Chiral 1,5-disubstituted 1,2,3-triazoles-versatile tools for foldamers and peptidomimetic applications

1,4- A nd 1,5-Disubstituted triazole amino acid monomers have gained increasing interest among peptidic foldamers, as they are easily prepared via Cu- A nd Ru-catalyzed click reactions, with the potential for side chain variation. While the latter is key to their applicability, the synthesis and structural properties of the chiral mono-or disubstituted triazole amino acids have only been partially addressed. We here present the synthesis of all eight possible chiral derivatives of a triazole monomer prepared via a ruthenium-catalyzed azide alkyne cycloaddition (RuAAC). To evaluate the conformational properties of the individual building units, a systematic quantum chemical study was performed on all monomers, indicating their capacity to form several low energy conformers. This feature may be used to effect structural diversity when the monomers are inserted into various peptide sequences. We envisage that these results will facilitate new applications for these artificial oligomeric compounds in diverse areas, ranging from pharmaceutics to biotechnology

Grignard synthesis of fluorinated nanoporous element organic frameworks based on the heteroatoms P, B, Si, Sn and Ge

We present the synthesis and characterization of fluorinated polymers based on P, B, Si, Sn and Ge as heteroatoms via Grignard activation. The polymers are microporous with hydrophobic surfaces. The borate-based polymer was successfully applied as solid acid catalyst in the esterification of acetic acid with ethanol. Grignard synthesis of fluorinated nanoporous element organic frameworks based on the heteroatoms P, B, Si, Sn and Ge Recently, porous polymers have attracted considerable attention as highly versatile materials for adsorption, separation and storage of gases, in catalysis, for optoelectronic applications and energy storage. Especially, metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) are of interest due to their high surface areas and pore volumes. In order to tune the surface polarity, porous ionic organic networks were reported. Depending on the desired properties such as porosity, polarity and functionality, these materials can be tailored for their application by varying the organic linker and connector element. The utilization of fluorinated linkers was reported for different MOFs and a COF, showing enhanced properties in terms of stability, hydrophobicity, gas affinity and selectivity in comparison to their non-fluorinated materials. In continuation of our work on element organic frameworks (EOFs) with P, Si and Sn as connector elements, here we present the synthesis and characterization of respective fluorinated porous polymers with P, B, Si, Sn and Ge as heteroatoms. The catalytic application of the borate based polymer as solid acid catalyst was demonstrated in the esterification of acetic acid with ethanol as test reaction. As the activation of the fluorinated biphenyl linker was not successful neither via lithiation as reported for the non-fluorinated linker nor via classical Grignard reaction, a magnesium-halogen exchange was applied. The linker 4,4′-dibromooctafluorbiphenyl was activated twofold with isopropylmagnesium chloride lithium chloride (turbo Grignard) and subsequent reaction with the respective element chlorides in a one-pot procedure (Scheme 1) resulted in the fluorinated polymers EF-EOF (E = P, B, Si, Sn, Ge). (Perfluorophenyl)-magnesium bromide was used for end-capping, converting remaining E–Cl bonds into E–Ar bonds to form fully substituted trivalent or tetravalent centers, respectively. In all cases, the resulting polymers were obtained as fluffy white powders

Separation in Biorefineries by Liquid Phase Adsorption: Itaconic Acid as Case Study

In biorefinery processes often the downstream processing is the technological bottleneck for an overall high efficiency. On the basis of recent developments, the selective liquid phase adsorption applying highly hydrophobic porous materials opened up new opportunities for process development. In this contribution, the efficiency of selective liquid phase adsorption is demonstrated for the separation and purification of itaconic acid from aqueous solutions for the first time. A wide range of different adsorbents was screened, revealing the surface polarity as well as textural properties as critical parameters for their performance. Adsorption from mixed solutions of itaconic acid and glucose exhibited extraordinary high selectivities for adsorbents with highly hydrophobic surfaces, especially certain activated carbons and hyper-cross-linked polymers. Evaluation of the pH dependence showed that the respective molecular species of itaconic acid/itaconate has a major impact on the adsorption performance. Additionally, experiments on a continuously operated fixed-bed adsorber were carried out, and the desorption behavior was evaluated. Overall, the technical feasibility of the selective adsorptive removal of itaconic acid from aqueous solutions with hydrophobic adsorbents is demonstrated as a model system for an alternative technology to conventional separation strategies in biorefinery concepts

Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-weighted MRI datasets (May 2001 through December 2015) from a national brain tumor consortium (n = 184; median age, 7 years [range, 1-23 years]; 94 male patients) and a pediatric cancer center (n = 100; median age, 8 years [range, 1-19 years]; 47 male patients) to develop and evaluate deep learning neural networks for pediatric low-grade glioma segmentation using a stepwise transfer learning approach to maximize performance in a limited data scenario. The best model was externally tested on an independent test set and subjected to randomized blinded evaluation by three clinicians, wherein they assessed clinical acceptability of expert- and artificial intelligence (AI)-generated segmentations via 10-point Likert scales and Turing tests. Results The best AI model used in-domain stepwise transfer learning (median Dice score coefficient, 0.88 [IQR, 0.72-0.91] vs 0.812 [IQR, 0.56-0.89] for baseline model; P = .049). With external testing, the AI model yielded excellent accuracy using reference standards from three clinical experts (median Dice similarity coefficients: expert 1, 0.83 [IQR, 0.75-0.90]; expert 2, 0.81 [IQR, 0.70-0.89]; expert 3, 0.81 [IQR, 0.68-0.88]; mean accuracy, 0.82). For clinical benchmarking (n = 100 scans), experts rated AI-based segmentations higher on average compared with other experts (median Likert score, 9 [IQR, 7-9] vs 7 [IQR 7-9]) and rated more AI segmentations as clinically acceptable (80.2% vs 65.4%). Experts correctly predicted the origin of AI segmentations in an average of 26.0% of cases. Conclusion Stepwise transfer learning enabled expert-level automated pediatric brain tumor autosegmentation and volumetric measurement with a high level of clinical acceptability. Keywords: Stepwise Transfer Learning, Pediatric Brain Tumors, MRI Segmentation, Deep Learning Supplemental material is available for this article. © RSNA, 2024

Adverse clinical sequelae after skin branding: a case series

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Population-based study of alcohol-related liver disease in England 2001-2018: Influence of socioeconomic position

INTRODUCTION: England has seen an increase in deaths due to alcohol-related liver disease (ALD) since 2001. We studied the influence of socioeconomic position on the incidence of ALD and the mortality after ALD diagnosis in England in 2001–2018.METHODS: This was an observational cohort study based on health records contained within the UK Clinical Practice Research Datalink covering primary care, secondary care, cause of death registration, and deprivation of neighborhood areas in 18.8 million residents. We estimated incidence rate and incidence rate ratios of ALD and hazard ratios of mortality.RESULTS: ALD was diagnosed in 57,784 individuals with a median age of 54 years and of whom 43% had cirrhosis. The ALD incidence rate increased by 65% between 2001 and 2018 in England to reach 56.1 per 100,000 person-years in 2018. The ALD incidence was 3-fold higher in those from the most deprived quintile vs those from the least deprived quintile (incidence rate ratio 3.30, 95% confidence interval 3.21–3.38), with reducing inequality at older than at younger ages. For 55- to 74-year-olds, there was a notable increase in the incidence rate between 2001 and 2018, from 96.1 to 158 per 100,000 person-years in the most deprived quintile and from 32.5 to 70.0 in the least deprived quintile. After ALD diagnosis, the mortality risk was higher for patients from the most deprived quintile vs those from the least deprived quintile (hazard ratio 1.22, 95% confidence interval 1.18–1.27), and this ratio did not change during 2001–2018.DISCUSSION: The increasing ALD incidence in England is a greater burden on individuals of low economic position compared with that on those of high socioeconomic position. This finding highlights ALD as a contributor to inequality in health

Ruthenium-catalyzed azide alkyne cycloaddition reaction: scope, mechanism and applications

The ruthenium-catalyzed azide alkyne cycloaddition (RuAAC) affords 1,5-disubstituted 1,2,3-triazoles in one step and complements the more established copper-catalyzed reaction providing the 1,4-isomer. The RuAAC reaction has quickly found its way into the organic chemistry toolbox and found applications in many different areas, such as medicinal chemistry, polymer synthesis, organocatalysis, supramolecular chemistry, and the construction of electronic devices. This Review discusses the mechanism, scope, and applications of the RuAAC reaction, covering the literature from the last 10 years

GRB 221009A, The BOAT

GRB 221009A has been referred to as the Brightest Of All Time (the BOAT). We investigate the veracity of this statement by comparing it with a half century of prompt gamma-ray burst observations. This burst is the brightest ever detected by the measures of peak flux and fluence. Unexpectedly, GRB 221009A has the highest isotropic-equivalent total energy ever identified, while the peak luminosity is at the $\sim99$th percentile of the known distribution. We explore how such a burst can be powered and discuss potential implications for ultra-long and high-redshift gamma-ray bursts. By geometric extrapolation of the total fluence and peak flux distributions GRB 221009A appears to be a once in 10,000 year event. Thus, while it almost certainly not the BOAT over all of cosmic history, it may be the brightest gamma-ray burst since human civilization began.Comment: Resubmitted to ApJ

Targeting membrane-bound viral RNA synthesis reveals potent inhibition of diverse coronaviruses including the middle East respiratory syndrome virus.

Coronaviruses raise serious concerns as emerging zoonotic viruses without specific antiviral drugs available. Here we screened a collection of 16671 diverse compounds for anti-human coronavirus 229E activity and identified an inhibitor, designated K22, that specifically targets membrane-bound coronaviral RNA synthesis. K22 exerts most potent antiviral activity after virus entry during an early step of the viral life cycle. Specifically, the formation of double membrane vesicles (DMVs), a hallmark of coronavirus replication, was greatly impaired upon K22 treatment accompanied by near-complete inhibition of viral RNA synthesis. K22-resistant viruses contained substitutions in non-structural protein 6 (nsp6), a membrane-spanning integral component of the viral replication complex implicated in DMV formation, corroborating that K22 targets membrane bound viral RNA synthesis. Besides K22 resistance, the nsp6 mutants induced a reduced number of DMVs, displayed decreased specific infectivity, while RNA synthesis was not affected. Importantly, K22 inhibits a broad range of coronaviruses, including Middle East respiratory syndrome coronavirus (MERS-CoV), and efficient inhibition was achieved in primary human epithelia cultures representing the entry port of human coronavirus infection. Collectively, this study proposes an evolutionary conserved step in the life cycle of positive-stranded RNA viruses, the recruitment of cellular membranes for viral replication, as vulnerable and, most importantly, druggable target for antiviral intervention. We expect this mode of action to serve as a paradigm for the development of potent antiviral drugs to combat many animal and human virus infections