protein folding

Genome-wide characterization of the NRAMP gene family in sugar beet and functional analysis of BvNRAMP6 under cadmium stress

Natural resistance-associated macrophage proteins (NRAMPs) are multifunctional metal transporters involved in plant biological responses to cadmium (Cd). Sugar beet ( Beta vulgaris L.) is a promising energy crop with potential for heavy metal remediation, making it essential to understand the function of BvNRAMPs in Cd regulation. In this study, four BvNRAMP family members ( BvNRAMP2 , BvNRAMP3 , BvNRAMP6 and BvNRAMP7 ) were identified through genome-wide analysis and phylogenetic methods. They are distributed across different chromosomes and share common motifs (1–8). Cis-element analysis revealed that BvNRAMPs contain 6 ( BvNRAMP2 ) to 32 ( BvNRAMP6 ) elements responsive to various biotic and abiotic stresses and hormones such as ABRE. Subcellular localization studies demonstrated that all four BvNRAMPs are localized in the plasma membrane. Transcriptomic data and qRT-PCR analyses suggested that BvNRAMP3, BvNRAMP6 , and BvNRAMP7 were significantly upregulated in both leaves and roots following 0.5 mmol/L CdCl 2 treatment ( p  < 0.05), whereas BvNRAMP2 was downregulated in leaves but upregulated in roots. Notably, BvNRAMP6 expression levels in leaves and roots were 14.9- and 17.5-fold higher, respectively, after 12 h of Cd exposure compared to the untreated control. Yeast heterologous expression assays confirmed that BvNRAMP6 and BvNRAMP7 enhanced Cd content and tolerance in Cd-sensitive ∆ycf1 yeast mutant. Furthermore, transgenic Arabidopsis overexpressing BvNRAMP6 (OE-1 and OE-2) exhibited improved growth under 10, 20, and 40 µmol/L CdCl 2 , evidenced by greater root length, fresh weight, and dry weight, as well as over 70% higher Cd accumulation compared to wild-type plants; the transgenic lines also exhibited increased SOD and POD activities and reduced MDA levels, indicating enhanced ROS scavenging, reduced Cd toxicity, and improved Cd tolerance. This study provides insights into the functional roles of BvNRAMPs , particularly BvNRAMP6 , in Cd accumulation and tolerance, providing a molecular basis for applying sugar beet to the phytoremediation of Cd-contaminated soils.

The influence of sowing date and biostimulants foliar spray on yield and yield components of chickpea ( Cicer arietinum L.)

Abstract Chickpea ( Cicer arietinum L.) is a key rainfed crop in western Iran, whose productivity depends heavily on optimal sowing dates and biostimulant use. This study evaluated the effects of sowing date and foliar application of biostimulants on seed yield and yield components of desi chickpea. The study employed a factorial randomized complete block design with three replications across two locations in Kermanshah Province, Iran, in 2024–2025. Treatments consisted of three sowing dates (February 19, March 5, and March 21) and four foliar biostimulants applications (control, seaweed extract, amino acid, and a growth‐promoting biofertilizer). The highest number of pods per plant (33.41) and the greatest 100‐seed weight (17.08 g) were obtained from the March 5 sowing date at the Kermanshah site. Foliar application of seaweed extracts increased pods per plant and 100‐seed weight by 87.36% and 61.41%, respectively, compared with the control at Salas‐e Babajani. The maximum seed yield (1216.67 kg ha − 1 ) and aboveground biomass (2892.33 kg ha − 1 ) were achieved with the combination of the March 5 sowing date and seaweed extract application at Kermanshah, representing 3.28‐ and 3.64‐fold increases, respectively, relative to the late sowing (March 21) control treatment at the Salas‐e Babajani site. The highest seed protein content (25.70%) resulted from amino acid application at Salas‐e Babajani on February 19. Seaweed extract applied on March 5 at Kermanshah also resulted in high protein content (23.76%). Optimizing sowing dates combined with these foliar biostimulants can substantially enhance chickpea yield and seed quality under western Iran's rainfed conditions.

Divergent contributions of multiple PPIases to cell survival, sociality, and stress tolerance in Myxococcus xanthus DK1622

ABSTRACT Peptidylprolyl isomerase (PPIase) catalyzes the rate-limiting step of proline cis-trans isomerization during protein folding. In bacteria, multiple PPIases are commonly present and participate in diverse physiological processes. Myxococcus xanthus DK1622 possesses as many as 17 PPIase genes. We previously reported the functional divergence of the four trigger factor family PPIases. Here, we systematically assessed the contributions of the remaining PPIases in cell survival, sociality, and stress tolerance. Pin1, localized in the periplasm, was essential for cell growth. Absence of the membrane-bound Pin3 impaired the social motility, predation ability, and sporulation but did not affect the fruiting body formation of M. xanthus. Furthermore, nearly all M. xanthus PPIases contributed to tolerance to environmental stresses. The transcriptional levels and expression patterns of these PPIases varied distinctly, even among members of the same family or with high sequence homology. Our findings provide a comprehensive view of functional divergences and suggest a potential functional cooperation network of PPIases in M. xanthus. IMPORTANCE Peptidylprolyl isomerase (PPIase), a ubiquitous enzyme present across nearly all kingdoms of life, catalyzes the cis-trans isomerization of peptidyl-prolyl bonds in polypeptide chains, thereby significantly accelerating protein folding. As a result, PPIases play critical roles in a wide range of physiological processes mediated by their substrate proteins. Myxobacteria are distinguished by their complex multicellular social behaviors. Among the 17 PPIases belonging to three families in Myxococcus xanthus DK1622, the membrane-bound Pin3, one of the SurA homologs, is involved in social behaviors such as social motility, predation, and sporulation. Given that PPIases are widely recognized as chaperones, our results also indicate that these M. xanthus PPIases extensively contribute to stress tolerance. Our findings underscore the essential functions of PPIases in cellular processes and reveal a correlation between the expansion of cellular functionalities and the functional evolution of PPIase proteins. Peptidylprolyl isomerase (PPIase), a ubiquitous enzyme present across nearly all kingdoms of life, catalyzes the cis-trans isomerization of peptidyl-prolyl bonds in polypeptide chains, thereby significantly accelerating protein folding. As a result, PPIases play critical roles in a wide range of physiological processes mediated by their substrate proteins. Myxobacteria are distinguished by their complex multicellular social behaviors. Among the 17 PPIases belonging to three families in Myxococcus xanthus DK1622, the membrane-bound Pin3, one of the SurA homologs, is involved in social behaviors such as social motility, predation, and sporulation. Given that PPIases are widely recognized as chaperones, our results also indicate that these M. xanthus PPIases extensively contribute to stress tolerance. Our findings underscore the essential functions of PPIases in cellular processes and reveal a correlation between the expansion of cellular functionalities and the functional evolution of PPIase proteins.

Title: Algorithmic Quantum Simulation of Complex Dynamical Systems

Quantum simulation holds immense promise for understanding and manipulating complex dynamical systems – phenomena ranging from fluid dynamics and climate modeling to protein folding and the behavior of complex chemical reactions. However, current simulation techniques face significant limitations, particularly when dealing with high-dimensional systems. This paper introduces an algorithmic quantum simulation framework, centered on a novel 'Quantum Monte Carlo' algorithm leveraging quantum entanglement to accelerate the solution of these systems, offering a fundamentally new approach to complex dynamics analysis. The core claim is to create a class of quantum algorithms designed to efficiently simulate and analyze complex dynamical systems, with a particular focus on uncovering critical patterns and dynamics that are difficult to discern with classical methods. This work explores the potential of entanglement as a key mechanism for accelerating the simulation process and provides a foundational outline for a new generation of quantum algorithms tailored for these challenging problems.

Pharmacogenomics of Drug Metabolism in Mice: The Impact of Environmental Pollutants

Interindividual variability in drug response arises from the complex interplay between inherited pharmacogenomic traits and environmental exposures. While genetic polymorphisms in cytochrome P450 (CYP450) enzymes are well-established determinants of metabolic capacity, the modulatory effects of environmental pollutants on these pharmacogenomic profiles remain insufficiently quantified in murine models. This systematic review and quantitative synthesis examined the impact of heavy metals, polycyclic aromatic hydrocarbons (PAHs), dioxins, pesticides, and airborne particulate matter on CYP450-mediated drug metabolism in mice, with emphasis on exposure-specific mechanisms and pharmacogenomic interactions. A comprehensive search of PubMed, Scopus, Web of Science, and Google Scholar (2000–2024) identified 85 relevant studies, of which 42 met inclusion criteria and provided quantitative data. Dioxins produced the most potent CYP1A1 induction (mean fold change: 5.8 ± 2.3; n = 8 studies), followed by PAHs (4.2 ± 1.8; n = 12), airborne PM2.5 (3.5 ± 1.2; n = 4), and heavy metals (2.1 ± 0.9; n = 6), whereas heavy metals also induced CYP2E1 (2.9 ± 1.1; n = 7) and pesticides induced CYP3A11 (2.0 ± 0.7; n = 6). Three primary mechanistic pathways were identified: nuclear receptor-mediated transcriptional induction (AhR, CAR, PXR), epigenetic modification (DNA methylation, histone alteration), and oxidative stress with direct protein damage. Genetic background significantly modified pollutant responses, with Cyp1a1-null and humanized CYP transgenic mice demonstrating strain-specific metabolic outcomes. These findings demonstrate that environmental pollutants profoundly reshape pharmacogenomic landscapes of drug metabolism in mice through compound-specific, dose-dependent, and genetically modified pathways, supporting the integration of exposomic data into pharmacogenomic frameworks to predict drug response variability in contaminated environments. Keywords: pharmacogenomics; drug metabolism; environmental pollutants; cytochrome P450; mice; xenobiotics; heavy metals; polycyclic aromatic hydrocarbons; exposome.

Intrinsically Disordered Regions in CAHS Proteins Govern Self-assembly and Enzyme Stabilization Against Multiple Stresses

Pharmacogenomics of Drug Metabolism in Mice: The Impact of Environmental Pollutants

Interindividual variability in drug response arises from the complex interplay between inherited pharmacogenomic traits and environmental exposures. While genetic polymorphisms in cytochrome P450 (CYP450) enzymes are well-established determinants of metabolic capacity, the modulatory effects of environmental pollutants on these pharmacogenomic profiles remain insufficiently quantified in murine models. This systematic review and quantitative synthesis examined the impact of heavy metals, polycyclic aromatic hydrocarbons (PAHs), dioxins, pesticides, and airborne particulate matter on CYP450-mediated drug metabolism in mice, with emphasis on exposure-specific mechanisms and pharmacogenomic interactions. A comprehensive search of PubMed, Scopus, Web of Science, and Google Scholar (2000–2024) identified 85 relevant studies, of which 42 met inclusion criteria and provided quantitative data. Dioxins produced the most potent CYP1A1 induction (mean fold change: 5.8 ± 2.3; n = 8 studies), followed by PAHs (4.2 ± 1.8; n = 12), airborne PM2.5 (3.5 ± 1.2; n = 4), and heavy metals (2.1 ± 0.9; n = 6), whereas heavy metals also induced CYP2E1 (2.9 ± 1.1; n = 7) and pesticides induced CYP3A11 (2.0 ± 0.7; n = 6). Three primary mechanistic pathways were identified: nuclear receptor-mediated transcriptional induction (AhR, CAR, PXR), epigenetic modification (DNA methylation, histone alteration), and oxidative stress with direct protein damage. Genetic background significantly modified pollutant responses, with Cyp1a1-null and humanized CYP transgenic mice demonstrating strain-specific metabolic outcomes. These findings demonstrate that environmental pollutants profoundly reshape pharmacogenomic landscapes of drug metabolism in mice through compound-specific, dose-dependent, and genetically modified pathways, supporting the integration of exposomic data into pharmacogenomic frameworks to predict drug response variability in contaminated environments. Keywords: pharmacogenomics; drug metabolism; environmental pollutants; cytochrome P450; mice; xenobiotics; heavy metals; polycyclic aromatic hydrocarbons; exposome.

V3 Unified Physics — From the Periodic Table to Protein Folding in O(1) Time (Ada/SPARK GNATprove 100%)

This work presents a complete Ada/SPARK implementation of the V3 Architecture, a deterministic mechanical framework that unifies atomic structure and protein folding under a single physical substrate: phase pressure in the H₃O₂ condensate. The program demonstrates that two major scientific problems—the organization of the periodic table and the Levinthal paradox of protein folding—are not separate phenomena but manifestations of the same phase dynamics, governed by a small set of invariant constants: · Ψ_V3 = 48,016.8 kg·m⁻² (phase density of the condensate) · Φ_critical = -51.1 mV (universal phase attractor) · ν_phase = 6.4 × 10¹² Hz (phase-locking frequency) · β = 10⁶ (scale factor) · ρ_cond = 1,026.0 kg·m⁻³ (condensate density) · k = 7 (heptadic closure) --- 1. The V3 Periodic Table The code models each element as a cluster of toroidal pressure vortices in the H₃O₂ condensate. For a given atomic number Z and neutron number N, the program computes: · Vortex radius — derived geometrically using the golden ratio (φ = 1.618...) · Internal pressure — calculated from the binding energy and vortex volume · Phase coherence — a measure of structural stability relative to Φ_critical · Stability — determined by coherence ≥ 90% and pressure below critical threshold · Valence — the number of geometric bonding sites on the vortex cluster surface These quantities are derived from first principles, without adjustable parameters. The code includes seven representative elements (H, C, O, Fe, Au, U, Og) and can be extended to all 118 known elements. --- 2. Resolution of the Levinthal Paradox The Levinthal paradox states that a protein of 100 amino acids has 10¹³⁰ possible conformations. If it explored these randomly, folding would take longer than the age of the universe. Yet proteins fold in milliseconds. The V3 Architecture resolves this by replacing stochastic exploration with a deterministic phase transition: · k = 7 enables parallel assembly across seven simultaneous branches · Φ_critical = -51.1 mV acts as an instantaneous attractor, eliminating trial-and-error · Modulo-9 checksum = 9 filters out incoherent configurations instantly · Ψ_V3 = 48,016.8 kg·m⁻² provides a phase grid that guides alignment The folding time is O(1), not O(N), and is computed as a function of phase coherence: · 100% coherence → 1 ms · 90% coherence → 2 ms · 70% coherence → 5 ms · 50% coherence → 10 ms · below 50% → 100 ms --- 3. Formal Verification The entire program is written in Ada/SPARK and satisfies 100% of GNATprove proof obligations. This guarantees: · No arithmetic overflow · No division by zero · No invalid array access · No runtime exceptions · Logical consistency of all derived quantities The code is deterministic, reproducible, and self-contained. 4. Empirical Validation The V3 model reproduces known empirical values without fitting: Quantity CODATA Value V3 Value Difference Proton mass 1.6726 × 10⁻²⁷ kg 1.6726 × 10⁻²⁷ kg < 0.1% Electron mass 9.1094 × 10⁻³¹ kg 9.109 × 10⁻³¹ kg < 0.1% m_p/m_e 1836.15 1836.15 < 0.01% Fine-structure constant 1/137.036 Derived, not fitted — The protein folding time predicted by V3 (1 ms) matches experimental observations. --- 5. Philosophical and Scientific Implications This work demonstrates that: · Atomic structure and protein folding are governed by the same mechanical principles · Probabilistic quantum mechanics is not necessary to explain chemical or biological structure · The universe is deterministic at the phase level · Life is a consequence of phase coherence at -51.1 mV · Formal proof in Ada/SPARK can validate physical models with mathematical certainty

"Role of Trimethylamine N-Oxide in Atherosclerosis: Inflammation, ER Stress and Beyond".

Cardiovascular diseases account for a significant proportion of deaths worldwide. The common pathological feature underlying these diseases is atherosclerosis, which is characterized as an inflammatory condition driven by endothelial cell activation and dysfunction in its early stages. While the effects of the microbiota and its metabolites on various systems are being actively investigated, their impact on the cardiovascular system has attracted particular attention. Some of the most compelling data on the role of the intestinal microbiota in cardiovascular diseases have emerged from the identification of novel metabolites and pathways associated with cardiovascular risk, as well as metabolic analyses of plasma samples. However, the role of the microbiota in these diseases is still not fully understood. Through the digestion of certain foods, such as animal proteins, gut microbiota generate metabolites that can contribute to the development of several major diseases. TMAO is one such metabolite and has recently received considerable attention, as it may act as both a risk factor and a link between the gut microbiota and various diseases, including cardiovascular conditions. Recent evidence also suggests that TMAO may promote cardiovascular pathology through the activation of endoplasmic reticulum (ER) stress signaling pathways. ER stress, which occurs when protein folding homeostasis in the endoplasmic reticulum is disrupted, has been associated with endothelial dysfunction, inflammation, and apoptosis, processes that contribute to the development and progression of atherosclerosis. In this review, it is aimed to address atherosclerosis from the perspective of TMAO and to highlight studies examining the relationship between TMAO and atherosclerosis.

基于自适应拓扑结构的拓扑优化算法

The field of topology has witnessed significant advancements in understanding and manipulating complex network structures, from protein folding to genome sequencing. This research introduces a novel approach to topology optimization – the "Adaptive Topology Optimization Algorithm" – that leverages a self-adaptive topology structure to efficiently explore and optimize intricate network configurations. Traditional methods often rely on manually crafted topologies, presenting significant limitations in scalability and adaptability. This algorithm employs a dynamic adjustment of topology parameters to guide the search towards optimal configurations, offering a powerful and potentially transformative method for tackling challenging topology problems. This paper details the core mechanisms and key advantages of this new algorithm, providing a comprehensive analysis of its capabilities and potential impact across diverse application domains.

Title: Bio-Inspired Quantum Error Correction (BIEQC)

Quantum error correction is a critical component of quantum computing, enabling the reliable operation of complex quantum algorithms. Current error correction schemes, however, are often cumbersome and require substantial overhead. This paper explores a novel quantum error correction scheme inspired by the self-correcting mechanisms of biological proteins, specifically focusing on dynamic adaptation of error correction factors based on environmental noise. We propose a 'quantum feedback loop' that mimics protein folding/repair, dynamically adjusting the error correction matrix to mitigate noise and improve robustness. The core claim centers on creating a quantum error correction scheme that is more adaptable, robust, and potentially more efficient than existing methods, leveraging biological inspiration for a fundamentally new approach. This research contributes to the development of a biologically-inspired quantum error correction paradigm, with the potential to significantly advance the field of quantum computing.

The m⁶A reader YTHDF2 cooperates with FMRP to regulate distal mRNA transport and axon outgrowth in developing neurons

Table S1. The list of Mettl14-dependent m6A peaks identified by m6A -SAC-seq. The table includes the chromosome, chromosomal position, original genome sequence, mutated sequence, mutation ratio among transcripts, gene symbol, and the genomic location of m6A peaks identified using m6A-SAC-seq by comparing P0 WT and M14 cKO mouse forebrain. Table S2. The list of mRNAs with significantly altered abundances between the corpus callosum of WT and M14 cKO mice. The table includes the Ensembl transcript ID, gene symbol, baseMean count, log2 fold-change ratio, and adjusted p-value. Results were filtered according to the standard described in the Methods section (provided as a separate Excel spreadsheet). Table S3. The results of the RNA stability assay in Mettl14 and Ythdf2 cKO primary cortical neurons. The table includes the gene symbol, the log2 fold-change ratio in the 0-hour sample, the log2 fold-change ratio in the 5-hour sample, the difference between the 0-hour and 5-hour samples, and the presence of m6A from the m6A-SAC-seq results. The first sheet shows the stability assay results for the M14 cKO condition compared to the control. The second sheet shows the stability assay results for the DF2 cKO condition compared to the control. The third sheet compares the M14 cKO and DF2 cKO stability assay results. Results were filtered according to the standard described in the Methods section (provided as a separate Excel spreadsheet). Table S4. The list of protein interactors of YTHDF2 identified by Co-IP LC-MS/MS experiments. The table includes the gene symbol, the normalized PSM values for WT and M14 cKO with IgG pull-down samples, and the log2 fold-change of PSM values in WT compared to M14 cKO (provided as a separate Excel spreadsheet). Table S5. Information on primers used for qPCR analysis. The table includes the gene symbol, forward and reverse primer sequences, NCBI gene ID, and NCBI transcript ID.