Progress in Biophysics & Molecular Biology最新文献

Quantum dots (QDs) are a class of remarkable materials that have garnered significant attention since their initial discovery. It is noteworthy to mention that it took approximately a decade for these materials to be successfully implemented in practical applications. While QDs have demonstrated notable optical properties, it is important to note that these attributes alone have not rendered them a feasible substitute for traditional organic dyes. Furthermore, it is worth noting that the substance under investigation exhibited inherent toxicity and instability in its initial state, primarily due to the presence of a heavy metal core. In the initial stages of research, it was observed that the integration of nanocomposites had a positive impact on the properties of QDs. The discovery of these nanocomposites was motivated by the remarkable properties exhibited by biocomposites found in nature. Recent discoveries have shed light on the potential utilization of QDs as a viable strategy for drug delivery, offering a promising avenue to enhance the efficacy of current pharmaceuticals and pave the way for the creation of innovative therapeutic approaches. The primary objective of this review was to elucidate the distinctive characteristics that render QDs highly suitable for utilization as nanocarriers. In this study, we will delve into the multifaceted applications of QDs as sensing nanoprobes and their utilization in diverse drug delivery systems. The focus of our investigation was directed toward the utilization of QD/polymer composites in sensing applications, with particular emphasis on their potential as chemical sensors, biosensors, and physical sensors.

Surface enhanced Raman spectroscopy (SERS) allows the ultrasensitive detection of analytes present in traces or even single molecule levels by the generation of electromagnetic fields. It is a powerful vibrational spectroscopic method that is capable to detect traces of chemical and biological analytes. SERS technique is involved in the extremely sophisticated studies of molecules with high specificity and sensitivity. In the vicinity of nanomaterials decorated surfaces, SERS can monitor extremely low concentrations of analytes in a non-destructive manner with narrow line widths. This review article is focused on some recently developed SERS-based sensors for distinct types of analytes like disease-related biomarkers, organic and inorganic molecules, various toxins, dyes, pesticides, bacteria as well as single molecules. This study aims to enlighten the arising sensing approaches based on the SERS technique. Apart from this, some basics of the SERS technique like their mechanism, detection strategy, and involvement of some specific nanomaterials are also highlighted herein. Finally, the study concluded with some discussion of applications of SERS in various fields like food and environmental analysis.

ATP synthase is a key protein in the oxidative phosphorylation process, as it aids in the effective production of ATP (Adenosine triphosphate) in all life's of kingdoms. ATP synthases have distinctive properties that contribute to efficient ATP synthesis. The ATP synthase of mycobacterium is of special relevance since it has been identified as a target for potential anti-TB molecules, especially Bedaquiline (BDQ). Better knowledge of how mycobacterial ATP synthase functions and its peculiar characteristics will aid in our understanding of bacterial energy metabolism adaptations. Furthermore, identifying and understanding the important distinctions between human ATP synthase and bacterial ATP synthase may provide insight into the design and development of inhibitors that target specific ATP synthase. In recent years, many potential candidates targeting the ATP synthase of mycobacterium have been developed. In this review, we discuss the druggable targets of the Electron transport chain (ETC) and recently identified potent inhibitors (including clinical molecules) from 2015 to 2022 of diverse classes that target ATP synthase of M. tuberculosis.

The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in biology, emphasizing stochastic processes at molecular, cellular, and higher levels in organisms as having a role beyond simple noise. The CDP and Noble's theories (NT) claim that biological systems use stochasticity. This paper presents the CDP and NT, discussing common notions and differences between the two theories. The paper presents the CDP-based concept of taking the disorder beyond its role in nature to correct malfunctions of systems and improve the efficiency of biological systems. The use of CDP-based algorithms embedded in second-generation artificial intelligence platforms is described. In summary, noise is inherent to complex systems and has a functional role. The CDP provides the option of using noise to improve functionality.

Trying to provide a broad overview about the origin of life in Earth, the most significant transitions of life before cells are listed and discussed. The current approach emphasizes the symbiotic relationships that emerged with life. We propose a rational, stepwise scenario for the origin of life that starts with the origin of the first biomolecules and steps forward until the origins of the first cells. Along this path, we aim to provide a brief, though comprehensive theoretical model that will consider the following steps: (i) how nucleotides and other biomolecules could be made prebiotically in specific prebiotic refuges; (ii) how the first molecules of RNAs were formed; (iii) how the proto-peptidyl transferase center was built by the concatenation of proto-tRNAs; (iv) how the ribosome and the genetic code could be structured; (v) how progenotes could live and reproduce as “naked” ribonucleoprotein molecules; (vi) how peptides started to bind molecules in the prebiotic soup allowing biochemical pathways to evolve from those bindings; (vii) how genomes got bigger by the symbiotic relationship of progenotes and lateral transference of genetic material; (viii) how the progenote LUCA has been formed by assembling most biochemical routes; (ix) how the first virion capsids probably emerged and evolved; (x) how phospholipid membranes emerged probably twice by the evolution of lipid-binding proteins; (xi) how DNA synthesis have been formed in parallel in Bacteria and Archaea; and, finally, (xii) how DNA-based cells of Bacteria and Archaea have been constituted. The picture provided is conjectural and present epistemological gaps. Future research will help to advance into the elucidation of gaps and confirmation/refutation of current statements.

In 2021 I noted that in all information-based systems we understand, Cognition creates Code, which controls Chemical reactions. Known agents write software which controls hardware, and not the other way around. I proposed the same is true in all of biology. Though the textbook description of cause and effect in biology proposes the reverse, that Chemical reactions produce Code from which Cognition emerges, there are no examples in the literature demonstrating either step. A mathematical proof for the first step, cognition generating code, is based on Turing's halting problem. The second step, code controlling chemical reactions, is the role of the genetic code. Thus a central question in biology: What is the nature and source of cognition? In this paper I propose a relationship between biology and Quantum Mechanics (QM), hypothesizing that the same principle that enables an observer to collapse a wave function also grants biology its agency: the organism's ability to act on the world instead of merely being a passive recipient. Just as all living cells are cognitive (Shapiro 2021, 2007; McClintock 1984; Lyon 2015; Levin 2019; Pascal and Pross, 2022), I propose humans are quantum observers because we are made of cells and all cells are observers. This supports the century-old view that in QM, the observer does not merely record the event but plays a fundamental role in its outcome.The classical world is driven by laws, which are deductive; the quantum world is driven by choices, which are inductive. When the two are combined, they form the master feedback loop of perception and action for all biology. In this paper I apply basic definitions of induction, deduction and computation to known properties of QM to show that the organism altering itself (and its environment) is a whole shaping its parts. It is not merely parts comprising a whole. I propose that an observer collapsing the wave function is the physical mechanism for producing negentropy. The way forward in solving the information problem in biology is understanding the relationship between cognition and QM.

Could nature be harnessing quantum mechanics in cilia to optimize the sensitivity of the mechanism of left–right symmetry breaking during development in vertebrates? I evaluate whether mechanosensing — i.e., the detection of a left-right asymmetric signal through mechanical stimulation of sensory cilia, as opposed to biochemical signalling — might be functioning in the embryonic left–right organizer of the vertebrate bodyplan through quantum mechanics. I conclude that there is a possible role for quantum biology in mechanosensing in cilia. The system may not be limited by classical thermal noise, but instead by quantum noise, with an amplification process providing active cooling.

Natural substances are increasingly being used as cancer treatments. Scutellarin, as a flavonoid, recently has been identified in a Chinese herbal extract called Erigeron breviscapus (Vant.). Scutellarin is being researched for its potential benefits due to the discovery that it possesses a variety of biological effects, such as neuroprotective, anti-bacterial, and anti-viral properties. In addition to these biological functions, scutellarin has also been found to have anti-tumor properties. The underlying mechanisms of scutellarin's anticancer activity involve its ability to inhibit various signaling pathways, such as Jak/STAT, ERK/AMPK, and Wnt/β-catenin. Additionally, scutellarin activates intrinsic and extrinsic apoptotic pathways, which causes the death of tumor cells, interrupts the cell cycle, and promotes its arrest. By limiting metastasis, angiogenesis, drug resistance, and other tumorigenic processes, scutellarin also reduces the aggressiveness of tumors. Despite its promising anticancer activity, scutellarin faces several challenges in its clinical development, including poor solubility, bioavailability, and pharmacokinetic properties. Therefore, it has been suggested that certain modifications can enhance the pharmacogenetic capabilities of scutellarin to decrease its limited water solubility. In conclusion, scutellarin represents a potential candidate for cancer treatment and further studies are needed to explore its clinical utility and optimize its therapeutic potential.

Tuberculosis (TB) is among the leading causes of death worldwide from a single infectious agent. This disease usually affects the lungs (pulmonary TB) and can be cured in most cases with a quick diagnosis and proper treatment. Microscopic sputum smear is widely used to diagnose and manage pulmonary TB. Despite being relatively fast and low cost, it can be exhausting because it depends on manually counting TB bacilli (Mycobacterium tuberculosis) in microscope images. In this context, different Deep Learning (DL) techniques are proposed in the literature to assist in performing smear microscopy. This article presents a systematic review based on the PRISMA procedure, which investigates which DL techniques can contribute to classifying TB bacilli in microscopic images of sputum smears using the Ziehl-Nielsen method. After an extensive search and a careful inclusion/exclusion procedure, 28 papers were selected from a total of 400 papers retrieved from nine databases. Based on these articles, the DL techniques are presented as possible solutions to improve smear microscopy. The main concepts necessary to understand how such techniques are proposed and used are also presented. In addition, replication work is also carried out, verifying reproducibility and comparing different works in the literature. In this review, we look at how DL techniques can be a partner to make sputum smear microscopy faster and more efficient. We also identify some gaps in the literature that can guide which issues can be addressed in other works to contribute to the practical use of these methods in laboratories.

Cellular and biochemical studies of nonhomologous DNA end joining (NHEJ) have long established that nuclease and polymerase action are necessary for the repair of a very large fraction of naturally-arising double-strand breaks (DSBs). This conclusion is derived from NHEJ studies ranging from yeast to humans and all genetically-tractable model organisms. Biochemical models derived from recent real-time and structural studies have yet to incorporate physical space or timing for DNA end processing. In real-time single molecule FRET (smFRET) studies, we analyzed NHEJ synapsis of DNA ends in a defined biochemical system. We described a Flexible Synapsis (FS) state in which the DNA ends were in proximity via only Ku and XRCC4:DNA ligase 4 (X4L4), and in an orientation that would not yet permit ligation until base pairing between one or more nucleotides of microhomology (MH) occurred, thereby allowing an in-line Close Synapsis (CS) state. If no MH was achievable, then XLF was critical for ligation. Neither FS or CS required DNA-PKcs, unless Artemis activation was necessary to permit local resection and subsequent base pairing between the two DNA ends being joined. Here we conjecture on possible 3D configurations for this FS state, which would spatially accommodate the nuclease and polymerase processing steps in an iterative manner. The FS model permits repeated attempts at ligation of at least one strand at the DSB after each round of nuclease or polymerase action. In addition to activation of Artemis, other possible roles for DNA-PKcs are discussed.