Field Of Biology Research Articles

Therapeutic Potential of CRISPR/Cas in Hashimoto's Thyroiditis: A Comprehensive Review.

Hashimoto's thyroiditis (HT) is a commonly occurring illness of autoimmune endocrine origin. It is usually present in the pediatric age group along with other well-known diseases, such as type 1 insulin-dependent diabetes. The defining feature of this disease is the immune-- mediated attack on the thyroid gland resulting in the destruction of thyroid tissues and cells. Given that HT frequently affects family members, it is well-recognized that individuals are genetically predisposed to this disease. Patients with HT also display a significantly increased risk for several different cancers, justifying the eminent need for the development of therapies for managing and treating HT. Gene editing has made several advancements in the field of molecular biology and has turned out to become a promising approach to correct several autoimmune diseases. Currently, CRISPR/Cas, a nuclease-based editing technique, is publicized as a promising tool for curing several genetic diseases and cancers. However, very limited research has been conducted as of now on autoimmune disease management and cure via CRISPR/Cas technique. This review provides an account of the potential candidate genes associated with Hashimoto's thyroiditis, and only a few animal and human models have been generated via the CRISPR/Cas gene editing technique. Mouse models of autoimmune thyroiditis generated through the CRISPR/Cas gene editing technique by targeting the candidate genes will provide us with a deeper insight into the pathophysiology of HT and further pave the way for the immunomodulation of HT via gene editing.

Detailed Study on the Interfacial Interaction between Different Polyoxometalates and Tetronic Block Copolymers Exploring the Langmuir-Blodgett Technique.

Polyoxometalates (POMs) interact with various biologically relevant entities. A basic understanding of this interaction is very important for various applications in the biological field. In this work, the focus is on the study of the interaction between tetronics and Keggin POMs. T701 and T90R4 are the two tetronics considered here; they have different solubilities in water due to different PPO/PEO ratios. The arrangement of PPO and PEO is also different with respect to the central ethylenediamine groups. Three different Keggin-type POMs, phosphomolybdic acid (PMA), phosphotungstic acid (PTA), and silicotungstic acid (STA), with different charge densities are chosen for an elaborate investigation using Langmuir-Blodgett technique. The observation is analyzed thoroughly, which shows both electrostatic interaction and adsorption of POMs on the PPO blocks of the tetronics due to the chaotropic effect, which is responsible for the binding of POMs (in subphase) with the tetronic monolayer. This interaction results in an expanded yet rigid monolayer for POM-tetronic association on the surface. Surface pressure vs mean molecular area isotherm is the key characterization to reach the conclusion. UV-vis spectroscopy, NMR, ITC, ellipsometric studies, FTIR, and SEM also serve as supportive characterization techniques.

Making Predictions Using Poorly Identified Mathematical Models

Many commonly used mathematical models in the field of mathematical biology involve challenges of parameter non-identifiability. Practical non-identifiability, where the quality and quantity of data does not provide sufficiently precise parameter estimates is often encountered, even with relatively simple models. In particular, the situation where some parameters are identifiable and others are not is often encountered. In this work we apply a recent likelihood-based workflow, called Profile-Wise Analysis (PWA), to non-identifiable models for the first time. The PWA workflow addresses identifiability, parameter estimation, and prediction in a unified framework that is simple to implement and interpret. Previous implementations of the workflow have dealt with idealised identifiable problems only. In this study we illustrate how the PWA workflow can be applied to both structurally non-identifiable and practically non-identifiable models in the context of simple population growth models. Dealing with simple mathematical models allows us to present the PWA workflow in a didactic, self-contained document that can be studied together with relatively straightforward Julia code provided on GitHub. Working with simple mathematical models allows the PWA workflow prediction intervals to be compared with gold standard full likelihood prediction intervals. Together, our examples illustrate how the PWA workflow provides us with a systematic way of dealing with non-identifiability, especially compared to other approaches, such as seeking ad hoc parameter combinations, or simply setting parameter values to some arbitrary default value. Importantly, we show that the PWA workflow provides insight into the commonly-encountered situation where some parameters are identifiable and others are not, allowing us to explore how uncertainty in some parameters, and combinations of parameters, regardless of their identifiability status, influences model predictions in a way that is insightful and interpretable.

Vibration assisted electron tunnelling in COVID-19 infection using quantum state diffusion.

The spread of the COVID-19 virus has become a global health crisis, and finding effective treatments and preventions is a top priority. The field of quantum biology primarily focuses on energy or charge transfer, with a particular emphasis on photosynthesis. However, there is evidence to suggest that cellular receptors such as olfactory or neural receptors may also use vibration-assisted electron tunnelling to enhance their functions. Quantum tunnelling has also been observed in enzyme activity, which is relevant to the invasion of host cells by the SARS-CoV-2 virus. Additionally, COVID-19 appears to disrupt receptors such as olfactory receptors. These findings suggest that quantum effects could provide new insights into the mechanisms of biological systems and disease, including potential treatments for COVID-19. We have applied the open quantum system approach using Quantum State Diffusion to solve the non-linear stochastic Schrödinger equation (SSE) for COVID-19 virus infection. Our model includes the mechanism when the spike protein of the virus binds with an ACE2 receptor is considered as dimer. These two entities form a system and then coupled with the cell membrane, which is modelled as a set of harmonic oscillators (bath). By simulating the SSE, we find that there is vibration-assisted electron tunnelling happening in certain biological parameters and coupling regimes. Furthermore, our model contributes to the ongoing research to understand the fundamental nature of virus dynamics. It proposes that vibration-assisted electron tunneling could be a molecular phenomenon that augments the lock-and-key process for olfaction. This insight may enhance our understanding of the underlying mechanisms governing virus-receptor interactions and could potentially lead to the development of novel therapeutic strategies.

Advancing Aquatic Food Safety Detection Using Highly Sensitive Graphene Oxide and Reduced Graphene Oxide (GO/r-GO) Fluorescent Sensors

AbstractWith the increasing demand for aquatic products, the requirement for the safety detection of aquatic products is also increasing. In the past decade, graphene oxide (GO) and reduced graphene oxide (r-GO) have become hot topics in many fields due to their special physical and chemical properties. With their excellent conductivity, a variety of electrochemical sensors have been developed in the fields of biology, food and chemistry. However, the unique optical properties of GO/r-GO have not yet been widely utilized. With the deepening of research, the fluorescence quenching performance of GO/r-GO has been proven to have excellent potential for building fluorescent sensors, and GO/r-GO fluorescent sensors have thus become an inevitable trend in sensor development. This review summarizes the main preparation methods of GO/r-GO and the principles of GO/r-GO fluorescent sensors comprehensively. Additionally, recent advances in utilizing GO/r-GO fluorescent sensors to detect aquatic food are discussed, including the application for the detection of harmful chemicals, microorganisms, and endogenous substances in aquatic products, such as pesticides, antibiotics and heavy metals. It is hoped that this review will help accelerate the progress in the field of analysis, and promote the establishment of an aquatic food supervision system.

Rice's trajectory from wild to domesticated in East Asia.

Rice (Oryza sativa) serves as a staple food for more than one-third of the global population. However, its journey from a wild gathered food to domestication remains enigmatic, sparking ongoing debates in the biological and anthropological fields. Here, we present evidence of rice phytoliths sampled from two archaeological sites in China, Shangshan and Hehuashan, near the lower reaches of the Yangtze River. We demonstrate the growth of wild rice at least 100,000 years before present, its initial exploitation as a gathered resource at about 24,000 years before present, its predomestication cultivation at about 13,000 years before present, and eventually its domestication at about 11,000 years before present. These developmental stages illuminate a protracted process of rice domestication in East Asia and extend the continuous records of cereal evolution beyond the Fertile Crescent.

Frequency multiplexing enables parallel multi-sample EPR

Electron paramagnetic resonance (EPR) spectroscopy stands out as a powerful analytical technique with extensive applications in the fields of biology, chemistry, physics, and material sciences. It proves invaluable for investigating the molecular structure and reaction mechanisms of substances containing unpaired electrons, such as metal complexes, organic and inorganic radicals, and intermediate states in chemical reactions. However, despite their remarkable capabilities, EPR systems face significant limitations in terms of sample throughput, as current commercial systems only target the analysis of one sample at a time. Here we introduce a novel scheme for conducting ultra-high frequency continuous-wave EPR (CW EPR) targeting the EPR spectroscopy of multiple microliter volume samples in parallel. Our proof-of-principle prototype involves two decoupled detection cells equipped with high qualty factor Q=104\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Q=104$$\\end{document} solenoidal coils tuned to 488 and 589 MHz, ensuring a significant frequency gap for effective radio frequency (RF) decoupling between the channels. To further enhance electromagnetic decoupling, an orthogonal alignment of the coils was adopted. The paper further presents an innovative radiofrequency circuit concept that utilizes a single physical RF channel to simultaneously conduct parallel EPR on up to eight cells. Parallel EPR experiments on two BDPA samples, each with a sample volume of 18.3 μL, registered signal-to-noise ratios of 255 and 252 for the two EPR measurement cells, with no observable coupling. The showcased prototype, built using cost-effective commercially available fabrication technology, is readily scalable and represents an initial step with promising potential for advancing sample screening with high-throughput parallel EPR.

Assessing the evolution of research topics in a biological field using plant science as an example.

Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field. Using plant biology as an example, we used machine learning and language models to classify plant science citations into topics representing interconnected, evolving subfields. The changes in prevalence of topical records over the last 50 years reflect shifts in major research trends and recent radiation of new topics, as well as turnover of model species and vastly different plant science research trajectories among countries. Our approaches readily summarize the topical diversity and evolution of a scientific field with hundreds of thousands of relevant papers, and they can be applied broadly to other fields.

Dirk Pette, remembered for his pioneering muscle research.

It is with great sadness that we learned of the passing of Prof. Dr. Dr. h.c. Dirk Pette. He passed away suddenly and unexpectedly on June 4, 2022. Dirk was an outstanding professor of biochemistry at the University of Konstanz, Germany and an internationally renowned researcher in the field of skeletal muscle biology. His research on electrical stimulation has had a profound impact on our understanding of myofiber type specification and the enormous adaptive potential of skeletal muscle. Under Dirk's leadership, new biological questions in the field of neuromuscular biology have developed into multidisciplinary approaches using advanced physiological, cell biological, and biochemical techniques. Dirk's research laboratory was frequently visited by a large number of national and international collaborators who familiarized themselves with the technically demanding stimulation protocols and bioanalytical techniques to study the intricate details of the highly complex process of fast-to-slow muscle transitions. Importantly, fundamental studies on the physiological effects of changes in innervation patterns on muscle phenotype have provided the scientific evidence base for a variety of innovative clinical applications. The skeletal muscle research community has lost one of its leading figures and an outstanding teacher of protein biochemistry. He leaves an inspiring legacy in the field of basic and applied myology. Dirk will be missed by his colleagues and by many students of neuromuscular biology and beyond.

How much can ChatGPT really help computational biologists in programming?

ChatGPT, a recently developed product by openAI, is successfully leaving its mark as a multi-purpose natural language based chatbot. In this paper, we are more interested in analyzing its potential in the field of computational biology. A major share of work done by computational biologists these days involve coding up bioinformatics algorithms, analyzing data, creating pipelining scripts and even machine learning modeling and feature extraction. This paper focuses on the potential influence (both positive and negative) of ChatGPT in the mentioned aspects with illustrative examples from different perspectives. Compared to other fields of computer science, computational biology has (1) less coding resources, (2) more sensitivity and bias issues (deals with medical data), and (3) more necessity of coding assistance (people from diverse background come to this field). Keeping such issues in mind, we cover use cases such as code writing, reviewing, debugging, converting, refactoring, and pipelining using ChatGPT from the perspective of computational biologists in this paper.

Integrating cryo-OrbiSIMS with computational modelling and metadynamics simulations enhances RNA structure prediction at atomic resolution

The 3D architecture of RNAs governs their molecular interactions, chemical reactions, and biological functions. However, a large number of RNAs and their protein complexes remain poorly understood due to the limitations of conventional structural biology techniques in deciphering their complex structures and dynamic interactions. To address this limitation, we have benchmarked an integrated approach that combines cryogenic OrbiSIMS, a state-of-the-art solid-state mass spectrometry technique, with computational methods for modelling RNA structures at atomic resolution with enhanced precision. Furthermore, using 7SK RNP as a test case, we have successfully determined the full 3D structure of a native RNA in its apo, native and disease-remodelled states, which offers insights into the structural interactions and plasticity of the 7SK complex within these states. Overall, our study establishes cryo-OrbiSIMS as a valuable tool in the field of RNA structural biology as it enables the study of challenging, native RNA systems.

Femtosecond laser ultrafast photothermal exsolution

Abstract Exsolution, as an effective approach to construct particle-decorated interfaces, is still challenging to yield interfacial films rather than isolated particles. Inspired by in vivo near infrared laser photothermal therapy (PTT), using 3 mol.% Y2O3 stabilized tetragonal zirconia polycrystals (3Y-TZP) as host oxide matrix and iron-oxide (Fe3O4/γ-Fe2O3/α-Fe2O3) materials as photothermal modulator and exsolution resource, femtosecond laser ultrafast exsolution approach is presented enabling to conquer this challenge. The key is to trigger photothermal annealing behavior via femtosecond laser ablation to initialize phase transition into tetragonal zirconia (t-ZrO2) and induce columnar crystal growth, where Fe-ions rapidly segregate along grain boundaries and diffuse towards the outmost surface, becoming “frozen” there, highlighting the potential to use photothermal materials and ultrafast heating/quenching behaviors of femtosecond laser ablation for interfacial modification via exsolution. Triggering interfacial iron-oxide coloring exsolution is composition and concentration dependent, indicating photothermal materials themselves and corresponding photothermal transition capacity play a crucial role, initializing at 5wt%, 2wt%, and and 3wt% for Fe3O4-/γ-Fe2O3/α-Fe2O3 embedded 3Y-TZP samples. Due to different photothermal effects, exsolution states of ablated 5wt% Fe3O4-/γ-Fe2O3/α-Fe2O3-embedded 3Y-TZP samples are completely different, complete coverage, exhaustion (ablated away) and partial exsolution (rich in the crystal boundaries of sublayers). This novel exsolution is uniquely featured by up to now the deepest microscale (10 μm from 5 wt%-Fe3O4-3Y-TZP sample) Fe-elemental deficient layer for exsolution and the whole coverage of exsolved materials rather than formation of isolated exsolved particles by other methods. It is believed that femtosecond laser ultrafast photothermal exsolution may pave a good way to modulate interfacial properties for extensive applications in the fields of biology, optics/photonics, energy, catalysis, environment, etc.

Direct reconstruction of tissue temperature fields during thermal therapy by dynamic response matching and steady-state correction

In the field of oncology thermotherapy technology, online and real-time reconstruction of biological tissue temperature field is a fundamental work with important practical needs. In this paper, we proposed a new method for direct reconstruction of biological tissue temperature field by dynamic response feature matching and steady-state correction. Based on the bioheat transfer equation, the step response model of tissue temperature field during thermal therapy is established, and the dynamic response eigenvectors of biological tissue temperature and the steady-state gain of temperature response are determined offline. According to the optimal matching principle between the temperature dynamic response of the observation point and the internal space point of tissue, the optimal matching matrix of the dynamic response features between the observation point temperature and the internal temperature field of tissue is determined with the use of the dynamic response eigenvectors. Further, through the weighted synthesis of observation point temperature response by using the optimal matching matrix of dynamic response features, the tissue transient temperature field pre-estimation model is established. Finally, by correcting the tissue temperature field pre-estimation model with steady-state gain correction factor, the direct reconstruction scheme of temperature field based on dynamic response feature matching and steady-state gain correction is established. In this work, the non-destructive reconstruction of the internal temperature field of biological tissues during laser-induced thermal therapy is achieved based on the above direct reconstruction scheme. Numerical simulation experiments are performed to investigated the effects of pre-estimation time domain, the number of measurement points, laser irradiation form and measurement error on the temperature field reconstruction results.

High-Throughput Multitarget Molecular Detection in an Automatic Light-Addressable Photoelectrochemical Sensing Platform.

Successively emerged high-throughput multitarget molecular detection methods bring significant development tides in chemical, biological, and environmental fields. However, several persistent challenges of intricate sample preparation, expensive instruments, and tedious and skilled operations still need to be further addressed. Here, we propose an automatic light-addressable photoelectrochemical (ALA-PEC) sensing platform for sensitive and selective detection of multitarget molecules. With Au nanoparticle-decorated TiO2 nanotube photonic crystals (Au-TiO2 NTPCs) as a photoelectrode and 8 kinds of antibiotics as target molecules, the ALA-PEC sensing system implements automatic detection of multimolecules in a short time with high sensitivity and good selectivity. Random samples with different amounts of antibiotics have been well-distinguished in the ALA-PEC system, and both the chemical components and concentrations have been well-illustrated in a pattern recognition model. It is worth noting that 8 samples are not the limit of the ALA-PEC sensing platform, which can be easily expanded to more complex detection arrays based on practical needs. The emerging ALA-PEC sensing platform provides a new solution for rapid screening and detection of multitarget and high-throughput substances and potentially brings the automatic, portable, sensitive, high-throughput, and cost-effective detection technique to an entire new realm.

Research on the application of the terahertz technique

Terahertz is a new radiation source with many unique advantages and terahertz technology is a very important cross-cutting frontier field, providing a very attractive opportunity for technological innovation, national economic development and national security that may lead to revolutionary developments in science and technology. This article introduces the advantages and disadvantages of electromagnetic waves in the terahertz frequency band, the origin and development history of terahertz technology, and the composition of common terahertz systems, and outlines the technologies of secure communication, detection, imaging, etc., according to their principles. The analysis shows that under the premise of ensuring the size of its key devices to be miniaturized in application, and solving the technical difficulties such as its complicated use, high overall cost and reliance on low-temperature operation, the terahertz technology will have a broad market prospect in the fields of biology, medical treatment, communication, military security and so on.

CHALLENGES AND OPPORTUNITIES TO DESIGN FUTURE CROPS: GATEWAY TO SUSTAINABLE AGRICULTURE IN 21ST CENTURY

The global food production system is facing numerous challenges due to factors such as population growth, climate change, limited resources, and environmental preservation. To address these challenges, various strategies can be employed to develop future crops that are more productive, nutritious, and resilient. One strategy is to improve the yield potential of existing crops by developing new high-yielding cultivars. This can be achieved through the development of new varieties that can produce more grain under optimal conditions. Additionally, improving the nutritional quality of crops is important to address nutrient deficiencies. Synthetic biology and metabolic engineering methods can be used to develop crops with enhanced nutritional value. Efficient utilization of agricultural resources is another important aspect of crop improvement. This includes developing crops that use water and nutrients more efficiently, reducing the need for irrigation and fertilizers, and minimizing environmental impacts. Increasing the resistance of crops to pests, diseases, and extreme weather events can also help reduce the use of pesticides and minimize crop losses. The domestication of wild or semi-wild plants through genetic manipulation offers new opportunities for crop design. These plants may have high nutritional value, stress tolerance, and specialized metabolites that can be incorporated into cultivated crops. Similarly, the domestication of orphan or neglected plants can contribute to crop improvement by incorporating unique traits. Genetic improvement through the transfer of genes from wild relatives or other species can also enhance crop productivity. Advancements in genomics and genetic technologies can aid in the identification and transfer of beneficial alleles. Agronomic improvements, such as maximizing the effectiveness of crop protection agents and fertilizers while minimizing their environmental impact, can also contribute to crop performance. The emerging field of synthetic biology offers opportunities for developing novel biological devices and systems that can further enhance crop productivity and resilience. Overall, these strategies can help address the challenges faced by the global food production system.

Linking Aging to Cancer: The Role of Chromatin Biology.

Epigenetic changes have been established to be a hallmark of aging, which implies that aging science requires collaborating with the field of chromatin biology. DNA methylation patterns, changes in relative abundance of histone post-translational modifications (PTMs), and chromatin remodeling are the central players in modifying chromatin structure. Aging is commonly associated with an overall increase in chromatin instability, loss of homeostasis and decondensation. However, numerous publications have highlighted that the link between aging and chromatin changes is not nearly as linear as previously expected. This complex interplay of these epigenetics elements during the lifetime of an organism likely contribute to cellular senescence, genomic instability, and disease susceptibility. Yet, the causal links between these phenomena still need to be fully unraveled. In this perspective article, we discuss potential future directions of aging chromatin biology.

Recent Advances in Magnesium–Magnesium Oxide Nanoparticle Composites for Biomedical Applications

Magnesium (Mg) is considered an attractive option for orthopedic applications due to its density and elastic modulus close to the natural bone of the body, as well as biodegradability and good tensile strength. However, it faces serious challenges, including a high degradation rate and, as a result, a loss of mechanical properties during long periods of exposure to the biological environment. Also, among its other weaknesses, it can be mentioned that it does not deal with bacterial biofilms. It has been found that making composites by synergizing its various components can be an efficient way to improve its properties. Among metal oxide nanoparticles, magnesium oxide nanoparticles (MgO NPs) have distinct physicochemical and biological properties, including biocompatibility, biodegradability, high bioactivity, significant antibacterial properties, and good mechanical properties, which make it a good choice as a reinforcement in composites. However, the lack of comprehensive understanding of the effectiveness of Mg NPs as Mg matrix reinforcements in mechanical, corrosion, and biological fields is considered a challenge in their application. While introducing the role of MgO NPs in medical fields, this article summarizes the most important results of recent research on the mechanical, corrosion, and biological performance of Mg/MgO composites.

A Comprehensive Exploration of Caspase Detection Methods: From Classical Approaches to Cutting-Edge Innovations.

The activation of caspases is a crucial event and an indicator of programmed cell death, also known as apoptosis. These enzymes play a central role in cancer biology and are considered one promising target for current and future advancements in therapeutic interventions. Traditional methods of measuring caspase activity such as antibody-based methods provide fundamental insights into their biological functions, and are considered essential tools in the fields of cell and cancer biology, pharmacology and toxicology, and drug discovery. However, traditional methods, though extensively used, are now recognized as having various shortcomings. In addition, these methods fall short of providing solutions to and matching the needs of the rapid and expansive progress achieved in studying caspases. For these reasons, there has been a continuous improvement in detection methods for caspases and the network of pathways involved in their activation and downstream signaling. Over the past decade, newer methods based on cutting-edge state-of-the-art technologies have been introduced to the biomedical community. These methods enable both the temporal and spatial monitoring of the activity of caspases and their downstream substrates, and with enhanced accuracy and precision. These include fluorescent-labeled inhibitors (FLIs) for live imaging, single-cell live imaging, fluorescence resonance energy transfer (FRET) sensors, and activatable multifunctional probes for in vivo imaging. Recently, the recruitment of mass spectrometry (MS) techniques in the investigation of these enzymes expanded the repertoire of tools available for the identification and quantification of caspase substrates, cleavage products, and post-translational modifications in addition to unveiling the complex regulatory networks implicated. Collectively, these methods are enabling researchers to unravel much of the complex cellular processes involved in apoptosis, and are helping generate a clearer and comprehensive understanding of caspase-mediated proteolysis during apoptosis. Herein, we provide a comprehensive review of various assays and detection methods as they have evolved over the years, so to encourage further exploration of these enzymes, which should have direct implications for the advancement of therapeutics for cancer and other diseases.

A short guide to addressing accessibility at scientific conferences.

Although encouraging progress to address issues of accessibility at scientific conferences has been made in recent years, further efforts are required to enact the comprehensive solutions necessary to accommodate the diverse needs of disabled scientists. This Opinion provides an easy-to-follow guide to ensuring that scientific conferences are accessible to disabled scientists and is aimed at conference organizers and funders in the field of cell biology. In this piece, I, a person who identifies as a disabled scientist, advocate for collective action within the cell biology community to promote the routine inclusion of accessibility officers on conference organizing panels and the use of accessibility checklists as part of applications for conference funding in order to build inclusive practices into conference planning and organization. I propose a move away from requiring personal disclosures of disability needs on a person-to-person basis towards community-agreed guidelines that ensure accessibility for scientists with a wide variety of needs. To that end, I detail a list of practical, cost-effective adjustments to standard conference activities that can enhance accessibility. Moreover, I suggest several long-term, high-impact changes - including guaranteeing the availability of wheelchair-accessible facilities and making hybrid meeting formats standard - aimed at enabling conference participation for all scientists.