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N-acetylglucosamine-1-phosphodiester α-N-acetylglucosaminidase (NAGPA), also known as the uncovering enzyme, catalyzes the final step in mannose-6-phosphate (M6P) signal generation for lysosomal enzyme trafficking. Despite its central role, the enzyme's architecture, catalytic mechanism, and the contribution of its C-terminal region remain incompletely defined. Here, we combine solution biophysics, cryo-electron microscopy, structural modeling, and a quantitative cell-based assay to characterize human NAGPA. We show that NAGPA forms a noncovalent dimer in solution, resolving prior uncertainty regarding disulfide-linked higher-order assemblies. The structure reveals an elongated dimer composed of two catalytic cores and two C-terminal EGF-like stalks, semi-rigid in nature, that likely position the catalytic domains ∼5 nm from the membrane. A structure determined in the presence of the substrate analog GlcNAc-1-phosphate captures GlcNAc and phosphate in the active site, identifying an invariant DGGGS motif that is critical for substrate recognition and enzyme catalysis. Based on these observations, we propose a substrate-assisted SNi-like mechanism for cleavage of the glycosidic C-O bond between GlcNAc and M6P. Functional assays show that the membrane-tethered full-length NAGPA is more active than the isolated catalytic core, and that mutations in the hinge linking the catalytic domain to the C-terminal stalk reduce activity. Together, these findings establish a structural and mechanistic framework for understanding NAGPA function in lysosomal enzyme targeting.

Multi-input association prediction is central to many key problems in computational biology, spanning tasks from drug-target, protein-protein, and virus-host interactions to higher-order challenges such as drug synergy modeling and peptide-major histocompatibility complex-T cell receptor binding prediction. Yet, widely used benchmarks often overestimate performance by enabling models to exploit degree ratio shortcut learning, while alternative out-of-distribution splits are overly restrictive and impractical. Here, we introduce an entity-balanced evaluation framework that systematically neutralizes shortcut signals by balancing positive and negative associations at the entity level. This enables fairer assessments that reflect genuine relational learning and extend naturally from pairwise to multi-entity problems. We further present UnbiasNet, a model-agnostic training strategy that cycles through diverse entity-balanced sub-training sets, removing access to degree ratio bias and enhancing robustness. Applied to drug-target, drug synergy, and virus-host prediction, our framework reveals the extent of shortcut reliance in existing methods while enabling consistent identification of meaningful biological associations. Furthermore, we demonstrate that removing access to degree ratio shortcuts directs models toward biologically meaningful features, improving both robustness and interpretability, thereby setting a rigorous foundation for future methodological progress.

The eukaryotic DNA damage and replication stress checkpoint is initiated by activation of the apical kinase complex ATR-ATRIP on RPA-coated ssDNA. In Saccharomyces cerevisiae, the Mec1-Ddc2 (hATR-ATRIP) activator and checkpoint mediator Dpb11 (hTopBP1) is recruited to the 9-1-1 checkpoint clamp (another Mec1-Ddc2 activator) at 5' ss-dsDNA junctions. It remains unclear how Mec1-Ddc2 encounters its activators on damaged DNA due to their differential DNA binding preferences. Using real-time single-molecule imaging, we show that Dpb11 binds to ssDNA directly and localizes to ss-dsDNA junctions in an RPA-dependent manner. Furthermore, Dpb11 recruits Mec1-Ddc2 to ss-dsDNA junctions. Single-molecule force spectroscopy was used to demonstrate that Dpb11 forms bridges on ssDNA, both alone and in the presence of RPA, reducing the end-to-end distance of gapped DNA. These data support a model in which Dpb11 facilitates Mec1-Ddc2 colocalization with its activators directly by recruiting Mec1-Ddc2 to gap junctions and indirectly by decreasing the effective gap length.

An unexpected loud sound can elicit an acoustic startle reflex and potentially cause a temporary threshold shift (TTS) for hearing and noise-induced tinnitus for a short period of time. This occurs, for example, with the high-amplitude noise burst that accompanies a bright light and impulsive force when police or military use a "flashbang" grenade to temporarily disable or confuse an adversary. This pilot study evaluated the effects of an unexpected loud acoustic impulse sound on human subject performance in terms of (1) word recognition in noise, and (2) sound localization, both examined in a hemi-anechoic free field with a horizontal plane 32 loudspeaker array. Eleven normal hearing, young, adult, male subjects were tested to determine whether acoustic startle, simulated TTS, simulated tinnitus, and combinations thereof, negatively impact performance. Results indicate that performance in a localization task is substantially affected by all three (and combinations) of these manipulations, whereas word in noise performance is principally degraded by TTS simulation. While these results are preliminary, due to the small sample size, the findings have potential implications for development of non-lethal flashbang grenades, i.e., without a concussive incendiary component.

Chronic stress, frequently associated with dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis and reduced neuroplasticity, is a major risk factor for psychiatric disorders such as anxiety and depression. The present study aimed to validate a 21-day chronic unpredictable stress (CUS) model and to investigate the effects of the Mas receptor agonist AVE0991 on stress-induced behavioral and molecular alterations. Male C57BL/6J mice were exposed to a 21-day CUS protocol. Animals were randomly assigned to four groups: control + saline, CUS + saline, control + AVE0991, and CUS + AVE0991 (3 mg/kg, i.p.). AVE was administered daily during the last two weeks of the stress protocol. Behavioral tests were performed to evaluate anxiety- and depressive-like behaviors, and plasma corticosterone, blood glucose levels, and brain-derived neurotrophic factor (BDNF) levels in the prefrontal cortex, hippocampus, and hypothalamus were measured. CUS exposure significantly increased plasma corticosterone and glucose levels and induced anxiety- and depressive-like behaviors. Stressed animals also showed reduced BDNF levels in the prefrontal cortex, hippocampus, and hypothalamus. Treatment with AVE0991 attenuated the increase in corticosterone and prevented stress-induced hyperglycemia. Moreover, AVE0991 reduced depressive-like behavior, increased latency to immobility, and improved anxiety-related parameters in the elevated plus maze and open field tests without affecting locomotor activity. AVE0991 also prevented the reduction of BDNF levels in stress-exposed animals. These findings validate the CUS model and demonstrate that activation of the Mas receptor by AVE0991 exerts anxiolytic, antidepressant, and neuroprotective effects, supporting its potential as a therapeutic strategy for stress-related neuropsychiatric disorders.

Tau is a microtubule-associated protein that plays a central role in neuronal stability and axonal transport. However, under pathological conditions, it undergoes structural and functional changes that lead to Alzheimer's disease (AD) and related tauopathies. Recent evidence highlights liquid-liquid phase separation (LLPS) as a critical mechanism underlying tau aggregation and the subsequent formation of neurofibrillary tangles (NFTs). This chapter explores the properties of tau, including its intrinsically disordered nature, isoforms, and post-translational modifications (PTMs), that predispose it to LLPS. We discuss the thermodynamic and molecular principles of LLPS, with emphasis on the interplay between multivalent interactions, crowding effects, RNA binding, and cofactors that modulate the formation of tau condensates. Special attention is given to the transition from dynamic, reversible tau droplets to irreversible fibrillar assemblies. The chapter further examines how truncation and PTM cross-talk alter the phase behavior and aggregation propensity of tau. Cellular implications of tau LLPS, including its role in stress granules, synaptic dysfunction, and seeding of NFTs, are also analyzed. Finally, we highlight the regulatory roles of chaperones, metal ions, and interacting proteins and underscore the therapeutic potential of targeting tau phase separation. Together, this synthesis positions the LLPS of tau as a pivotal event in AD pathogenesis and a promising target for therapeutic intervention.

Bacterial catabolism of 2,3-dihydroxypropanesulfonate (DHPS) links algal production to marine degradation and connects sulfosugar metabolism to sulfide production in the gut. In surface seawater, DHPS occurs as a dilute, mixed R/S pool, whereas in the anaerobic gut it is produced predominantly as S-DHPS through bacterial sulfoglycolysis pathways. Uptake is achieved via tripartite ATP-independent periplasmic (TRAP) transporters that employ periplasmic substrate-binding proteins (HpsK), but the molecular basis of enantiomer recognition has not been defined. Here, we compare HpsK proteins from the marine bacterium Ruegeria pomeroyi and the gut anaerobe Bilophila wadsworthia using proteomics, biophysical analysis, X-ray crystallography, and bioinformatics. RpHpsK binds both R- and S-DHPS with low-nanomolar affinity (K D 5-9 nM), whereas BwHpsK binds selectively to S-DHPS (K D 530 nM), representing an ∼100-fold difference in affinity and strict stereoselectivity. Crystal structures reveal two contrasting strategies for chiral recognition: RpHpsK accommodates both enantiomers through subtle side-chain "toggling" within an otherwise conserved binding pocket, whereas BwHpsK achieves stereoselectivity through a distinct hydrogen-bonding network and a binding site that sterically excludes R-DHPS. Sequence similarity and genome neighbourhood analyses place these proteins in separate clusters associated with oxidative (HpsNOP) or glycyl radical enzyme-linked (HpsGH/HpfGH) pathways. These findings show how changes in binding-site architecture tune ligand stereoselectivity and illustrate the adaptation of TRAP-associated substrate binding proteins to distinct ecological and metabolic niches.

The identification of novel noninvasive biomarkers remains a major challenge in the diagnosis of neurodegenerative diseases. Significant efforts focus on fluid biomarkers, including proteins, peptides, and miRNAs, detectable in blood plasma and peripheral blood cells. Here, we review recent findings on blood plasma and peripheral blood cells physical parameters in Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis emphasizing atomic force microscopy and calorimetry assay. Alterations in morphology, nanostructure, and stiffness of red blood cells and platelets, together with thermodynamic signatures of red blood cells and plasma, provide sensitive indicators of disease-related changes. These integrated biophysical parameters not only distinguish neurodegeneration from healthy states but also enable discrimination among different neurodegenerative disorders, highlighting their potential as minimally invasive diagnostic markers.

LIM domain kinase 1 (LIMK1) has been identified as a promising therapeutic target for a variety of conditions, such as chronic pain, open-angle glaucoma, various cancers, schizophrenia, and Fragile X syndrome. However, identifying inhibitors that selectively inhibit LIMK1 over LIM domain kinase 2 (LIMK2) has proven to be challenging. A viable strategy to overcome this difficulty is the development of covalent inhibitors, which can offer both potency and selectivity for LIMK1 due to a reactive cysteine, C349, near the active site absent in its paralog LIMK2. Here we identify an irreversible covalent inhibitor of LIMK1 (cLIMK1i), which is highly selective for LIMK1 over both LIMK2 and a panel of over 100 kinases. A crystal structure of LIMK1 soaked with cLIMK1i reveals it is a type I inhibitor occupying the ATP-binding site with its acrylamide moiety oriented toward the P-loop where C349 resides. Computational modeling supports that the P-loop of LIMK1 can adopt a conformation compatible with covalent bond formation. Biochemical and biophysical characterization of the interaction of cLIMK1i with LIMK1 demonstrates that the covalent bond with LIMK1-C349 is essential for its potent inhibition. These results support covalent inhibition of LIMK1 as a viable strategy for selectively inhibiting LIMK1 over LIMK2 and other kinases.

Over the last forty years, monoclonal antibodies have become increasingly important therapeutic agents, with most manufactured as preformulated solutions. However, bioformulation of complex proteins is a difficult engineering challenge; formulations must be tailored to individual therapies, necessitating time- and material-intensive campaigns to select combinations of excipients to simultaneously optimize various design criteria. These additives complicate formulation design with unintuitive and non-linear relationships, creating a vast multidimensional design space that is intrinsically difficult to optimize using traditional techniques. To address this challenge, we investigated a high-throughput discovery pipeline using machine learning to model and predict the effects of GRAS excipients on formulation behavior of a model antibody. This was supported by automation-assisted "on-demand" formulation to produce dozens of uniquely formulated antibody solutions for downstream evaluation and biophysical characterization. This pipeline was then integrated into an iterative closed-loop cycle of automated Design-Build-Test-Learn (DBTL), where new rounds of experiments are designed by the model. The process yielded both improved formulations and accurate predictive models of formulation behavior across multiple target objectives (melting temperature, diffusivity, and high-concentration viscosity). This validates the utility of this technique to both map the underlying property-function landscape and effectively guide formulation development while balancing multiple competing design requirements.

Giant viruses are large DNA viruses that infect unicellular and multicellular eukaryotes and form exceptionally large extracellular particles. (Meta)genomics and (meta)transcriptomics have provided insight into their diverse coding repertoire, but many of the proteins remain to be characterized as they lack homology with known proteins. Here, we integrate cross-linking mass spectrometry, quantitative proteomics, computational tools and cryo-EM data to characterize the protein architecture of intact melbournevirus particles. Based on this, we allocate 88 viral proteins to different virion sub-compartments and propose topologies of 25 inner membrane proteins. We assign eight components of the capsid in cryo-EM data, including proteins that tether the capsid shell to the membrane, reflecting key points in virion maturation. The data provide a valuable resource and demonstrate the power of an integrative approach to gain system-level structural insights into a poorly characterized biological system.

Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Studies were included if they provided Centiloids, radiotracer, age, and sex. Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%). In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

[This corrects the article DOI: 10.1039/D2RA06711K.].

Phytoplankton cells exude a wide array of chemicals in the water column, generating a localized microenvironment known as the phycosphere. Although it is now well accepted that the phycosphere mediates interactions between phytoplankton and bacteria, the chemical gradients around individual phytoplankton cells have never been explicitly measured, and their shape has been classically assumed to be set by ideal diffusion. Here we used Raman microspectroscopy to obtain micrometer-scale measurements of the concentration profile of a phytoplankton metabolite (fucoxanthin) around individual phytoplankton cells of different species, having radii between [Formula: see text] and 60 [Formula: see text]m. We found that fucoxanthin concentration decreases more rapidly with distance from the cell than predicted by ideal diffusion, showing that the phycosphere includes compounds whose diffusion is characterized by nonideal effects. We explain this observation using a space-dependent diffusivity model where nonideality arises from viscosity and solubility gradients in the extracellular environment. Our results suggest an onion-structured model of the phycosphere, in which small hydrophilic solutes that obey ideal diffusion generate broad but weak gradients, whereas insoluble compounds are retained within [Formula: see text] to [Formula: see text] from the phytoplankton cell surface and yield steep gradients of organic matter. These observations, supported by evidence that fucoxanthin can act as an effective chemoattractant for marine bacteria, show the existence of strong and highly localized chemical cues with potentially far-reaching impacts on microbial interactions in aquatic environments. These findings highlight the importance of directly measuring the microscale chemical landscape experienced by marine microbes.

Recently, powerful experimental techniques have emerged that use infrared vibrational excitation to modulate UV/VIS spectra for applications such as subensemble-selective photochemistry in VIPER 2D-IR spectroscopy, vibrationally enhanced multiplexing in fluorescence imaging, single molecule vibrational spectroscopy, and IR-induced modulation of photocurrents in optoelectronic devices. Although these approaches rely on IR induced modulation of electronic spectra, they do not directly measure it. Here, we combine ultrafast two-dimensional vibrational-electronic (2D-VE) spectroscopy and theoretical spectroscopy to directly probe how IR pre-excitation impacts the UV/VIS spectrum, using the dye coumarin 6 as an example. We find that IR excitation does not simply shift the electronic absorption band but produces complex spectral changes arising from multiple vibronic transitions. Simulations reproduce the experimental spectra and reveal that dominant contributions originate from changes near the 0-0 transition rather than from a single red-shifted M-0 transition. In addition, oscillatory features in the 2D-VE spectra are observed and assigned to zero-quantum coherences between vibrational modes, demonstrating that vibrational coherences can strongly influence signal amplitudes in VIPER-type experiments. Finally, the correlation between vibrational and electronic frequencies enables the separation and analysis of molecular subensembles, as illustrated for hydrogen-bonded and free coumarin 6 in mixed solvents. These results provide a detailed microscopic picture of how vibrational excitation modifies electronic spectra and offer important insight for understanding and optimizing vibrationally promoted electronic resonance techniques.

The effect of a pencil scanning proton beam in two regions of the Bragg curve with different linear energy transfer (LET) relative to X-ray radiation on the induction of micronuclei (MN) in cytochalasin-blocked binucleate lymphocytes (CBBLs) during in vitro irradiation of human peripheral blood at doses ranging from 0 to 2.0 Gy was studied. A nonlinear dose-response relationship was observed in the dose range of 0 to 1.0 Gy. The frequency of MN in CBBLs during proton irradiation was 2 times lower than during X-rays and did not depend on the LET value. In the dose range above 1 Gy, the dose dependences were linear, the value of the relative biological effectiveness depended on LET and was equal to 0.76 before the Bragg peak, and 1.16 at the peak.

Systematically characterized the ARF family in Triticeae revealed its evolutionary expansion patterns and validated that TaARF4.1 acts as a repressor enhancing salt/alkali tolerance potentially by regulating cell wall metabolism and ROS homeostasis. Auxin response factors (ARFs) are core transcription factor families mediating auxin signaling, which not only regulate plant growth and development but also bridge the trade-off between growth and stress adaptation. However, their roles in responding to abiotic stresses-particularly salt/alkali stress, a major constraint to global wheat production-remain poorly understood in wheat (Triticum aestivum). To address this, we integrated evolutionary genomics, multi-tissue expression profiling, and functional validation across 10 Poaceae species (including wheat, rice, maize, and other Triticeae crops) to systematically identify stress-regulatory wheat ARFs (TaARFs). We identified 349 ARF members and reconstructed the evolutionary trajectory across 10 species, clarified orthologous relationships between TaARFs and rice ARFs (OsARFs), and revealed that TaARF expansion is driven by two mechanisms: ancient whole-genome duplication (WGD) conserving core ARF functions and recent gene duplication burst (RBGD) generating Triticeae-specific duplicates (e.g., TaARF4.1/4.2). GO enrichment and stress-induced expression analyses highlighted Group IV repressor ARFs (TaARF4.1/4.2/9) as candidate regulators of abiotic stress responses. Transcriptome integration across salt/alkali-treated wheat leaves and roots identified stably stress-responsive TaARFs, while functional assays confirmed TaARF4.1, as a repressor ARF with the whole-cell localization, was associated with key genes involved in stress signaling, cell wall metabolism, and reactive oxygen species (ROS) homeostasis. This study demonstrates that underutilized genome evolution data aids gene mining in complex crop genomes, providing novel genetic resources for wheat salt/alkali tolerance breeding and insights into auxin-mediated stress adaptation mechanisms.

Understanding how virus sequences are shaped by selection can inform vaccine design and transmission inference. Modeling within-host evolution to interrogate these questions requires a detailed mechanistic framework that accurately captures sequence diversification. The CD 8 + cytotoxic T-lymphocyte (CTL) response plays an important role in immune-mediated selection and can leave strong signatures in virus sequences; however, existing sequence-based within-host virus modeling frameworks do not explicitly include a human leukocyte antigen (HLA)-aware CTL response. We extended our previously published within-host sequence evolution simulator, wavess, to include an explicit CTL response, and share a method for identifying HLA-specific CTL epitopes given a founder virus sequence. We also updated the model to permit a variable recombination rate, which allows for modeling non-adjacent genes, segmented genomes, and recombination hotspots. These extensions to wavess allow for more accurate simulation of viruses and virus genes, particularly in regions of the genome where the immune response is dominated by CTLs (rather than antibodies). It also provides the foundation for investigations of how these newly-added biological mechanisms influence within-host evolution. The core of wavess is written in Python 3, with helper functions written in R. It is available at https://github.com/MolEvolEpid/wavess.

TATA-box binding protein-associated factor 15 (TAF15) is an RNA-binding protein and the primary fibrillar constituent in a subset of frontotemporal lobar degeneration (FTLD) cases. However, the molecular determinants underlying TAF15 aggregation remain unclear. Here, we show that TAF15 forms amyloid fibrils under physiological conditions and develop a cellular biosensor to monitor its propagation. Both recombinant TAF15 fibrils and pathological aggregates extracted from FTLD patient brains selectively seed TAF15 biosensor cells, demonstrating prion-like properties. The closely related protein FUS does not seed TAF15 aggregation, revealing a cross-seeding barrier, but partially incorporates into inclusions during TAF15-induced seeding, potentially explaining their pathological overlap in FTLD. Computational and peptide-based mapping identifies aggregation-prone motifs within the low-complexity domain that stabilize ex vivo fibril cores and drive TAF15 propagation. These findings establish TAF15 as an amyloid-forming, prion-like protein and define sequence determinants underlying its self-assembly, providing a mechanistic framework for FTLD-TAF15 and potential therapeutic targets.