The unique Efg1 fungal virulence regulon in the catheterized bladder environment.

July 28, 2026| Source: Proceedings of the National Academy of Sciences of the United States of America

Urinary catheterization, a frequent procedure in hospitals, nursing homes, and other healthcare facilities, is a primary driver of nosocomial infections. The most common of these are catheter-associated urinary tract infections (CAUTIs), which often progress to severe complication, sepsis, and ultimately death. The fungus Candida albicans is a primary causative agent of CAUTIs; yet, its tissue-specific pathogenesis remains poorly understood, which complicates development of efficient treatments. While Efg1 is a known virulence driver in CAUTI, its specific downstream targets within the unique bladder environment have not been defined. Here, we identify and validate the EFG1 regulon that is active during conditions that mimic the human catheterized bladder and, additionally, confirm the regulon by transcriptional profiling of catheters retrieved from patients with C. albicans infection. We found that this urine-specific signature is highly conserved in clinical samples, with Efg1-dependent genes being among the most robustly induced transcripts during active human infection. Furthermore, we characterized two of these key factors, ECE1 and EED1 , validating their roles in infection both in vitro in human urine and in vivo using a CAUTI mouse model. Elucidating this tissue-specific regulon offers a strategic roadmap for the development of targeted therapies to mitigate these ever-increasing life-threatening fungal infections.

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Reversing vegetable biodiversity loss to diversify diets.

Vegetables are a critical component of diets, with inadequate intake of this essential food group leading to poor dietary quality and malnutrition. Food system assessments identify insufficient production, comparatively high prices, and sociocultural barriers as key constraints to vegetable consumption. We argue that vegetable biodiversity, spanning vegetable species and their varieties, as well as their wild relative species, is a central yet underutilized lever for enhancing vegetable consumpt

EnvironmentAugust 4, 2026

Sediment accumulation rate predicts the temporal resolution of marine fossil assemblages.

Time averaging (TA), the mixing of noncontemporaneous organisms in fossil assemblages, governs the resolution of paleontological data and determines which biological and environmental processes are recorded in the geological record. To assess variation in TA and its dependence on external drivers, we used amino acid and radiocarbon methods to individually date 7,593 specimens across 384 samples from late Quaternary marine assemblages of calcifying organisms. Bivalve mollusks dominated the data,

EnvironmentJuly 28, 2026

Geometry controls momentum flux in the sprinkler problem.

Hydro- and aero-mechanical devices convert fluid flows into useful motions, force, and power. The operating principles can involve subtle and poorly understood physics, as epitomized by open questions about systems that aspirate flows through curving tubular arms. Since its introduction by Mach and popularization by Feynman, the so-called reverse sprinkler problem has evoked many competing theories and fluid mechanical effects that have not to date been distinguished by experiments. Here we cond

EnvironmentJuly 28, 2026

Guanidine fuels rapid resurrection of desert cyanobacteria.

In desert ecosystems, microbial activity is driven by brief hydration pulses but is severely limited by persistent nutrient scarcity. Cyanobacteria serve as essential pioneer photoautotrophs, maintaining biogeochemical cycles and ecosystem stability in these arid landscapes. However, their ability to quickly reactivate after rehydration is critically restricted by nitrogen availability. Although the nitrogen demand can be met later by biological nitrogen fixation, it is ineffective and irrelevan

EnvironmentJuly 28, 2026

A unified machine-learning framework for ab initio multiscale modeling of liquids.

Understanding and predicting the behavior of liquid matter across length scales-using only the microscopic interactions encoded in the Schrödinger equation-remains a central challenge in the physical sciences. Achieving this goal requires not only an accurate and efficient description of intermolecular forces but also a consistent framework that bridges the micro-, meso-, and macroscales. Here, by combining machine-learned interatomic potentials (MLIPs) with neural classical density functio