Service members with traumatic brain injury are at approximately two- to four-fold higher risk of Alzheimer's disease or related dementias than those without such an injury, with risk increasing with injury severity. The amyloid/tau/neurodegeneration biomarker framework treats amyloid, tau, and neurodegeneration as independent axes but omits astroglial injury, despite evidence that reactive astrogliosis (indexed by glial fibrillary acidic protein, GFAP) must be elevated for cognitive decline to occur in amyloid-positive individuals. Total GFAP immunoassays aggregate intact protein with multiple calpain- and caspase-cleaved proteoforms, blurring the biological signal. We compared a calpain-cleaved GFAP neoepitope, the glial fibrillary acidic protein neoepitope (neoGFAP™), against total GFAP across the full traumatic brain injury—mild cognitive impairment—Alzheimer's disease continuum in Veterans using a two-stage plasma-to-cerebrospinal-fluid biomarker approach. A plasma triage gate combining phosphorylated tau 217 and amyloid beta 42 was applied to 367 unique subjects; a cerebrospinal-fluid benchmarking cohort of 57 subjects (controls, chronic blast traumatic brain injury, mild cognitive impairment, and Alzheimer's disease) received head-to-head neoGFAP and total GFAP measurement. In the whole benchmarking cohort, neoGFAP discriminated mild cognitive impairment plus Alzheimer's disease from non-Alzheimer subjects with an area under the receiver-operating-characteristic curve of 0.81 versus 0.73 for total GFAP, a trend-level advantage that did not reach nominal significance. Within the gate-positive, amyloid-committed subset of 23 subjects, neoGFAP dominance became significant by McNemar's exact test (six discordant subjects favored neoGFAP, none the reverse). Across diagnostic contrasts, neoGFAP outperformed total GFAP for Alzheimer's disease versus control and, importantly for Veterans, for mild cognitive impairment versus chronic blast-exposed Veterans without cognitive impairment. In chronic blast injury, neoGFAP was paradoxically depleted relative to controls, consistent with tissue sequestration of aggregated proteoform fragments. Unbiased proteomic profiling confirmed coordinated elevation across astrocytic, neuronal, mitochondrial, and microglial compartments. An exploratory subject-level reclassification improved accuracy from 71.1 percent using plasma alone to 79.5 percent with added cerebrospinal-fluid markers and age. In a same-cohort ProQuantum™ replication (n=57), CSF neoGFAP preserved its discrimination advantage over total GFAP for MCI+AD versus non-AD (AUROC 0.76 vs 0.72; cross-platform Spearman ρ=0.84), while plasma neoGFAP achieved AUROC 0.90, comparable to pTau217 (0.92) and exceeding Aβ42/40 (0.84). In this small sample, neoGFAP™ is a superior proteoform-resolved diagnostic and prognostic biomarker across the continuum and supports adding an astroglial-proteoform axis to amyloid/tau/neurodegeneration biomarker frameworks in high-risk populations.
William E. Haskins, Kevin Wang, Guangzheng Cai et al.· medRxiv· 0 citations
This preprint introduces the molecular and biochemical extension of The Bell TowerArchitecture. By taking the asymptotic limit (ε → 0) of the discrete lattice Z^3, we define acontinuous rigid field Φ(z) governed by Weierstrass infinite products and Mittag-Leffler expansions. This geometric framework replaces traditional Linear Combination of Atomic Orbitals (LCAO) approximations and eliminates artificial electron-overlap singularities. When mapped onto fermionic probability density |ψ|^2 , the exact Cartesian bundle constrainty = kx + 1/(2k) identically vanishes the non-linear vortex stretching term, (ω · ∇)u ≡ 0,establishing absolute topological protection. Numerical extraction on a 150 × 150 computational mesh confirms a peak core density |ψ|^2 max = 0.9974, a regularized external vacuum integrity |ψ|^2 min = 7.7413 × 10−208, and a non-latent geometric restoring gradient of 5.9792.This structural mechanism provides a deterministic solution to Levinthal’s Paradox in protein folding, translating biochemical efficiency into an intrinsic property of a rigid Hilbert space
Silvio Gabbianelli· Zenodo (CERN European Organi...· 0 citations
Abstract Nitrogen-containing organic compounds (NOCs) are key characteristic components in particulate matter (PM) from household solid fuel combustion, yet their personal exposure and class-dependent toxicity remain poorly characterized. We compared size-resolved personal exposure to particulate nitrated phenols (NPs) and nitro-PAHs (n-PAHs) among rural users of clean coal (CC), raw coal chunk (RCC), and biomass (BB), and evaluated representative compounds in A549 cells. Biomass users had the highest PM2.5-bound n-PAH exposure (up to 11.5-fold above clean coal), while NPs varied little across fuel groups (≤1.3-fold); CC and RCC users showed comparable PM2.5-bound NPs concentrations (64.0 ± 12.1 vs 57.4 ± 25.8 ng m–3, P = 0.545). n-PAHs exhibited greater cytotoxicity with lower IC50 values, whereas NPs produced stronger NF-κB activation by larger increases in p-IκB-α and COX-2 expression. Physicochemical descriptor analysis and molecular docking suggested that divergent biological responses may be partly attributable to differing hydrophobicity and protein interaction modes: hydrophobic contacts for n-PAHs, polar and hydrogen-bonding interactions for NPs. These results demonstrate clean heating transitions better mitigate n-PAH than NP exposure. NPs and n-PAHs differ substantially in cytotoxicity and NF-κB-mediated inflammation, providing a case study linking real-world personal exposure monitoring to molecular toxicology for health-risk-based prioritization of combustion-derived PM constituents.
Rong Feng, Hongmei Xu, Zhenxing Shen et al.· Environmental Science & Tech...· 0 citations
Researchers at Osaka University in Japan and the University of Queensland in Australia have published a review analysing the enormous gap between theory and measured values that confronts luminescence nanothermometry, the technique used to measure temperature inside cells. The authors argue that the concept of temperature itself remains valid in statistical-thermodynamic terms even at the 10 nm scale, but report that the so-called "10⁵ gap issue", in which measured values (~1 K) run 100,000 times larger than calculated ones (~10 μK), remains unresolved. Attempts have been made to narrow the gap by assigning a lower thermal conductivity to intracellular membranes and by taking Kapitza resistance into account, but the authors call for more refined measurement methods alongside a theoretical rethink before the phenomenon can be fully explained. [Quantum Biology Society] Pinning down quantitatively when, where and how much heat is generated at the cellular level is a central problem in understanding how organisms maintain body temperature and run their metabolism. As luminescence nanothermometry has advanced, using fluorescent proteins, quantum dots and nanodiamonds among other probes, striking results have been reported: stable temperature differences of more than 1 K between organelles even in unstimulated cells, and mitochondrial temperatures that may possibly rise as high as 323 K (about 50 °C) under full activation of respiration in human embryonic kidney 293 cells and primary skin fibroblasts. A review by Madoka Suzuki of Osaka University and Taras Plakhotnik of the University of Queensland, published in Biophysical Reviews in 2020, takes on the fundamental dilemma sitting behind those spectacular observations. ■ Is the Concept of Temperature Valid at the Nanoscale? Before weighing the reliability of nanothermometers, the authors first examine whether temperature, a macroscopic state function, can even be defined in the microscopic world of the nanometre scale. Statistical mechanics says that the smaller the system, the more severe its temperature fluctuations become. Molecular dynamics simulations put the temperature fluctuation of a single amino acid residue at around 70 K, and the textbook formula gives the same figure for a spherical volume of water with a radius of 0.25 nm. But the characteristic correlation time of these fluctuations is extremely short: roughly 15 ps for a spherical region of radius 1.5 nm in water, and about 12 ns for a nanodiamond of radius 50 nm. At the 10 nm scale the fluctuations run on the order of 1 K, with a characteristic time on the order of 0.1 ns. Since real measurement times are far longer than this, random temperature fluctuations average out. The authors put a number on it: the thermodynamically limited noise floor for a 50 nm thermometer is a few μK s^1/2, more than three orders of magnitude below the best experimental figure achieved so far. The upshot is that in aqueous conditions and with luminescent temperature probes, the concept of temperature holds even at the 10 nm scale, and thermal fluctuation is not what limits present-day nanothermometry. ■ The Heart of the Contradiction: The 10⁵ Gap Issue The hardest problem in this field is the gap between calculation and measurement that refuses to close. The calculation: when cells are assumed to have the thermal conductivity of water and the heat equation is applied, the rise in whole-cell temperature from a local heat source comes out very small. Suzuki's own group calculated that whole-cell temperature in HeLa cells could rise by only 10 μK (0.00001 K) if the sarco/endoplasmic reticulum Ca²⁺-ATPase (Serca) were solely responsible for the temperature changes measured on Ca²⁺ shock. The measurement: Yang and colleagues measured a local temperature rise of about 1 K in the NIH3T3 cell line using quantum-dot nanothermometry. Yet accounting for that rise theoretically would require a heat source of about 1 μW or more, a figure that appears to be three orders of magnitude larger than what has been determined in stimulated brown adipocytes, cells known for generating heat. The name for this 100,000-fold (10⁵) discrepancy comes from a 2015 paper by Suzuki's group, the review's first author, and it has been the subject of fierce debate ever since, running through a published exchange between Baffou's group, which set out the critique, and researchers working with fluorescent thermometers. ■ Cross-Checking With Non-Luminescent Probes, and Rethinking Thermal Conductivity Could the fluorescent thermometers be responding to intracellular variables other than temperature, such as viscosity, pH or ionic strength, and producing an artefact? Cross-checks with non-luminescent probes: the authors point to significant temperature rises observed with probes working on entirely different principles. Bimetal microcantilevers registered about 0.2 K in stimulated brown adipocytes. Micro-thermocouple arrays inside a thermally stabilised system detected frequent fluctuations of about 60 mK and, in one detection area, a continuous elevation of up to 285 mK, while other areas stayed stable. A microscale thermocouple probe detected rapid rises of about 7.5 K near mitochondria in neurons of the sea slug Aplysia californica when the cells were stimulated with a proton uncoupler. Given this variety of probes and methods, the authors conclude that it may be unnecessary to decide that the temperature increase is unmeasurable in individual cells. Thermal conductivity and Kapitza resistance: one attempt to narrow the gap has been to question the thermal conductivity used in the calculations. Bastos and colleagues measured the thermal conductivity of a single lipid bilayer experimentally at about 0.2 W m⁻¹ K⁻¹ at 300 K, only a third that of water. Bringing in Kapitza resistance, the thermal resistance at the boundary between two different materials, the authors' modelling brings the average effective thermal conductivity inside a cell down to around 0.1 W m⁻¹ K⁻¹, roughly six times smaller than water. ■ Significance and Open Questions Resetting thermal conductivity to a lower value to reflect the complexity of the cell's interior does close some of the distance between calculation and measurement, but nowhere near enough to fill a 100,000-fold gap. The authors put it plainly: the gap still remains although it has narrowed, and they suggest this may give some ground for optimism about eventually closing it. The review settles that the concept of temperature stays physically valid down to the 10 nm scale, while summing up coolly the divide between theory and experiment that the field now faces. Temperature is more than an index of heat. It shifts chemical equilibria, affects flows driven by electrochemical gradients, and has been shown to drive directional motion of particles and to induce the accumulation of nucleotides and lipids, which makes it a core variable in the metabolism of living things. The authors conclude that resolving the 10⁵ dilemma will require approaching the gap from both sides at once: refining the theoretical estimates as the complexity of cellular processes becomes better understood, and developing new measurement methods that are more accurate and less susceptible to artefacts. #IntracellularTemperature #Nanothermometry #LuminescenceNanothermometry #FiveOrdersGap #ThermalConductivity #KapitzaResistance #ThermalFluctuations #StatisticalMechanics #Nanodiamond #ODMR #Thermogenesis #Mitochondria #Review #QuantumBiology #BiophysicalReviews Source (Biophysical Reviews, open access): https://doi.org/10.1007/s12551-020-00683-8 Commentary from the sceptical side (How hot are single cells?, free): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7398142/ Perspective defending the measurements (2021, free): https://pmc.ncbi.nlm.nih.gov/articles/PMC8660847/
inquantio· Zenodo (CERN European Organi...· 0 citations
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Abstract Digital computers have reshaped scientific practice, moving working scientific knowledge from printed texts into algorithms, simulations, and models. Advances in artificial intelligence (AI) are now accelerating that shift, progressing science in areas from protein folding to climate modelling, and raising the prospect of a further transformation in how science is done. With growing hype around the field, there is a risk that inflated claims about AI’s potential obscure both its current limitations and its longer-term possibilities. This paper explores how AI contributes to science, introducing a framework organised around task capabilities, scientific workflow integration, and domain constraints. It uses that framework to open wider questions about the role of AI in scientific discovery. These include: Is scientific knowledge constructed and used by AI agents considered scientific understanding if it is impenetrable to humans, or does scientific understanding refer to an activity that is intrinsically human? What technical advances are needed to move AI beyond pattern matching toward causal reasoning? And what institutional changes are needed to support responsible AI adoption? How researchers and policymakers engage with these questions will shape whether AI accelerates progress within existing scientific paradigms or catalyses the generation of new forms of scientific knowledge. This paper marks the opening of a call for papers from RSS Data Science and AI, which invites contributions that take up these and related questions from multiple perspectives.
Kyle Cranmer, Neil D. Lawrence, Jessica K Montgomery et al.· RSS Data Science and Artific...· 0 citations
A substantial fraction of the Mycobacterium tuberculosis proteome remains functionally uncharacterised. Rv1025, a 155-residue protein carrying the domain of unknown function DUF501 (Pfam PF04417), is essential by transposon mutagenesis and vulnerable by CRISPR interference, an attractive but neglected drug target, yet has never been functionally described. The family (4,370 proteins, no Gene Ontology term, no solved structure) is uncharacterised across all organisms and essential in three Actinobacterial genera. A Foldseek search of the AlphaFold model against complete structural databases finds no significant homolog, indicating a novel fold. The operon eno-divIC-Rv1025-ppx2 is conserved across the Actinobacteria phylum, yet AlphaFold-Multimer finds no direct complex between Rv1025 and its neighbour DivIC. Instead, conservation across 8,700 homologous sequences reveals a near-invariant Cys113-His115-Glu59 cluster forming a pocket. Holo AlphaFold3 predictions with Zn, Fe and Mn confidently place a divalent metal on this triad at 2.25-2.47 A; mutating the triad relocates the metal, and an independent backbone-geometry predictor recovers the same site, confirming specificity. The triad is universal across the family: present in all 1,472 near-complete bacterial sequences of the Pfam alignment, with no non-conservative substitution among the 2,228 sequences examined, a defining feature of bacterial DUF501 rather than a mycobacterial peculiarity. We propose that DUF501 is a metal-binding protein and candidate metalloenzyme, the first functional hypothesis for this family, whose conserved, essential metal pocket is a promising drug target. As the predictions build on a conservation-defined site within a fully computational study, they are supportive rather than proof of metal occupancy and warrant experimental validation.
Christophe Guyeux· bioRxiv (Cold Spring Harbor...· 0 citations
Quantum-driven constraint on complex systems aims to accelerate solution processes by dynamically adjusting constraint parameters. This paper explores the potential of quantum annealing and variational quantum eigensolver (VQE) to optimize these parameters. The core claim is to implement an algorithm that dynamically adjusts constraint parameters on complex systems (e.g., protein folding, DNA sequencing) to achieve optimal solution speed and accuracy. The approach leverages quantum annealing for its ability to escape local optima and VQE for efficient exploration of the solution space. This research investigates the feasibility and potential advantages of employing quantum computing for optimization tasks within complex systems, offering a novel methodology for enhancing computational efficiency.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Researchers at Osaka University in Japan and the University of Queensland in Australia have published a review analysing the enormous gap between theory and measured values that confronts luminescence nanothermometry, the technique used to measure temperature inside cells. The authors argue that the concept of temperature itself remains valid in statistical-thermodynamic terms even at the 10 nm scale, but report that the so-called "10⁵ gap issue", in which measured values (~1 K) run 100,000 times larger than calculated ones (~10 μK), remains unresolved. Attempts have been made to narrow the gap by assigning a lower thermal conductivity to intracellular membranes and by taking Kapitza resistance into account, but the authors call for more refined measurement methods alongside a theoretical rethink before the phenomenon can be fully explained. [Quantum Biology Society] Pinning down quantitatively when, where and how much heat is generated at the cellular level is a central problem in understanding how organisms maintain body temperature and run their metabolism. As luminescence nanothermometry has advanced, using fluorescent proteins, quantum dots and nanodiamonds among other probes, striking results have been reported: stable temperature differences of more than 1 K between organelles even in unstimulated cells, and mitochondrial temperatures that may possibly rise as high as 323 K (about 50 °C) under full activation of respiration in human embryonic kidney 293 cells and primary skin fibroblasts. A review by Madoka Suzuki of Osaka University and Taras Plakhotnik of the University of Queensland, published in Biophysical Reviews in 2020, takes on the fundamental dilemma sitting behind those spectacular observations. ■ Is the Concept of Temperature Valid at the Nanoscale? Before weighing the reliability of nanothermometers, the authors first examine whether temperature, a macroscopic state function, can even be defined in the microscopic world of the nanometre scale. Statistical mechanics says that the smaller the system, the more severe its temperature fluctuations become. Molecular dynamics simulations put the temperature fluctuation of a single amino acid residue at around 70 K, and the textbook formula gives the same figure for a spherical volume of water with a radius of 0.25 nm. But the characteristic correlation time of these fluctuations is extremely short: roughly 15 ps for a spherical region of radius 1.5 nm in water, and about 12 ns for a nanodiamond of radius 50 nm. At the 10 nm scale the fluctuations run on the order of 1 K, with a characteristic time on the order of 0.1 ns. Since real measurement times are far longer than this, random temperature fluctuations average out. The authors put a number on it: the thermodynamically limited noise floor for a 50 nm thermometer is a few μK s^1/2, more than three orders of magnitude below the best experimental figure achieved so far. The upshot is that in aqueous conditions and with luminescent temperature probes, the concept of temperature holds even at the 10 nm scale, and thermal fluctuation is not what limits present-day nanothermometry. ■ The Heart of the Contradiction: The 10⁵ Gap Issue The hardest problem in this field is the gap between calculation and measurement that refuses to close. The calculation: when cells are assumed to have the thermal conductivity of water and the heat equation is applied, the rise in whole-cell temperature from a local heat source comes out very small. Suzuki's own group calculated that whole-cell temperature in HeLa cells could rise by only 10 μK (0.00001 K) if the sarco/endoplasmic reticulum Ca²⁺-ATPase (Serca) were solely responsible for the temperature changes measured on Ca²⁺ shock. The measurement: Yang and colleagues measured a local temperature rise of about 1 K in the NIH3T3 cell line using quantum-dot nanothermometry. Yet accounting for that rise theoretically would require a heat source of about 1 μW or more, a figure that appears to be three orders of magnitude larger than what has been determined in stimulated brown adipocytes, cells known for generating heat. The name for this 100,000-fold (10⁵) discrepancy comes from a 2015 paper by Suzuki's group, the review's first author, and it has been the subject of fierce debate ever since, running through a published exchange between Baffou's group, which set out the critique, and researchers working with fluorescent thermometers. ■ Cross-Checking With Non-Luminescent Probes, and Rethinking Thermal Conductivity Could the fluorescent thermometers be responding to intracellular variables other than temperature, such as viscosity, pH or ionic strength, and producing an artefact? Cross-checks with non-luminescent probes: the authors point to significant temperature rises observed with probes working on entirely different principles. Bimetal microcantilevers registered about 0.2 K in stimulated brown adipocytes. Micro-thermocouple arrays inside a thermally stabilised system detected frequent fluctuations of about 60 mK and, in one detection area, a continuous elevation of up to 285 mK, while other areas stayed stable. A microscale thermocouple probe detected rapid rises of about 7.5 K near mitochondria in neurons of the sea slug Aplysia californica when the cells were stimulated with a proton uncoupler. Given this variety of probes and methods, the authors conclude that it may be unnecessary to decide that the temperature increase is unmeasurable in individual cells. Thermal conductivity and Kapitza resistance: one attempt to narrow the gap has been to question the thermal conductivity used in the calculations. Bastos and colleagues measured the thermal conductivity of a single lipid bilayer experimentally at about 0.2 W m⁻¹ K⁻¹ at 300 K, only a third that of water. Bringing in Kapitza resistance, the thermal resistance at the boundary between two different materials, the authors' modelling brings the average effective thermal conductivity inside a cell down to around 0.1 W m⁻¹ K⁻¹, roughly six times smaller than water. ■ Significance and Open Questions Resetting thermal conductivity to a lower value to reflect the complexity of the cell's interior does close some of the distance between calculation and measurement, but nowhere near enough to fill a 100,000-fold gap. The authors put it plainly: the gap still remains although it has narrowed, and they suggest this may give some ground for optimism about eventually closing it. The review settles that the concept of temperature stays physically valid down to the 10 nm scale, while summing up coolly the divide between theory and experiment that the field now faces. Temperature is more than an index of heat. It shifts chemical equilibria, affects flows driven by electrochemical gradients, and has been shown to drive directional motion of particles and to induce the accumulation of nucleotides and lipids, which makes it a core variable in the metabolism of living things. The authors conclude that resolving the 10⁵ dilemma will require approaching the gap from both sides at once: refining the theoretical estimates as the complexity of cellular processes becomes better understood, and developing new measurement methods that are more accurate and less susceptible to artefacts. #IntracellularTemperature #Nanothermometry #LuminescenceNanothermometry #FiveOrdersGap #ThermalConductivity #KapitzaResistance #ThermalFluctuations #StatisticalMechanics #Nanodiamond #ODMR #Thermogenesis #Mitochondria #Review #QuantumBiology #BiophysicalReviews Source (Biophysical Reviews, open access): https://doi.org/10.1007/s12551-020-00683-8 Commentary from the sceptical side (How hot are single cells?, free): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7398142/ Perspective defending the measurements (2021, free): https://pmc.ncbi.nlm.nih.gov/articles/PMC8660847/
inquantio· Zenodo (CERN European Organi...· 0 citations
Chironomids are abundant aquatic macroinvertebrates with known pollutant tolerance, but the molecular effects of chlorantraniliprole (CAP) remain unclear. In this study, we exposed Propsilocerus akamusi larvae to LC10 and LC50 of CAP, sampled at 48 h and 144 h, and integrated biochemical assays, metabolomics, and transcriptomics to profile stress responses. Our results showed that CAP elevated antioxidant enzymes and protein carbonyls, indicating severe oxidation, especially at LC50. At 48 h, LC10 activated JNK-mediated antioxidative and drug metabolism pathways, whereas LC50 altered glycolysis, cofactor biosynthesis, and fatty acid metabolism. At 144 h, LC10 enriched proteasome and oxidative phosphorylation pathways; chaperones PaHsp70 and PaHsp90 were upregulated by 4.14- and 2.08-fold, respectively, and were negatively correlated with lipid and carbohydrate metabolites, indicating a metabolic shift toward protein repair. In contrast, LC50 CAP triggered protein processing in the endoplasmic reticulum (ER) and TCA cycle dysregulation, with upregulation of PaCalreticulin linked to energy crisis markers, reflecting severe energy collapse. After knockdown of PaHsp70, the survival rates of chironomid larvae exposed to LC10 and LC50 CAP significantly decreased from 80.8% to 65.8% and from 43.3% to 28.3%, respectively. Collectively, our results revealed that low CAP concentrations triggered early detoxification followed by proteasome- and Hsp-mediated strategies to sustain protein homeostasis whereas high concentrations directly disrupted core metabolism and ultimately caused energy collapse and lethal ER stress in chironomid larvae. These findings provide mechanistic insights into the chronic effects of CAP on aquatic insects.
Jiani Li, Wei Chen, Jian Mao et al.· Animals· 0 citations
Background: Pathogenesis-related (PR) proteins, primarily thaumatin-like proteins (TLPs) and chitinases, are the principal cause of protein haze formation in white wines, increasing bentonite requirements and affecting winemaking efficiency. However, evaluating their spatial variability before harvest remains challenging because conventional analytical methods are destructive, labor-intensive, and spatially limited. Methods: This study developed a non-destructive framework to predict the accumulation of PR proteins in Vitis vinifera cv. Chardonnay and Sauvignon Blanc by integrating multitemporal UAV-derived multispectral imagery with stem water potential (Ψstem). Vegetation indices and physiological measurements were acquired throughout berry development over two growing seasons. Elastic Net, XGBoost, and CatBoost models were developed using the 2023 growing season as the calibration dataset through 20 independent jackknife training iterations, with five-fold cross-validation for hyperparameter optimization and an internal 80/20 split used exclusively for early stopping. The models were subsequently externally validated using the independent 2024 growing season. Model interpretation was performed using SHAP to identify influential predictors of model predictions. Results: CatBoost provided the most consistent predictive performance across response variables and was therefore selected for spatial prediction. SHAP analysis revealed cultivar-specific predictor hierarchies, with GNDVI at harvest dominating predictions in Chardonnay, whereas multitemporal NDVI variables were the most influential predictors in Sauvignon Blanc. Stem water potential acquired during Berry Filling II and pre-harvest consistently contributed to model performance in both cultivars, highlighting the importance of late-season physiological conditions. Spatial prediction maps revealed marked intra-vineyard heterogeneity in PR protein accumulation, identifying vineyard sectors with contrasting predicted protein concentrations. Conclusions: Integrating multitemporal UAV multispectral imagery, stem water potential, and explainable machine learning provides an accurate and interpretable framework for predicting the accumulation of pathogenesis-related proteins before harvest. This approach expands the application of remote sensing from conventional assessments of vine vigor to the prediction of biochemical traits directly associated with wine protein stability, supporting targeted sampling, selective harvesting, and more efficient bentonite management in precision viticulture.
Adrián Vera-Esmeraldas, Carlos Valle, Mauricio Galleguillos et al.· Remote Sensing· 0 citations
Eukaryotic genomes are organized into chromatin, a highly compact structure in which DNA is packaged into nucleosomes. Nucleosome formation, where DNA is wrapped around histone proteins, is essential for genome stability. This compaction protects DNA from damage and regulates accessibility of genes. Nucleosomes must be disassembled and reassembled during DNA replication and repair. These processes require precise regulation of histone folding, transfer, and deposition by a diverse network of histone chaperones. Chromatin assembly factor 1 (CAF-1) is a conserved histone chaperone that specifically deposits newly synthesized histones during replication-coupled and repair-coupled nucleosome assembly. The sliding clamp proliferating cell nuclear antigen (PCNA) serves as a regulatory scaffold during these processes by recruiting CAF-1 and many other proteins to sites of DNA replication and repair. Recent structural and biochemical studies have revealed increasingly complex mechanisms underlying PCNA-mediated CAF-1 recruitment, involving multiple protein interaction motifs, DNA-binding domains, and regulatory mechanisms that ensure efficient nucleosome assembly. This review summarizes current advances in understanding the molecular mechanisms by which human and yeast CAF-1 complexes are recruited to sites of DNA synthesis and how CAF-1 function is coordinated with other histone chaperones during replication and repair. These studies have provided important insights into how cells coordinate DNA metabolism with epigenome maintenance to preserve genome integrity.
Ian Hall, Carly A. Nowoj, Lynne M. Dieckman· Biomolecules· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
