Biophysical reviews最新文献

Recurrent neural networks are frequently studied in terms of their information-processing capabilities. The structural properties of these networks are seldom considered, beyond those emerging from the connectivity tuning necessary for network training. However, real biological networks have non-contingent architectures that have been shaped by evolution over eons, constrained partly by information-processing criteria, but more generally by fitness maximization requirements. Here, we examine the topological properties of existing biological networks, focusing in particular on gene regulatory networks in bacteria. We identify structural features, both local and global, that dictate the ability of recurrent networks to store information on the fly and process complex time-dependent inputs.

Magnesium sulfate (MgSO₄) is a therapeutically versatile agent used across various medical conditions. This review integrates experimental and computational findings to elucidate the clinical, cellular, molecular, and electronic mechanisms underlying MgSO₄'s therapeutic effects, focusing on its antioxidant properties. MgSO₄ remains the gold standard treatment for preeclampsia and eclampsia, preventing seizures and mitigating oxidative damage. In preterm birth, it offers fetal neuroprotection, although its efficacy as a tocolytic agent is limited. MgSO₄ also shows promise in treating respiratory conditions, notably severe asthma, where it acts as a bronchodilator. Its applications extend to anesthesia, pain management, and cardiac arrhythmias, reflecting its diverse pharmacological actions. Advanced computational methods, including molecular dynamics simulations and quantum chemistry calculations, have revealed how MgSO₄ interacts with cell membranes and neutralizes hydroxyl radicals. These studies suggest that MgSO₄'s antioxidant effects stem from its ability to stabilize membrane structures and modulate electron transfer processes. The therapeutic effects are mediated through multiple pathways, including calcium channel modulation, NMDA receptor antagonism, and anti-inflammatory mechanisms. Although generally safe, MgSO₄ requires careful monitoring due to its narrow therapeutic window. Future research should focus on precision dosing strategies, innovative delivery systems, and expanded therapeutic applications. A comprehensive understanding of MgSO₄'s molecular mechanisms and clinical applications will further optimize its therapeutic use.

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Thick filaments isolated from various sources, most frequently skeletal and cardiac muscles, have been studied, but several aspects of their behavior remain to be clarified. Myosin II is the principal component of these filaments. A "traditional" interacting-heads motif (IHM) has been observed in isolated thick filaments. In this motif, the two heads of the myosin II molecule interact and are stuck to the backbone of the filaments. Another aspect, the super-relaxed state (SRX state), has been described in situ, in relaxed demembranated muscle fibers and myofibrils. It has frequently been claimed that the IHM and the SRX state are closely related. Some authors still consider this relationship valid, but this view is now broadly called into question. These two phenomena occur in very different conditions, making it difficult to determine if and how they are related. For example, macromolecular crowding is a characteristic feature in situ (regardless of interfilament spacing), but not in the conditions in which the "traditional" IHM has been observed. Recent studies in situ have attempted to resolve this problem, but some of the reported findings conflict. Moreover, the association of other proteins with the myosin filaments in situ increases thick filament complexity. Experimental conditions may affect the results obtained but the consideration of long-overlooked data would help to prevent erroneous interpretations. For instance, neither the absence (EM studies) or presence (in situ studies) of cell-associated water nor electrical charges are taken into account in any of the published studies in this domain and the omission of these two parameters could lead to contradictory conclusions. My principal objective here is to provide a brief overview (with a limited number of illustrative references) of the increasing complexity of our understanding of thick filaments over the years, particularly as concerns the weak coupling or absence of coupling between the IHM and the SRX state (recent findings that may be difficult to interpret).

This Editorial introduces the contents of Volume 17, Issue 1 of Biophysical Reviews, the official journal of the International Union for Pure and Applied Biophysics (IUPAB). A major highlight of the Issue is the announcement of the winner of the 2025 Michéle Auger Award for Young Scientists' Independent Research. The broad scope of the articles in the Issue and the geographically widespread locations of the contributing authors of the reviews in the Issue mirror the goals of IUPAB, namely to organize worldwide advancements, co-operation, communication, and education in biophysics.

Hydrogen peroxide (H₂O₂) is a key reactive oxygen species involved in cellular redox signaling and oxidative stress. Due to its polar nature, its transport across membranes is regulated by aquaporins (AQPs), membrane channels traditionally known for H₂O transport. Certain AQPs, known as peroxiporins, facilitate selective H₂O₂ permeation, playing critical roles in mantaining redox homeostasis. This review summarizes insights from molecular dynamics (MD) simulations into the mechanisms of H₂O₂ transport through AQPs. Key structural regions, such as the selectivity filter (SF) and NPA motif, influence H₂O₂ permeation, with energy profiles revealing differences from H₂O transport. While molecular mimicry suggests similarities in the movement of H₂O and H₂O₂, specific interactions and energetic barriers highlight the complexity of the process. We highlight the need for integrating computational and experimental findings for further studies to unify mechanistic understanding and develop applications in redox biology.

Photodynamic therapy (PDT) involves a reaction between photosensitizers (PS) and oxygen (O₂) to generate cytotoxic reactive oxygen species (ROS), which effectively eliminate undesired cells. Compared to conventional treatments like surgery, radiation, and chemotherapy, PDT offers several advantages, including minimal toxicity to healthy tissues and no long-term systemic side effects. However, its therapeutic efficacy is limited under hypoxic conditions, as the process relies on the presence of oxygen in the target tissue. To address these challenges, combining PDT with photothermal therapy (PTT) creates a synergistic phototherapy approach. The heat generated by PTT enhances blood flow in tumors, increasing oxygen delivery to tumor sites and boosting PDT's effectiveness. These combinations are being explored in PDT/PTT as an innovative, synergistic cancer treatment strategy, aiming to enhance the therapeutic index. One promising strategy to connect both PDT and PTT therapies involves developing nanosystems that integrate metal hexacyanoferrate (MHCF) nanoparticles with multifunctional PS. Here, we review several studies that have evaluated the combination of MHCF with various PSs to apply PDT and PTT synergistically. We discuss how nanocomposites based on these materials can address the challenges and limitations still faced in PDT/PTT. This review aims to identify new opportunities for the application of metal hexacyanoferrates in these phototherapeutic modalities.

Incorporating biological molecular interactions into cognitive computing through chemical artificial intelligence (AI) presents a transformative approach with far-reaching implications for various fields, such as protein engineering, drug discovery, bioinformatics, synthetic biology, and unconventional computing. Cognitive computing, designed to emulate human thought processes and enhance decision-making, utilizes technologies, such as machine learning, natural language processing, and speech recognition for better human-system interactions. Despite advancements, the integration of biological processes with cognitive computing remains fraught with challenges, particularly due to the complexity and scale of biological data. Here, we explore the possible benefits of connecting cognitive computing with biological knowledge, including more precise models of protein interactions, gene regulation, and metabolic pathways, which could lead to personalized treatments and early disease detection. Furthermore, we discuss the intersection of cognitive computing and biophysical research techniques, examining how analogies from neuroscience-like synaptic communication and neural plasticity-can inform the development of neuromorphic chips and enhance predictive models. Additionally, the study delves into intrinsically disordered proteins (IDPs) and their crucial roles in brain function and information processing. These insights are pivotal for advancing neuroinformatics and creating more adaptive, context-aware cognitive computing algorithms. By leveraging biophysical investigations and the unique properties of IDPs, the research aims to bridge the gap between the biological processes and their computational analogs, proposing novel methods, such as chemical AI implemented in liquid solutions as promising avenues for future advancements.

One of the main focuses of glycobiology is investigating the synthesis and modification of carbohydrates in biological systems, due to their involvement in various processes such as cell recognition, differentiation, and immune response. Since the study of these glycans contributes to the understanding of complex biological functions, these biochemical compounds can be analyzed using lectins, which are ubiquitous proteins in nature capable of specifically recognizing carbohydrates. In addition, lectin-carbohydrate interaction can be visualized by conjugating these proteins with quantum dots (QDs), which are fluorescent nanoprobes with advantageous properties, including photostability and size-tunable emission. QDs also possess chemically active surfaces that enable the attachment of biomolecules, such as lectins. In this review, we provide detailed reports of studies involving QD-lectin conjugates conducted by the Biomedical Nanotechnology Group at the Federal University of Pernambuco (UFPE/Brazil) and its collaborators. An integrated perspective on the use of QD-lectin conjugates to study saccharides in a range of biological systems, from bacteria and fungi to red blood cells and cancer tissues, is also presented. We hope this comprehensive review inspires further studies exploring the brightness of lectins upon conjugation with QDs to unravel glycobiological processes.

We report on two key discoveries resulting from the combination of the Hilbert phase plate (HPP) and the Wiener filter: firstly, the resolution of the HPP's mixed image problem through a one-step experiment, and secondly, the unification of the Zernike phase plate (ZPP) and the HPP. When the phase of the HPP is reduced to less than π, it produces a mixed image comprising both the normal and the differential images. The HPPU (left-right unified HPP), proposed to address this issue, required a two-step experimental process. However, during our efforts to resolve the mixed image problem using either the left or right HPP, we discovered that the Wiener filtering process not only addresses this issue but also facilitates the unification of the ZPP and HPP. We will discuss the theoretical development behind these discoveries and their verification through simulations of three phase contrast methods: the Scherzer, ZPP, and HPP methods.

Various biophysical and biochemical techniques have been developed to measure the affinity of interacting molecules. This review analyzes the combination of three methods: differential scanning fluorimetry as the initial high-throughput screening technique and microscale thermophoresis and isothermal titration calorimetry as complementary methods to quantify binding affinity. The presented work is the first to detailed compare the strengths and flaws of these three specific methods, as well as their application possibilities and complementarity. The fundamentals of these methods will be covered, including the most often-used models for characterizing observable phenomena and an emphasis on methods for analyzing data. A comprehensive review of numerous approaches to data analysis found in the literature is additionally provided, with the benefits and drawbacks of each, as well as the pitfalls and related concerns. Finally, examples of different systems will be presented, and methods used and some discrepancies in results will be described and discussed.