Protocol to generate dual-target compounds using a transformer chemical language model.

Here, we present a protocol to generate dual-target compounds (DT-CPDs) interacting with two distinct target proteins using a transformer-based chemical language model. We describe steps for installing software, preparing data, and pre-training the model on pairs of single-target compounds (ST-CPDs), which bind to an individual protein, and DT-CPDs. We then detail procedures for assembling ST- and corresponding DT-CPD data for specific protein pairs and evaluating the model's performance on hold-out test sets.

The Best of Both Worlds: ΔDFT Describes Multiresonance TADF Emitters with Wave-Function Accuracy at Density-Functional Cost.

With their narrow-band emission, high quantum yield, and good chemical stability, multiresonance thermally activated delayed fluorescence (MR-TADF) emitters are promising materials for OLED technology. However, accurately modeling key properties, such as the singlet-triplet (ST) energy gap and fluorescence energy, remains challenging. While time-dependent density functional theory (TD-DFT), the workhorse of computational materials science, suffers from fundamental issues, wave function-based coupled-cluster (CC) approaches, like approximate CC of second-order (CC2), are accurate but suffer from high computational cost and unfavorable scaling with system size.

The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat.

Currently in wheat breeding, genome wide association studies (GWAS) have successfully revealed the genetic basis of complex traits such as nitrogen use efficiency (NUE) and its biological processes. In the GWAS model, thresholding is common strategy to indicate deviation of expected range of -(s), and it can be used to find the distribution of true positive associations under or over of test statistics. Therefore, the threshold plays a critical role to identify reliable and significant associations in wide genome, while the proportion of false positive results is relatively low.

The Shu complex interacts with the replicative helicase to prevent mutations and aberrant recombination.

Homologous recombination (HR) is important for DNA damage tolerance during replication. The yeast Shu complex, a conserved homologous recombination factor, prevents replication-associated mutagenesis. Here we examine how yeast cells require the Shu complex for coping with MMS-induced lesions during DNA replication.

Photoinduced formation of a platina-α-lactone - a carbon dioxide complex of platinum. Insights from femtosecond mid-infrared spectroscopy.

The binding of carbon dioxide to a transition metal is a complex phenomenon that involves a major redistribution of electron density between the metal center and the triatomic ligand. The chemical reduction of the ligand reveals itself unambiguously by an angular distortion of the CO-molecule as a result of the occupation of an anti-bonding π-orbital and a shift of its antisymmetric stretching vibration, ν, to lower wavenumbers. Here, we generate a carbon dioxide complex of the heavier group-10 metal, platinum, by ultrafast electronic excitation and cleavage of CO from the photolabile oxalate precursor, oxaliplatin, and monitored the ensuing primary dynamics with ultrafast mid-infrared spectroscopy.

Rationalizing Predictions of Isoform-Selective Phosphoinositide 3-Kinase Inhibitors Using MolAnchor Analysis.

Explaining the predictions of machine learning models is of critical importance for integrating predictive modeling in drug discovery projects. We have generated a test system for predicting isoform selectivity of phosphoinositide 3-kinase (PI3K) inhibitors and systematically analyzed correct predictions of selective inhibitors using a new methodology termed MolAnchor, which is based on the "anchors" concept from explainable artificial intelligence. The approach is designed to generate chemically intuitive explanations of compound predictions.

A "phosphorus derivative" of aziridines: on the importance of ring strain energy and three heteropolar bonds in azaphosphiridines.

Compared to aziridines, azaphosphiridines, which formally result from the replacement of a carbon atom by phosphorus, have been much less studied. In this work, accurate values for one of the most prominent properties, the ring strain energy (RSE), have been theoretically examined for a wide range of azaphosphiridine derivatives. Strongly related aspects of interest for developing the use of azaphosphiridines in heteroatom and polymer chemistry are ring opening reactions and polymerisations, the latter facilitated by their significantly high RSE.

The earliest large carpenter bee () and its adhering pollen (Araliaceae, Theaceae).

The association of pollinators with their host plants is a critical element of ecosystem functioning and one that is usually determined indirectly in the fossil record from specific morphological traits of flowers or putative pollinating animals. The exceptionally fine preservation at Messel, Germany, offers an excellent source of data on pollen from fossil flowers as well as preserved adhering to insects as direct evidence of their association with specific floral lineages. Here, we report on pollen recovered from the body and legs of a large carpenter bee (Apidae: Xylocopinae: Xylocopini) from the Eocene of Messel.

Liquid biopsy in organ damage: introduction of an innovative tool for assessing the complexity of blunt splenic injury.

Liquid biomarkers are essential in trauma cases and critical care and offer valuable insights into the extent of injury, prognostic predictions, and treatment guidance. They can help assess the severity of organ damage (OD), assist in treatment decisions and forecast patient outcomes. Notably, small extracellular vesicles, particularly those involved in splenic trauma, have been overlooked.

EEFSEC deficiency: A selenopathy with early-onset neurodegeneration.

Inborn errors of selenoprotein expression arise from deleterious variants in genes encoding selenoproteins or selenoprotein biosynthetic factors, some of which are associated with neurodegenerative disorders. This study shows that bi-allelic selenocysteine tRNA-specific eukaryotic elongation factor (EEFSEC) variants cause selenoprotein deficiency, leading to progressive neurodegeneration. EEFSEC deficiency, an autosomal recessive disorder, manifests with global developmental delay, progressive spasticity, ataxia, and seizures.

Assessment of the efficacy of palliative sedation in advanced cancer patients by evaluating discomfort levels: a prospective, international, multicenter observational study.

Background: Palliative sedation involves the intentional proportional lowering of the level of consciousness in patients with life-limiting disease who are experiencing refractory suffering. The efficacy of palliative sedation needs to be monitored to ensure patient comfort. The aim of this study was to evaluate the efficacy using discomfort levels combined with sedation/agitation levels.

The Hemibiotrophic Apple Scab Fungus Induces a Biotrophic Interface but Lacks a Necrotrophic Stage.

Microscopic evidence demonstrated a strictly biotrophic lifestyle of the scab fungus on growing apple leaves and characterised its hemibiotrophy as the combination of biotrophy and saprotrophy not described before. The pathogen-host interface was characterised by the formation of knob-like structures of the fungal stroma appressed to epidermal cells as early as 1 day after host penetration, very thin fan-shaped cells covering large parts of the host cell lumen, and enzymatic cuticle penetration from the subcuticular space limited to the protruding conidiophores. The cell wall had numerous orifices, facilitating intimate contact with the host tissue.

Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials.

Dementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive decline and impairs patients' daily life. Affected patients show great heterogeneity in their symptomatic progression, which hampers the identification of efficacious treatments in clinical trials. Using artificial intelligence approaches to enable clinical enrichment trials serves a promising avenue to identify treatments.

Deep learning for opportunistic, end-to-end automated assessment of epicardial adipose tissue in pre-interventional, ECG-gated spiral computed tomography.

Objectives: Recently, epicardial adipose tissue (EAT) assessed by CT was identified as an independent mortality predictor in patients with various cardiac diseases. Our goal was to develop a deep learning pipeline for robust automatic EAT assessment in CT.

Methods: Contrast-enhanced ECG-gated cardiac and thoraco-abdominal spiral CT imaging from 1502 patients undergoing transcatheter aortic valve replacement (TAVR) was included.

Isolation, Purification, and Comprehensive Flow Cytometry Assessment of Lung Stromal Cells.

Stromal cells are non-hematopoietic cells that consist of endothelial cells and various mesenchymal cell populations. The composition of the stromal cell compartment is diverse in different organs. Numerous recent studies demonstrated that the lung environment contains heterogeneous mesenchymal stromal cell populations with distinctive genomic signatures and location preferences.

Metastasis Detection Using True and Artificial T1-Weighted Postcontrast Images in Brain MRI.

Objectives: Small lesions are the limiting factor for reducing gadolinium-based contrast agents in brain magnetic resonance imaging (MRI). The purpose of this study was to compare the sensitivity and precision in metastasis detection on true contrast-enhanced T1-weighted (T1w) images and artificial images synthesized by a deep learning method using low-dose images.

Materials And Methods: In this prospective, multicenter study (5 centers, 12 scanners), 917 participants underwent brain MRI between October 2021 and March 2023 including T1w low-dose (0.

Influence of Data Curation and Confidence Levels on Compound Predictions Using Machine Learning Models.

While data curation principles and practices are a major topic in data science, they are often not explicitly considered in machine learning (ML) applications in chemistry. We have been interested in evaluating the potential effects of data curation on the performance of molecular ML models. Therefore, a sequential curation scheme was developed for compounds and activity data, and different ML classification models were generated at increasing data confidence levels and evaluated.

Identification of cell type-specific cell-penetrating peptides through in vivo phage display leveraged by next generation sequencing.

Vascular anomalies (VA) refer to abnormal blood or lymphatic vessel architecture, most often as a result of dysregulated growth. Venous malformations (VM), a subgroup of VAs, are triggered by activating mutations in the Angiopoietin/TIE2-PI3K/AKT/mTOR signaling pathway with TIE2 L914F (gene name TEK) being one of the most frequent mutations in patients with VMs. Although systemic targeting of the overactivated pathway is possible, it would be a therapeutic advantage to restrict treatment to only the affected lesions.

Linear and Two-Dimensional Infrared Spectroscopy of the Multifunctional Vibrational Probe, 3-(4-Azidophenyl) Propiolonitrile. Deperturbing a Fermi Triad by Isotopic Substitution.

Infrared probes are chemical moieties whose vibrational modes are used to obtain spectroscopic information about structural dynamics of complex systems; in particular, of biomacromolecules. Here, we explore the vibrational spectroscopy and dynamics of a reagent, 3-(4-azidophenyl)propiolonitrile (AzPPN), for selectively tagging thiols in protein environments with a multifunctional infrared probe containing both, an azide and a nitrile chromophore. The linear infrared spectrum of AzPPN is heavily perturbed in the antisymmetric azide stretching region as a result of accidental Fermi resonances.

Strong coupling between WS monolayer excitons and a hybrid plasmon polariton at room temperature.

Light-matter interactions between plasmonic and excitonic modes have attracted considerable interest in recent years. A major challenge in achieving strong coupling is the identification of suitable metallic nanostructures that combine tight field confinement with sufficiently low losses. Here, we report on a room-temperature study on the interaction of tungsten disulfide (WS) monolayer excitons with a hybrid plasmon polariton (HPP) mode supported by nanogroove grating structures milled into single-crystalline silver flakes.

Pain chronification risk assessment: advanced phenotyping and scoring for prediction and treatments tailored to individualized patient profile.

Unlabelled: Acute pain is a physiologic, protective life-important warning neurological signal indicating multi-level tissue modulations caused by a broad spectrum of health adverse events such as stress overload, mechanical trauma, ischemia-reperfusion, sterile and infection-triggered inflammation, single- and multi-organ damage, acute and chronic wounds, tissue remodeling and degeneration, amongst others. On the other hand, pain chronification results in a pathologic transformation from the protective pain signaling into persistent debilitative medical condition with severe consequences including but not restricted to phenotype-specific behavioral patterns, reduced quality of life, and cognitive and mood disorders. Who is predisposed to an increased vs.