Academic Digital Library for institutions, students, and solo learners

Discovery

Content search and filters

This is the first search surface for the seven content types. Next we will connect full-text search and metadata-specific filters.

Results 1,892

Periodicals

Experimental Molecular Communication Testbed Based on Magnetic Nanoparticles in Duct Flow

Simple and easy to implement testbeds are needed to further advance molecular communication research. To this end, this paper presents an in-vessel molecular communication testbed using magnetic nanoparticles dispersed in an aqueous suspension as they are also used for drug targeting in biotechnology. The transmitter is realized by an electronic pump for injection via a Y-connector. A second pump provides a background flow for signal propagation. For signal reception, we employ a susceptometer, an electronic device including a coil, where the magnetic particles move through and generate an electrical signal. We present experimental results for the transmission of a binary sequence and the system response following a single injection. For this flow-driven particle transport, we propose a simple parameterized mathematical model for evaluating the system response.

Biotechnology• 2018• arXiv
Access Full TextView Details
Periodicals

Simulation of charged nanotubes self-assembly during evaporation of a sessile droplet on a substrate

The ability to control the morphology of the nanotube deposit formed during the evaporation of a sessile droplet on a substrate is of theoretical and practical interest. Such deposits are required for various applications including nanotechnology, medicine, biotechnology, and optronics. In the experiment of Zhao et al. [J. Colloid Interface Sci. 440, 68 (2015)], an annular deposit was formed near the contact line. The deposition geometry is caused by the coffee ring effect. This deposit is unusual in its morphology. It changes gradually in space from a disordered structure in the inner part of the ring to an aligned structure of nanotubes close to the periphery. To understand the mechanisms that lead to this, we have developed a mathematical model that takes into account the effects of advection, diffusion, and electrostatic interactions on particle transport. Results of numerical calculations have confirmed that all these factors together have an influence on the formation of such a variable morphology. Qualitative agreement with the experiment is shown for some values of the model parameters.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Scalable HPC and AI Infrastructure for COVID-19 Therapeutics

COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE recently established the Medical Therapeutics project as part of the National Virtual Biotechnology Laboratory, and tasked it with creating the computational infrastructure and methods necessary to advance therapeutics development. We discuss innovations in computational infrastructure and methods that are accelerating and advancing drug design. Specifically, we describe several methods that integrate artificial intelligence and simulation-based approaches, and the design of computational infrastructure to support these methods at scale. We discuss their implementation and characterize their performance, and highlight science advances that these capabilities have enabled.

Biotechnology• 2020• arXiv
Access Full TextView Details
Periodicals

Exploring Latent Space for Generating Peptide Analogs Using Protein Language Models

Generating peptides with desired properties is crucial for drug discovery and biotechnology. Traditional sequence-based and structure-based methods often require extensive datasets, which limits their effectiveness. In this study, we proposed a novel method that utilized autoencoder shaped models to explore the protein embedding space, and generate novel peptide analogs by leveraging protein language models. The proposed method requires only a single sequence of interest, avoiding the need for large datasets. Our results show significant improvements over baseline models in similarity indicators of peptide structures, descriptors and bioactivities. The proposed method validated through Molecular Dynamics simulations on TIGIT inhibitors, demonstrates that our method produces peptide analogs with similar yet distinct properties, highlighting its potential to enhance peptide screening processes.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Thiolation and PEGylation of silicon carbide nanoparticle

In this study, we implement thiol termination on the surface of few-nanometer-sized silicon carbide (SiC) nanoparticles (NPs) to enable further applications, such as fluorescent biomarkers. Various spectroscopic techniques are employed to monitor the effectiveness of the surface treatment. A thiol-Michael addition reaction is performed by conjugating 4-arm PEGmaleimide molecules to the thiol groups of SiC NPs, further demonstrating the reactivity of thiol-terminated SiC NPs, which also acts as a protection layer against oxidation. These fluorescent thiolated SiC NPs, both with and without conjugated molecules, are directly applicable as bioinert probes. Since SiC NPs can potentially host room-temperature fluorescent defect quantum bits, our results are an important step to realize a bioinert, ultrasmall quantum sensor bioagents, which may open new avenues in biotechnology.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Diagnosing Heterogeneous Dynamics in Single Molecule/Particle Trajectories with Multiscale Wavelets

We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large datasets generated in single molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistically adaptive universal thresholding, whose advantage is to avoid a single arbitrary threshold that might conceal individual variability across populations. How to implement this multiscale method is described, focusing on local confined diffusion separated by transient transport periods or hopping events, with 3 specific examples: in cell biology, biotechnology, and glassy colloid dynamics. This computationally-efficient method can run routinely on hundreds of millions of data points analyzed within an hour on a desktop personal computer.

Biotechnology• 2013• arXiv
Access Full TextView Details
Periodicals

Experimental demonstration of kinetic proofreading inherited in ligation-based information replication

We experimentally demonstrate that information replication by templated ligation of DNA strands inherits a kinetic proofreading mechanism and achieves significant error suppression through cascade replication. A simple simulation model derived from the experimental results shows that templated ligation has a significant advantage over replication by polymerization for error suppression of long strands. Specifically, longer chains show lower error rates, significantly distinct from the chain-growth polymerization where errors typically accumulate with chain length. This mechanism provides a plausible route for high-fidelity replication in prebiotic chemistry and illustrates how physical principles such as nonequilibrium kinetics and network architecture can drive reliable molecular information replication. The approach also offers new strategies for error suppression in biotechnology.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Leveraging Sequence Embedding and Convolutional Neural Network for Protein Function Prediction

The capability of accurate prediction of protein functions and properties is essential in the biotechnology industry, e.g. drug development and artificial protein synthesis, etc. The main challenges of protein function prediction are the large label space and the lack of labeled training data. Our method leverages unsupervised sequence embedding and the success of deep convolutional neural network to overcome these challenges. In contrast, most of the existing methods delete the rare protein functions to reduce the label space. Furthermore, some existing methods require additional bio-information (e.g., the 3-dimensional structure of the proteins) which is difficult to be determined in biochemical experiments. Our proposed method significantly outperforms the other methods on the publicly available benchmark using only protein sequences as input. This allows the process of identifying protein functions to be sped up.

Biotechnology• 2021• arXiv
Access Full TextView Details
Periodicals

What if we could hot swap our Biometrics?

What if you could really revoke your actual biometric identity, and install a new one, by live rewriting your biological self? We propose some novel mechanisms for hot swapping identity based in novel biotechnology. We discuss the potential positive use cases, and negative consequences if such technology was to become available and affordable. Biometrics are selected on the basis that they are supposed to be unfakeable, or at least not at reasonable cost. If they become easier to fake, it may be much cheaper to fake someone else's biometrics than it is for you to change your own biometrics if someone does copy yours. This potentially makes biometrics a bad trade-off for the user. At the time of writing, this threat is highly speculative, but we believe it is worth raising and considering the potential consequences.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Predicting Student Actions in a Procedural Training Environment

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are firstly grouped into clusters. Then an extended automaton is created for each cluster based on the sequences of events found in the cluster logs. The main objective of this model is to predict the actions of new students for improving the tutoring feedback provided by an intelligent tutoring system. The proposed model has been validated using student logs collected in a 3D virtual laboratory for teaching biotechnology. As a result of this validation, we concluded that the model can provide reasonably good predictions and can support tutoring feedback that is better adapted to each student type.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Dynamic modeling and predictive control of a microfluidic system

Microfluidics, the study of fluids in microscopic channels, has led to important advances in fields as diverse as microelectronics, biotechnology and chemistry. Microfluidic research is primarily based on the use of microfluidic chips, low-cost devices that can be used to perform laboratory experiments using small amounts of fluid. These systems, however, require advanced control mechanisms in order to accurately achieve the flow rates and pressures required in the experiments. In this paper, we present the design of a model predictive controller intended to regulate the fluid flows in one of these systems. The results obtained, both through simulations and real experiments performed on the device, show that predictive control is an ideal technique to control these systems, especially taking into account all the existing constraints.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Thermal fluctuations of magnetic nanoparticles

The reversal time (superparamagnetic relaxation time) of the magnetization of fine single domain ferromagnetic nanoparticles owing to thermal fluctuations plays a fundamental role in information storage, paleomagnetism, biotechnology, etc. Here a comprehensive tutorial-style review of the achievements of fifty years of development and generalizations of the seminal work of Brown [W.F. Brown, Jr., Phys. Rev., 130, 1677 (1963)] on thermal fluctuations of magnetic nanoparticles is presented. Analytical as well as numerical approaches to the estimation of the damping and temperature dependence of the reversal time based on Brown's Fokker-Planck equation for the evolution of the magnetic moment orientations on the surface of the unit sphere are critically discussed while the most promising directions for future research are emphasized.

Biotechnology• 2012• arXiv
Access Full TextView Details
Periodicals

A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences

Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning motif finding in the biomolecular data are recorded in the DNA Patent Database which serves as a resource for policy makers and members of the general public interested in fields like genomics, genetics and biotechnology. In this paper we present a computational approach to mining for RNA tertiary motifs in genomic sequences. Specifically we describe a method, named CSminer, for finding RNA coaxial helical stackings in genomes. A coaxial helical stacking occurs in an RNA tertiary structure where two separate helical elements form a pseudocontiguous helix and provides thermodynamic stability to the molecule as a whole. Experimental results demonstrate the effectiveness of our approach.

Biotechnology• 2017• arXiv
Access Full TextView Details
Periodicals

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance for technological applications in interdisciplinary fields such as biotechnology, medicine and advanced materials. Here we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO2) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption.

Biotechnology• 2015• arXiv
Access Full TextView Details
Periodicals

Representing Information on DNA using Patterns Induced by Enzymatic Labeling

Enzymatic DNA labeling is a powerful tool with applications in biochemistry, molecular biology, biotechnology, medical science, and genomic research. This paper contributes to the evolving field of DNA-based data storage by presenting a formal framework for modeling DNA labeling in strings, specifically tailored for data storage purposes. Our approach involves a known DNA molecule as a template for labeling, employing patterns induced by a set of designed labels to represent information. One hypothetical implementation can use CRISPR-Cas9 and gRNA reagents for labeling. Various aspects of the general labeling channel, including fixed-length labels, are explored, and upper bounds on the maximal size of the corresponding codes are given. The study includes the development of an efficient encoder-decoder pair that is proven optimal in terms of maximum code size under specific conditions.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

M13-phage-based star-shaped particles with internal flexibility

We report on the construction and the dynamics of monodisperse star-shaped particles, mimicking, at the mesoscale, star polymers. Such multi-arm star-like particles result from the self-assembly of gold nanoparticles, forming the core, with tip-linked filamentous viruses - M13 bacteriophages - acting as spines in a sea urchin-like structure. By combining fluorescence and dark-field microscopy with dynamic light scattering, we investigate the diffusion of these hybrid spiny particles. We reveal the internal dynamics of the star particles by probing their central metallic core, which exhibits a hindered motion that can be described as a Brownian particle trapped in a harmonic potential. We therefore show that the filamentous viruses and specifically their tip proteins behave as entropic springs, extending the relevance of the study of such hybrid mesoscopic analogs of star polymers to phage biotechnology.

Biotechnology• 2023• arXiv
Access Full TextView Details
Periodicals

"Betweenness Centrality" as an Indicator of the "Interdisciplinarity" of Scientific Journals

In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation Reports of the Science Citation Index and the Social Sciences Citation Index 2004, and then also in relation to local citation environments which can be considered as proxies of specialties and disciplines. Betweenness centrality is shown to be an indicator of the interdisciplinarity of journals, but only in local citation environments and after normalization because otherwise the influence of degree centrality (size) overshadows the betweenness-centrality measure. The indicator is applied to a variety of citation environments, including policy-relevant ones like biotechnology and nanotechnology.

Biotechnology• 2009• arXiv
Access Full TextView Details
Periodicals

Field models and numerical dosimetry inside an extremely-low-frequency electromagnetic bioreactor: the theoretical link between the electromagnetically induced mechanical forces and the biological mechanisms of the cell tensegrity

We have implemented field models and performed a detailed numerical dosimetry inside our extremely-low-frequency electromagnetic bioreactor which has been successfully used in $\textit{in vitro}$ Biotechnology and Tissue Engineering researches. The numerical dosimetry permitted to map the magnetic induction field (maximum module equal to about 3.3 mT) and to discuss its biological effects in terms of induced electric currents and induced mechanical forces (compression and traction). So, in the frame of the tensegrity-mechanotransduction theory of Ingber, the study of these electromagnetically induced mechanical forces could be, in our opinion, a powerful tool to understand some effects of the electromagnetic stimulation whose mechanisms remain still elusive.

Biotechnology• 2019• arXiv
Access Full TextView Details
Periodicals

On the Capacity of DNA Labeling

DNA labeling is a powerful tool in molecular biology and biotechnology that allows for the visualization, detection, and study of DNA at the molecular level. Under this paradigm, a DNA molecule is being labeled by specific k patterns and is then imaged. Then, the resulted image is modeled as a (k + 1)- ary sequence in which any non-zero symbol indicates on the appearance of the corresponding label in the DNA molecule. The primary goal of this work is to study the labeling capacity, which is defined as the maximal information rate that can be obtained using this labeling process. The labeling capacity is computed for any single label and several results are provided for multiple labels as well. Moreover, we provide the optimal minimal number of labels of length one or two that are needed in order to gain labeling capacity of 2.

Biotechnology• 2023• arXiv
Access Full TextView Details
Periodicals

Five-Gene Expression Formula Accurately Detects Hepatocellular Carcinoma Tumors

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Several diagnostic methods, such as imaging modalities and Serum Alpha-Fetoprotein (AFP) testing, have been used for HCC detection; however, their effectiveness is limited to later stages of the disease. In contrast, transcriptomic analysis of biposy samples has shown promise for early detection. While machine learning techniques have been applied to transcriptomic data for cancer detection, their clinical adoption remains limited due to challenges such as poor generalizability across different datasets, lack of interpretability, and high computational complexity. To address these limitations, we developed a novel predictive formula for HCC detection using the Kolmogorov-Arnold Network (KAN). This formula is based on the expression levels of five genes: VIPR1, CYP1A2, FCN3, ECM1, and LIFR. Derived from the GSE25097 dataset, the formula offers a simple, interpretable, efficient, and accessible approach for HCC identification. It achieves 99% accuracy on the GSE25097 test set and demonstrates robust performance on six additional independent datasets, achieving accuracies of above 90% in all cases. These findings highlight the critical role of these five genes as biomarkers for HCC detection, offering a foundation for future research and clinical applications to improve HCC diagnostic approaches.

Biotechnology• 2025• arXiv
Access Full TextView Details
Periodicals

Time-dependent invasion laws for a liquid-liquid displacement system

Capillary-driven flow of fluids occurs frequently in nature and has a wide range of technological applications in the fields of industry, agriculture, medicine, biotechnology, and microfluidics. By using the Onsager variational principle, we propose a model to systematically study the capillary imbibition in titled tubes, and find different laws of time-dependent capillary invasion length for liquid-liquid displacement system other than Lucas-Washburn type under different circumstances. The good agreement between our model and experimental results shows that the imbibition dynamics in a capillary tube with a prefilled liquid slug can be well captured by the dynamic equation derived in this paper. Our results bear important implications for macroscopic descriptions of multiphase flows in microfluidic systems and porous media.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Utilizing of protein splicing phenomenon for optimization of obtaining and purification of the recombinant human growth hormone

Protein splicing is a post-translational autocatalystic excision of internal protein sequence (intein) with the subsequent ligation of the flanking polypeptides (exteins). The high specificity of excision ensured by intein makes it possible to use a phenomenon of protein splicing for the biotechnology purposes. The aim of this work was optimization of obtaining and purification of the recombinant human growth hormone using the protein splicing. It was experimentally demonstrated that the use of modified intein as auto-removal affine marker makes it possible to perform the rapid and cheap isolation of the recombinant protein Hgh. Furthermore, this approach allows to obtain the human growth hormone with native N-terminus, without formyl-metionine. Key words: intein, human growth hormone, protein splicing

Biotechnology• 2006• arXiv
Access Full TextView Details
Periodicals

Microfinance in Thailand: Navigating Challenges and Unlocking Opportunities

This review article explores the challenges and opportunities faced by the Bank for Agriculture and Agricultural Cooperatives (BAAC) in Thailand from a microfinance perspective. It examines the role of BAAC as a specialized financial institution in assisting underprivileged households and small businesses in accessing financial services. The study emphasizes the challenges and opportunities faced by BAAC in promoting sustainable development. It also explores BAAC's role in advancing the BCG Model policy, which fosters sustainability in the agricultural sector through Bio Economy Credit, Circular Economy Credit, and Green Credit. These initiatives support investments in biotechnology, waste reduction (Zero Waste), organic farming, and safe food production, all aimed at enhancing farmers' quality of life, stimulating growth in agriculture, and preserving the environment. Moreover, BAAC remains committed to upholding transparency, fairness, and operational standards.

Biotechnology• 2024• arXiv
Access Full TextView Details
Periodicals

Manipulation, trapping, splitting and merging of water and aqueous bio-droplets by photovoltaic optoelectronic tweezers

Optical and optoelectronic techniques for micro- and nano-object manipulation are becoming essential tools in nano- and bio-technology. A remarkable optoelectronic technique that has experimented a strong development in the last few years is the so called photovoltaic optoelectronic tweezers. It is based on the light-induced electric fields generated by the bulk photovoltaic effect in certain ferroelectrics such as LiNbO3. The technique is simple and versatile, enabling a successful manipulation of a large variety of micro- and nano-objects with only optical control, without the need of electrodes or power supplies. However, it is still a challenge for this tool, to handle objects immersed in aqueous solution due to the electric screening effects of polar liquids. This has hindered their application in biotechnology and biomedicine where most processes develop in aqueous solution. In this work, a new efficient route to overcome this problem has been proposed and demonstrated. It uses photovoltaic optoelectronic tweezers to manipulate aqueous droplets, immersed in a non-polar oil liquid, but hanging at the interface air-oil. In this singular configuration, the high electric fields generated in the photovoltaic substrate allow a simple and flexible manipulation of aqueous droplets controlled by the light. Droplet guiding, trapping, merging and splitting have been achieved and efficient operation with water and a variety of bio-droplets (DNA, sperm, and PBS solutions) have been demonstrated. The reported results overcome a main limitation of these tweezers to handle bio-materials and promises a high potential for biotechnological and biochemistry applications including their implementation in optofluidic devices.

Biotechnology• 2020• arXiv
Access Full TextView Details
Previous1...1617181920...79Next