technique for new substances. The scripts are available at GitHub and the dataset at Zenodo.

Omentin Is Independently Associated with Stroke Severity and Ipsilateral Carotid Artery Stenosis in Patients with Acute Cerebral Ischemia.

Mounting evidence indicates an association between adipokines and inflammation-related atherosclerosis. Here, we sought to investigate the association of vaspin and omentin with clinical characteristics and outcomes of patients with acute cerebral ischemia (ACI). Consecutive ACI patients were evaluated within 24 h from symptom-onset. Stroke aetiology was classified using TOAST criteria. Adipokines were assayed using quantikine enzyme immunoassay commercially available kits. Stroke severity was assessed by NIHSS-score, and ipsilateral carotid stenosis (≥50% by NASCET criteria) by ultrasound and CT/MR angiography. Major cerebrovascular events were assessed at three months. We included 135 ACI patients (05 (78%) and 30 (22%) with acute ischemic stroke and transient ischemic attack, respectively; mean age ± SD: 59 ± 10 years; 68% men; median NIHSS-score: 3 (IQR:1-7)). Omentin was strongly correlated to admission stroke severity (Spearman rho coefficient: +0.303; p < 0.001). Patients with ipsilateral carotid stenosis had higher omentin levels compared to patients without stenosis (13.3 ± 8.9 ng/mL vs. 9.5 ± 5.5 ng/mL, p = 0.014). Increasing omentin levels were independently associated with higher stroke severity (linear regression coefficient = 0.290; 95%CI: 0.063-0.516; p = 0.002) and ipsilateral carotid stenosis (linear regression coefficient = 3.411; 95%CI: 0.194-6.628; p = 0.038). No association of vaspin with clinical characteristics and outcomes was found. Circulating omentin may represent a biomarker for the presence of atherosclerotic plaque, associated with higher stroke severity in ACI patients.

Rotational kinematics of pelvis and upper trunk at butterfly stroke: Can fins affect the dynamics of the system?

The purpose of the present study was to investigate the rotational kinematics pattern of the upper trunk and the pelvis and the complexity-variability of their movement, during the sprint butterfly stroke between male and female swimmers with long fins (18-26 cm) and without fins. Two pairs of 3D accelerometers and gyroscopes were used to measure segments' flexion-extension angles. There were no gender differences apart from the record. The amplitude values at the pelvis were significantly larger when swimming without fins while at the C7 they were significantly larger when swimming with them. Autocorrelation coefficients of angles' time histories were higher when swimming with fins for both segments. The power spectrums revealed a dominant frequency representing the stroke period which grew significantly stronger for the fin condition. Correlation Dimension verified a lower dimensionality for the fin condition for the C7 segment movement pattern. Overall fin use seems to offer "strength" to the swimmer's movement pattern. This does not imply better movement coordination, but rather a trend toward a more stable attractor.