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Pseudomonas aeruginosa H1-T6SS delivers effectors in response to exogenous T6SS attacks. In this study, a CRISPRi screen identifies pathways involved in P. aeruginosa resistance to T6SS effectors of Acinetobacter baylyi and Vibrio cholerae.

A modularized open-source pipeline for invasive brain signal decoding bridges the gap between closed-loop neuromodulation and clinical brain–computer interface approaches in a large patient cohort.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

The first experimental demonstration of saturable absorption in core-electron transitions in aluminium paves the way for investigating warm dense matter, which potentially has an important role in planetary science and the realization of inertial confinement fusion.

STM investigations and first principles calculations provide an understanding of the microscopic mechanism behind the mobility of N-heterocyclic carbenes (NHCs) on gold surfaces. Now, it is shown that a ballbot-type motion allows the formation of self-assembled monolayers due to the NHC extracting a gold atom from the surface, leading to a ligated gold adatom.

Federated learning (FL) algorithms have emerged as a promising solution to train models for healthcare imaging across institutions while preserving privacy. Here, the authors describe the Federated Tumor Segmentation (FeTS) challenge for the decentralised benchmarking of FL algorithms and evaluation of Healthcare AI algorithm generalizability in real-world cancer imaging datasets.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

How the histone variant H2A.Z controls cell fate remains unclear. Here, the authors reveal that the H2A.Z interacting partner HMG20A plays a key role in regulating transcription during early head and heart development.

The atmosphere has dried across most regions of Europe in recent decades, a trend that can be attributed primarily to human impacts, according to tree ring records spanning 400 years and Earth system model simulations.

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.

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.

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.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

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.

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.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

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.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

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.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

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.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Over half the world’s rivers dry periodically, yet little is known about the biological communities in dry riverbeds. This study examines biodiversity across 84 non-perennial rivers in 19 countries using DNA metabarcoding. It finds that nutrient availability, climate and biotic interactions influence the biodiversity of these dry environments.

A large-scale CRISPR-mediated deep mutational scanning approach is used to interrogate the function of mutations in the endogenous locus of TP53 mapping to the DNA-binding domain.

During development, groups of cells sometimes have to order themselves relative to a tissue in a coordinated manner, and this is true of ommatidial cells in the eye. Using a genetic and molecular approach, the Nemo kinase is shown to be involved in regulating the rate of ommatidial rotation; the study also links this event to cellular interaction through cadherin, important for coordinating reorientation.

In liquid-phase TEM, microfluidic reactors are used to monitor nanoscale (electro)chemical dynamics in liquid environments. Here, the authors develop a reactor design with accelerated mass transport, facilitating quantitative in-situ and in-operando studies.

Genome assemblies of four filamentous Zygnematophyceae and co-expression network analyses shed light on the evolutionary roots of the mechanism for balancing environmental responses and multicellular growth.

Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance.

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

A species-level phylogenetic analysis of the high-elevation flora of the European Alps reveals that the flora is young and colonist rich. Its assembly was primarily driven by the Pleistocene climatic cycles, rather than ancient orogenic events.

Forest dynamics are monitored at large scales with remote sensing, but individual tree data are necessary for ground-truthing and mechanistic insights. This study on high temporal resolution dendrometer data across Europe reveals that the 2018 heatwave affected tree physiology and growth in unexpected way.

The ubiquitous second messenger c-di-GMP regulates many biological processes in bacteria, including cell cycle, motility, virulence and biofilm formation. Here, Kaczmarczyk et al. develop a c-di-GMP biosensor that enables dynamic real-time tracking of c-di-GMP levels in individual living cells.

Quantifying chemical short-range order (CSRO) remains a formidable for volume-averaged or 2D microscopy methods. Here the authors introduce a machine-learning approach that breaks the resolution limitations of atom probe tomography to reveal the 3D atomistic architecture of CSRO in Fe-based alloys.

Stanislav Kmoch and colleagues identify mutations in TMEM70 in individuals with isolated mitochondrial ATP synthase deficiency, and demonstrate that complementation of cell lines of affected individuals with wild-type TMEM70 restores ATP synthase function.

A broad class of theories exist which share the distinguishing characteristics of quantum mechanics but allow even stronger correlations. Here, the principle of 'information causality' is introduced and shown to be respected by both classical and quantum physics; however, it is violated by other models that resemble quantum mechanics but with stronger correlations. It is suggested that information causality may help to distinguish physical theories from non-physical ones.

There is an urgent need for biomarkers for type 2 diabetes progression that provide a deeper understanding of the disease process. Here, the authors identify biomarkers in three molecular classes, replicate them in other cohorts and explore top protein biomarkers in detail in functional studies.