Top-down proteomics.

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine.

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak.

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. In this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time.

Top-down mass spectrometry of native proteoforms and their complexes: a community study.

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories.

Temocillin for febrile urinary tract infections caused by ESBL-producing Enterobacteriaceae in children: a monocentric exposed/non-exposed study.

Objectives: To compare the efficacy of temocillin with standard of care (SOC) for treatment of ESBL-producing Enterobacteriaceae (ESBL-E) febrile urinary tract infection (ESBL-E FUTI) in children.

Methods: A monocentric retrospective study of children hospitalized with confirmed ESBL-E FUTI from January 2015 to May 2022 was conducted, comparing clinical cure and a 3 month relapse between two groups of patients: 'exposed' patients (EP) and 'non-exposed' patients (NEP) to temocillin. EP received temocillin for at least 3 days.

Evaluating protein cross-linking as a therapeutic strategy to stabilize SOD1 variants in a mouse model of familial ALS.

Mutations in the gene encoding Cu-Zn superoxide dismutase 1 (SOD1) cause a subset of familial amyotrophic lateral sclerosis (fALS) cases. A shared effect of these mutations is that SOD1, which is normally a stable dimer, dissociates into toxic monomers that seed toxic aggregates. Considerable research effort has been devoted to developing compounds that stabilize the dimer of fALS SOD1 variants, but unfortunately, this has not yet resulted in a treatment.

Corrigendum: Applications and techniques for fast machine learning in science.

[This corrects the article DOI: 10.3389/fdata.2022.

Top-down mass spectrometry of native proteoforms and their complexes: A community study.

The combination of native electrospray ionisation with top-down fragmentation in mass spectrometry allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and co-factors. While this approach is powerful, both native mass spectrometry and top-down mass spectrometry are not yet well standardised, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics (CTDP) initiated a study to develop and test protocols for native mass spectrometry combined with top-down fragmentation of proteins and protein complexes across eleven instruments in nine laboratories.

The Effect of Chemical Environment and Temperature on the Domain Structure of Free-Standing BaTiO via In Situ STEM.

Ferroelectrics, due to their polar nature and reversible switching, can be used to dynamically control surface chemistry for catalysis, chemical switching, and other applications such as water splitting. However, this is a complex phenomenon where ferroelectric domain orientation and switching are intimately linked to surface charges. In this work, the temperature-induced domain behavior of ferroelectric-ferroelastic domains in free-standing BaTiO films under different gas environments, including vacuum and oxygen-rich, is studied by in situ scanning transmission electron microscopy (STEM).

Structure Relaxation Approximation (SRA) for Elucidation of Protein Structures from Ion Mobility Measurements (II). Protein Complexes.

Characterizing structures of protein complexes and their disease-related aberrations is essential to understanding molecular mechanisms of many biological processes. Electrospray ionization coupled with hybrid ion mobility/mass spectrometry (ESI-IM/MS) methods offer sufficient sensitivity, sample throughput, and dynamic range to enable systematic structural characterization of proteomes. However, because ESI-IM/MS characterizes ionized protein systems in the gas phase, it generally remains unclear to what extent the protein ions characterized by IM/MS have retained their solution structures.

High Velocity, Low-Voltage Collective In-Plane Switching in (100) BaTiO Thin Films.

Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly-correlated electrical and elastic coupling that elicit fast and efficient collective switching.

Why it is Unfortunate that Linear Machine Learning "Works" so well in Electromechanical Switching of Ferroelectric Thin Films.

Machine learning (ML) is relied on for materials spectroscopy. It is challenging to make ML models fail because statistical correlations can mimic the physics without causality. Here, using a benchmark band-excitation piezoresponse force microscopy polarization spectroscopy (BEPS) dataset the pitfalls of the so-called "better", "faster", and "less-biased" ML of electromechanical switching are demonstrated and overcome.

Applications and Techniques for Fast Machine Learning in Science.

In this community review report, we discuss applications and techniques for machine learning (ML) in science-the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found.

The European Green Deal and nephrology: a call for action by the European Kidney Health Alliance.

The world faces a dramatic man-made ecologic disaster and healthcare is a crucial part of this problem. Compared with other therapeutic areas, nephrology care, and especially dialysis, creates an excessive burden via water consumption, greenhouse gas emission and waste production. In this advocacy article from the European Kidney Health Alliance we describe the mutual impact of climate change on kidney health and kidney care on ecology.

Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging.

The status of metabolomics as a scientific branch has evolved from proof-of-concept to applications in science, particularly in medical research. To comprehensively evaluate disease metabolomics, multiplatform approaches of NMR combining with mass spectrometry (MS) have been investigated and reported. This mixed-methods approach allows for the exploitation of each individual technique's unique advantages to maximize results.

massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation.

Motivation: Mass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computational challenges in its analysis. The complexity of the data arises from its large size, high-dimensionality and spectral nonlinearity.

The Human Proteoform Project: Defining the human proteome.

Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown.

Peak learning of mass spectrometry imaging data using artificial neural networks.

Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size and high dimensional nature of MSI, especially 3D datasets, still pose computational and memory complexities that hinder accurate identification of biologically relevant molecular patterns. Moreover, the subjectivity in the selection of parameters for conventional pre-processing approaches can lead to bias.

Multimodal platform for assessing drug distribution and response in clinical trials.

Background: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.

Methods: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI.

Assessment of environmental sustainability in renal healthcare.

The health effects of climate change are becoming increasingly important; there are direct effects from heatwaves and floods, and indirect effects from the altered distribution of infectious diseases and changes in crop yield. Ironically, the healthcare system itself carries an environmental burden, contributing to environmental health impacts. Life cycle assessment is a widely accepted and well-established method that quantitatively evaluates environmental impact.

Increasing Top-Down Mass Spectrometry Sequence Coverage by an Order of Magnitude through Optimized Internal Fragment Generation and Assignment.

A major limitation of intact protein fragmentation is the lack of sequence coverage within proteins' interiors. We show that collisionally activated dissociation (CAD) produces extensive internal fragmentation within proteins' interiors that fill the existing gaps in sequence coverage, including disulfide loop regions that cannot be characterized using terminal fragments. A barrier to the adoption of internal fragments is the lack of methods for their generation and assignment.

Local Probe Comparison of Ferroelectric Switching Event Statistics in the Creep and Depinning Regimes in Pb(Zr_{0.2}Ti_{0.8})O_{3} Thin Films.

Ferroelectric materials provide a useful model system to explore the jerky, highly nonlinear dynamics of elastic interfaces in disordered media. The distribution of nanoscale switching event sizes is studied in two Pb(Zr_{0.2}Ti_{0.