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Water electrolysis provides a carbon-neutral means to generate hydrogen fuel from water, but the process typically requires expensive, rare metal catalysts. Here, the authors prepare hydrogen- and oxygen-evolving electrocatalysts from earth-abundant elements that outperform noble-metal counterparts.

Unfortunately, the noble aims of the Melbourne Consensus statement on the early detection of prostate cancer lack rigour, failing to take into account the breadth of evidence in this field; as a result, they fall disappointingly short of providing clarity on this important issue.

Diamond, a statistically rigorous method, is capable of finding meaningful feature interactions within machine learning models, making black-box models more interpretable for science and medicine.

Several solutions to the ‘missing xenon’ problem have been proposed that involve the selective sorption of Xe in minerals found in the Earth. It is now shown that a zeolite, Ag-natrolite, absorbs and retains 28 wt% Xe at 1.7 GPa and 250 °C, conditions found in subsurface Earth, through expulsion of metallic Ag(0).

Surface enhanced Raman spectroscopy is a sensitive technique capable of detecting single molecules via their vibrational fingerprints. Here, the authors demonstrate improved sensitivity with photo-induced enhanced Raman spectroscopy applied to trace-level detection of explosives and other analytes.

Cascadia is a mass spectrometry-based de novo sequencing model that uses a transformer architecture to handle data-independent acquisition data and achieves substantially improved performance across a range of instruments and experimental protocols.

A full theoretical understanding of plasmon decay into hot carriers will help in applications such as solar cells or photocatalysis. Here, the authors present a quantized plasmon model to calculate the hot-carrier distribution from plasmon decay and show its sensitivity to the band structure of the host metal.

A theoretical foundation for entrapment methods is presented, along with a method that enables more accurate evaluation of false discovery rate (FDR) control in proteomics mass spectrometry analysis pipelines. Evaluation of popular data-dependent acquisition tools indicates that these generally seem to control the FDR, but data-independent acquisition tools exhibit inconsistent control of the FDR at both the peptide and protein levels.

Identification of the peptide that generates each acquired tandem mass spectrum is a fundamental challenge in mass spectrometry-based proteomics. Here, the authors present Casanovo, a machine learning model that translates the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide.

There is on-going research into efficient noble metal-free materials for electrocatalytic hydrogen evolution. Here, the authors prepare ternary molybdenum sulfoselenide particles supported on three-dimensional porous nickel selenide foam, and demonstrate the high efficiency of the hydrogen evolving composite.

Douglas William Hume assesses a first-hand account of controversial work with the Yanomami people.

Electrocatalysts for the oxygen evolution reaction are coated with carbon layers to improve performance but the mode of operation is poorly understood. Here, authors show charge transfer between catalyst and carbon boosts the catalytic activity of the carbon to rival that of the underlying material.

Efficient and durable electrocatalysts are essential for boosting oxygen evolution reaction toward hydrogen production. Here, the authors report a combined theoretical and experimental study on high-entropy spinel oxide with element mixing and strains providing superior activity and stability.

Membrane-less electrochemical systems eliminate the need for costly ion-exchange membranes, but typically suffer from low-power densities. Braff et al.propose a hydrogen bromine laminar flow battery, which rivals the performance of the best membrane-based systems.

The development of malaria parasites is controlled by coordinated changes in gene expression. Here, the authors show that the three-dimensional genome structure of human malaria parasites is strongly connected with transcriptional activity of specific gene families throughout the life cycles of Plasmodium falciparum and Plasmodium vivax parasites.

Authors report MagNet, a plasma extracellular vesicle (EV) enrichment strategy using magnetic beads. Proteomic interrogation of this plasma EV fraction enables the detection of proteins that are beyond the dynamic range of mass spectrometry of unfractionated plasma.

The authors achieve gate-controlled proximitization of a quantum dot in a planar germanium heterostructure, an isotopically purifiable group IV material. A patterned Pt germanosilicide superconductor is introduced via a thermally activated reaction.

Metallic glasses are strong but at the same time are brittle once they yield. A new Pd-based metallic glass now shows significantly enhanced fracture toughness. The unique combination of yield strength and toughness makes this glass comparable to the toughest as well as strongest materials known.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Ni–Fe based compound are known as active electrocatalysts for oxygen evolution reaction, but not a good choice for the other half-reaction of water-splitting. Here the authors report a unique interface between Ni and γ-Fe₂O₃ that efficiently catalyzes the cathodic hydrogen evolution reaction.

Selective electrochemical CO₂ reduction (CO₂RR) in strong acids remains challenging due to competition with the hydrogen evolution reaction. Now it is reported that peripheral functionalization of immobilized molecular complexes with quaternary ammonium groups can regulate the mass distribution surrounding the active sites, enabling selective CO₂RR in strong acids.

Harmful algal blooms (HABs) pose negative worldwide impacts that could be minimized through the development of a forecasting tool. Quantitative analysis of peptides produced by a coastal microbiome prior to a HAB reveals predictive biomarkers that can forecast bloom events over 24 hours in advance.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

A self-supervised approach to learning from 24 million spectra generates a foundation model for detecting and characterizing small molecules by tandem mass spectrometry.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

Dense mapping of DNase I cleavage sites across the whole yeast genome by next-generation sequencing reveals a global view of the binding of regulatory proteins to genomic DNA. The high resolution allows the identification of new binding sites for known factors as well as the de novo derivation of factor binding motifs.