Field Of Life Sciences Research Articles

Analysis of Macromolecular Systems as Enabler for Energy and Life Science Applications

AbstractIdeas concerning the conceptual existence of macromolecular and colloidal systems found their inception at the beginning of the last century. The experimental technology developed to discover and characterize those systems can be associated with seminal pioneers laying the foundations for microscopic, hydrodynamic, and light scattering approaches. In this perspective, we focus our attention on the origins of the discovery and characterization of macromolecular and colloidal systems with selected examples from the beginnings to the present. This perspective attempts to directly interconnect the design of new macromolecular as well as colloidal systems and the simultaneous development of using advanced characterization techniques for design verification. While not claiming a complete coverage of the entire field of modern polymer science, our selected examples concern the field of life science and the recently and rapidly developing area of energy materials.

Activity of Mangrove-Derived Fusarium equiseti 20CB07RF Extract Against Clinical, Antibacterial-Resistant Pseudomonas aeruginosa

Endophytic fungi originating from mangroves are potential sources of secondary metabolites with varying bioactivities. This research explores the bioactive metabolites produced by endophytes derived from mangrove plants. Endophytic fungi were collected from various parts of several mangrove plants (roots, stems, and leaves, as well as the surrounding mud). A total of 17 endophytics fungi were obtained. The isolates were derived from the leaves (1 isolate), stems (8 isolates), roots (5 isolates), and surrounding mud (3 isolates). A single fungal colony was cultured using solid-state fermentation for 14 days. The fermented fungal biomass was extracted using ethyl acetate (EtOAc) and evaluated for its antibacterial activity against clinical pathogenic bacteria. In the preliminary screening, the EtOAc extract of the CB07RF1 isolate exhibited notable growth-inhibitory effects against Pseudomonas aeruginosa. The isolate was verified by molecular identification using a study of the rDNA internal transcribed spacer (ITS) sequence, revealed that isolate CB07RF1 was very similar to Fusarium equiseti (99% similarity). Isolate 20CB07RF1, obtained by solid-state fermentation using a rice medium indicated as peptide compound group, and featured active components that exhibited potent growth inhibitory activity against Pseudomonas aeruginosa at a concentration of 12.5 mg/mL. This study demonstrates, for the first time, that Fusarium equiseti extracts grown in a rice medium contain antimicrobial compounds that can inhibit the growth of P. aeruginosa, an important clinical pathogen known for its antibacterial resistance. These findings accent mangrove endophytic fungi as important sources of bioactive compounds and will advance related research in the fields of biotechnology, pharmacology, and life sciences.

A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes.

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

Refraction color based contact detection for single cell micromanipulation: a cornerstone for precise automation

Abstract Single cell studies represent a cutting-edge field in life science. For cells growing on a soft substrate, a precise micromanipulation is indispensable in order for high-quality single-cell sampling. The foundation of micromanipulation is the accurate triaxial movement control, of which the major challenge lies in the z-axis positioning. Conventional methods rely on manual operation but are hampered by low efficiency. Resorting to additional sensors and cameras might help, whereas the system configuration becomes inevitably complicated. In this work, a vision-based approach utilizing interface refraction color is reported. By monitoring the color change induced by refraction during the contact process, we realized an accurate movement control of the end-effector. The reported method is capable of detecting the z-axis contact between the capillary tip and the substrate in a fully automated manner. Tested by 70 batches of a total of 3840 images, the proposed technique achieves an overall accuracy of 94.28% with precision of 2.73 μm, sufficing in the applications of single cell sampling. Detecting z-axis contact by interface refraction color marks an innovative computer vision method and it is proposed and validated in this work. Our method holds a promise of being a potent part of a close-loop control mechanism for automated single cell micromanipulation.

Two dimensional alkaline earth metal sensors (2D-AEMS) of fluorescent strontium sulfide nanosheets for neurotransmitter drug detection via photo induced electron transfer (PIET)

A new sensing platform has been introduced that provides a powerful solution for fluorescence-based biosensors using photoluminescent nanosheets (NS) using the novel two dimensional alkaline earth metal sensors (2D-AEMS). We have synthesized two-dimensional (2D) fluorescent strontium sulfide (SrS) NS using deep eutectic solvent (DES) as green solvent media by a hydrothermal method. The resulting product of 2D SrS NS to enhance the fluorescence intensity was achieved successfully followed by probe ultrasonication. The optical properties of SrS NS were studied by UV–visible and photoluminescence (PL) spectroscopy. The 2D SrS NS showed a blueish-green fluorescence optimized at λex320 nm/λem390 nm and a quantum yield of 38.6% was calculated. Under optimal conditions, the fluorescent SrS NS effectively detected noradrenaline (NA) by PIET-based fluorescence quenching and wavelength shifts were observed. Our proposed 2D-AEMS of 2D SrS NS fluorescence intensity was quenched in a wide linear range from 1 to 300 µM, with a limit of detection (LOD = 3*3SD/S) of 0.047 µM. The 2D-AEMS (fluorescent SrS NS) was applied to the determination of NA in human urine samples, with good recovery ranging from 98.7-100.08%. Also, the SrS NS fluorescence quenching mechanism in the detection of NA was investigated by zeta potential analysis, UV analysis, and dynamic light scattering (DLS). Our proposed 2D SrS NS fluorescence nanomaterials stand as an innovative platform for generating fluorescence sensors, with extensive potential applications in medical, biological, and life science fields, designed to replace traditional dye fluorescence in the near future.

Fluorescent carbon nanodot-based rapid cell nucleus staining and application for diagnosis.

Cell nucleus status decides the activities of corresponding cells, making its rapid and effective staining important for revealing the actual condition of biological environment in life science and related fields. In this study, fast staining of cell nucleus is realized by fluorescent carbon nanodots (CDs). The staining mechanism is due to the positively charged CD surface-induced cell membrane penetration, which facilitates the CD-nucleus binding via electrostatic attraction. The size of cell nucleus is easily measured with fluorescence imaging technique. In addition, the CD-based cell nucleus stain is applied for discriminating the normal and cancer cells by determining the cell-to-nucleus ratio with fluorescence images.

Oxygen-deficiency induced fluorescence nanosensor (ODIFN): Synthesis of Two-Dimensional NayWO4-x·2H2O nanosheets and its application in dopamine detection

Oxygen-deficiency induced fluorescence nanosensor (ODIFN) method applied in the Two-Dimensional nanosheets has been demonstrated in this paper. In this approach, we synthesized the abundant oxygen-deficient Two-Dimensional (2D) NayWO4-x·2H2O nanosheets fluorescence sensors and applied them for highly sensitive and selective dopamine detection. Researchers have been intensively motivated to create novel nanomaterials that enable the effective detection of dopamine (DA) in clinical samples. DA is a significant biomarker for various brain-related diseases such as Parkinson’s disease. We developed 2D NayWO4-x·2H2O nanosheets that exhibited a stable fluorescence emission at λem 360 nm. The non-stochiometric Na presenting in 2D nanosheets acts as a defecting agent for oxygen deficiency that results in strong and stable fluorescence. The fabricated fluorescence nanosheets were exhibited for the detection of dopamine with high sensitivity and selectivity. The ODIFN demonstrated a linear range of detection from 50 nM to 2 µM with a limit of detection of 0.31 nM and a very high R2 value of 0.996. Moreover, the sensor performance was evaluated in a biological fluid (blood serum) with results of R2 value of 0.995, which proves the high potential of NayWO4-x·2H2O nanosheets in DA sensing. The ODIFN via the 2D NayWO4-x·2H2O fluorescent sensor is a novel platform for producing artificial fluorescence that can be widely applied in all fields such as medical, biological, and life science fields to replace the traditional dyes that are highly harmful to environments.

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism

BackgroundMicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn’t been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training.ResultsThe experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227.ConclusionsThe model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.Graphical

Advances in the application of AlphaFold2: a protein structure prediction model

Protein structure prediction is an important research field in life sciences and medicine, and it is also a key application scenario of artificial intelligence in scientific research. AlphaFold2 is a protein structure prediction system developed by DeepMind based on deep learning, capable of efficiently generating the atomic-scale spatial structure of a protein from the amino acid sequence. It has demonstrated superior performance in the prediction of protein structures since its inception, thus attracting much attention and research. This paper introduces the model architecture, highlights, limitations, and application progress of AlphaFold2. Furthermore, it briefs the capabilities, highlights, and limitations of several other types of protein structure prediction models and prospects the future development direction in this field.

Short-chain fatty acids: bridges between diet, gut microbiota, and health.

In recent years, gut microbiota has become a hot topic in the fields of medicine and life sciences. Short-chain fatty acids (SCFAs), the main metabolites of gut microbiota produced by microbial fermentation of dietary fiber, play a vital role in healthy and ill hosts. SCFAs regulate the process of metabolism, immune, and inflammation and have therapeutic effects on gastrointestinal and neurological disorders, as well as antitumor properties. This review summarized the production, distribution, and molecular mechanism of SCFAs, as well as their mechanisms of action in healthy and ill hosts. In addition, we also emphasized the negative effects of SCFAs, aiming to provide the public with a more comprehensive understanding of SCFAs.

Detection of Ascorbic Acid by Two-Dimensional Conductive Metal-Organic Framework-Based Electrochemical Sensors.

The realization of efficient and accurate detection of biomolecules has become a key scientific issue in the field of life sciences. With the rapid development of nanotechnology, electrochemical sensors constructed from the superior physical and chemical properties of nanomaterials show faster and more accurate detection. Among nanomaterials, two-dimensional conductive MOF (2D cMOF) is considered to be a star material in electrochemical sensors due to its remarkable conductivity, high porosity, and stability. In this paper, a Cu3(HHTP)2/SPE electrochemical sensor for the detection of ascorbic acid (AA) was constructed by modifying 2D cMOF (Cu3(HHTP)2) on the surface of the screen-printed electrode (SPE). The sensor exhibited excellent catalytic activity in the detection of AA, with a lower detection limit of 2.4 μmol/L (S/N = 3) and a wide linear range of 25-1645 μmol/L. This high catalytic activity can be attributed to the abundant catalytic sites in Cu3(HHTP)2 and the rapid electron transfer between Cu+ and Cu2+, which accelerates the oxidation of AA. This work lays a foundation for the subsequent development of MOFs with special electrochemical catalytic properties and the integration of 2D cMOF into intelligent electrical analysis devices.

The Effects of Questionnaire Length on the Relative Impact of Response Styles in Ambulatory Assessment

Ambulatory assessment (AA) is becoming an increasingly popular research method in the fields of psychology and life science. Nevertheless, knowledge about the effects that design choices, such as questionnaire length (i.e., number of items per questionnaire), have on AA data quality is still surprisingly restricted. Additionally, response styles (RS), which threaten data quality, have hardly been analyzed in the context of AA. The aim of the current research was to experimentally manipulate questionnaire length and investigate the association between questionnaire length and RS in an AA study. We expected that the group with the longer (82-item) questionnaire would show greater reliance on RS relative to the substantive traits than the group with the shorter (33-item) questionnaire. Students (n = 284) received questionnaires three times a day for 14 days. We used a multigroup two-dimensional item response tree model in a multilevel structural equation modeling framework to estimate midpoint and extreme RS in our AA study. We found that the long questionnaire group showed a greater reliance on RS relative to trait-based processes than the short questionnaire group. Although further validation of our findings is necessary, we hope that researchers consider our findings when planning an AA study in the future.

Extraction Optimization, Structure Analysis and Antioxidant Activity of Polysaccharide from Sanghuangporus baumii

Introduction: In this study, we optimized the extraction process, analyzed the structure and assessed the antioxidant activity of Sanghuangporus baumii polysaccharide (SBP). The present results provide important information for the Sanghuangporus baumii polysaccharides in potential natural antioxidant effects. Background: The extraction and structural analysis of polysaccharides from Sanghuangporus has gained significant attention in the fields of chemistry, medicine, and life sciences. There is great significance in maximizing the extraction of polysaccharides from Sanghuangporus and developing their potential products in a scientific and rational manner. Objective: The study was designed to establish an efficient and practical extraction process for SBP, and then investigated the structure and the antioxidant activity. Methods: The Response Surface Methodology (RSM) based on Box-Behnken design was used to explore the ultrasound-assisted extraction of SBP, and the structure of SBP was studied by ultraviolet spectroscopy, infrared spectroscopy and other instrumental analysis methods. The total antioxidant capacity of SBP was studied by the Ferric Reducing Ability of Plasma (FRAP) method, and the scavenging capacity of ABTS+·, DPPH· and OH· was carried out as the index to investigate its antioxidant activity in vitro. Results: The statistical analysis results showed that the optimal conditions for extracting SBP were an ultrasound time of 20.74 min, ultrasound power of 268.40 W and material-liquid ratio of 1:25.71. Under optimal conditions, the experimental yield of SBP was 3.36 ± 0.01%. The RSM optimization process was applied to the experiment of complex enzyme extraction of SBP, and the yield increased to 4.72 ± 0.03%. Structural analysis showed that SBP mainly consisted of glucose, a small amount of mannose and galactose, and the molecular weight distribution was uneven, mainly concentrating in the three parts of 24.5,6.4,2.5 kDa. Moreover, SBP exhibited dose-dependent and strong reducing power and radical scavenging activity. For DPPH·, ABTS+· and OH· radical scavenging assays, IC50 values were 1.505 ± 0.050 mg/ml, 0.065 ± 0.036 mg/ml and 0.442 ± 0.007 mg/ml, respectively. Conclusion: In the present study, a β-linked heteroglucan (SBP) was extracted using the optimized process combining enzymes from the fruiting bodies of Sanghuangporus baumii. SBP exhibited effective and dose-dependent antioxidant activities. Our findings were of great value in terms of developing polysaccharides with potential natural antioxidants.

The policy is dead, long live the policy—Revealing science, technology, and innovation policy priorities and government transitions via network analysis

Abstract Each government has priorities for science, technology, and innovation policies (STIP). How can we identify the changing or reinforced STIP research priorities induced by government transitions? This study aims to unveil the STIP changing structure in the public funding research call contents in Colombia from 2007 to 2022, applying a co-word and network analysis approach to 389 funding research calls. We showed each government’s changing distribution of the betweenness centrality of 334 fields from Health, Life, Physical, and Social Sciences. We found that STIP priorities are getting denser and more diverse in terms of research fields. Despite this complexity, just 14 fields of Life, Physical, and Social Sciences, such as drug discovery, general business, management & accounting, and nature and landscape conservation, maintained their higher strategic relevance despite the government in office. This study maps the short and long-term focus of STIP regardless of the changing political tide inherent in democratic countries.

Contribution to the world of 3D cell products created by bio 3D printing technology and to the life science field

We have been making 3D tissues consist of cells only, based on the corporate philosophy of "contributing to dramatic advances in medical care through the practical application of innovative 3D cell stacking technology." Currently, in the field of regenerative medicine, we are working toward obtaining approval from the Ministry of Health, Labor and Welfare and commercializing large artificial organs that are made from patients' own cells and have functions such as nerve regeneration, osteochondral regeneration, and blood vessels. On the other hand, this three-dimensional cell stacking technology can be extended to technology for culturing cells in an environment similar to the human body, and is expected to serve as a new methodology for evaluating the effects of new products in various fields on living organisms. Therefore, we are planning a business to provide developers of pharmaceuticals, foods, cosmetics, etc. with a small device called "Functional Cell Device (FCD)" that reproduces some of the functions of human organs outside the body. As the first step, we have developed a three-dimensional liver construct (3D mini-liver). The in vitro human liver model has a wide range of usage, such as evaluation of hepatotoxicity of drugs, elucidation of drug metabolism mechanism, and model of liver disease. In this report, we will outline it together with actual examples in regenerative medicine.

Magnesium Oxide Nanoparticles: Biogenic Synthesis and Biomedical Applications

AbstractCurrently, nanotechnology is developing at an exponential rate because of its widespread applications in various fields of life sciences. Traditionally, nanoparticles are fabricated through a variety of physical and chemical approaches but because of their limited efficiency in biomedical applications, biogenic synthesis of nanoparticles has gained much attention. Biogenically fabricated magnesium oxide nanoparticles (MgONPs) possess unique features that enabled their use in therapeutics and environmental biotechnology. Biogenically MgONPs can be fabricated using plant extracts (Manihot esculenta, Rhizophora lamarckii, Ocimum sanctum, rosemary, Bauhinia purpurea, and others), bacteria (S. coelicolor, A. johnsonii RTN), fungi (Aspergillus flavus TFR‐12, Aspergillus brasiliensis TFR 2, white‐button mushroom's) and algae (S. whigti). These biogenically synthesized MgONPs are being reported as antifungal, antioxidant, antibacterial, antipyretic, anti‐inflammatory, and anticancer agents. Moreover, their photocatalytic activity is far being discovered against certain organic dyes. This review focuses on the biogenic synthesis of MgONPs, their applications in therapeutics, and as antimicrobial agents as well as future prospects associated with their applications in the biomedical field.

Stability of switched neutral stochastic functional systems with different structures under high nonlinearity

This paper studies the stability of the hybrid neutral stochastic functional differential equations (NSFDEs) with different structures under highly nonlinear conditions. NSFDEs are of wide suitability for simulating random processes with memory, such as tumor evolution mechanism in life science field. The new stochastic system studied in this paper has completely different system structures in different switching subspaces, and the coefficients are highly nonlinear. Moreover, the neutral term is subject to the Markovian switching. This work fills the gap of the stability analysis for differently structured highly nonlinear neutral stochastic functional systems. By using the Lyapunov functional method and the generalized Khasminskii-type conditions, we first establish the existence and uniqueness theorem as well as the asymptotical bounded property of the unique global solution. Then the important stable properties are obtained including H∞ stability, asymptotic stability and exponential stability in Lp. Finally a numerical example is given to illustrate the effectiveness of the results.

Synthesis, characterization, DFT calculations, and anticancer properties of VI-period and f-block elements-substituted zinc oxide nanopowders

Nanotechnology provides promising ways in which a wide range of new materials can be manufactured which appear to have enormous potential in the field of biomedicine and life sciences. ZnO can be applied in many physical and optical processes and used as a good anti-cancer agent. ZnO NPs are recognized as SAFE or GRAS, non-toxic and biocompatible particles. In this study, wurtzite ZnO samples co-doped by rare earth elements (Tb, Er) were prepared via sol-gel auto-combustion route and their crystallographic structure as well as their morphologies were examined using XRD and TEM techniques. The analysis disclosed that all synthesized products crystallized in a hexagonal structure and the crystallites/particles size diminished with the increase of co-doping content. The electronic structure and optical properties of the different products were assessed using DFT calculations. Doping Tb and Er rare earth elements into ZnO has a significant effect on its optoelectronic properties. The computational study showed that the co-doping of Tb and Er on pure ZnO decreased the band gap and increased the refractive index. The extinction spectrum of pristine ZnO showed a peak in the ultraviolet region at 5 eV, while those of the co-doped ZnO samples displayed stronger peaks in the infrared region (near 0.4 eV). The anticancer properties of Tb/Er co-doped ZnO nanoparticles were examined on cervical cancer (HeLa cells) and colon cancer (HCT-116) by using an in vitro MTT assay. The cell viability assay findings indicated a reduction in HeLa and HCT-116 cells after 48 h of treatment of the synthesized samples. The treatment with co-doped ZnO nanoparticles produced chromatin condensation and formation of apoptotic bodies in HCT-166 cells, which indicates that the prepared co-doped ZnO nanoparticles induced programmed cell death in HCT-116 cells. According to these results, it can be concluded that the prepared Tb/Er co-doped ZnO nanoparticles have promising applications in developing new optoelectronic devices and also in treating cervical and colon cancers.

High‐Resolution 3D Printing of Dual‐Curing Thiol‐Ene/Epoxy System for Fabrication of Microfluidic Devices for Bioassays

AbstractThe customized processing of polymer materials in the microscale by high‐resolution 3D printing provides an easy access to advanced applications in the fields of optics, microfluidics, tissue engineering, and life science. However, the 3D printing of enclosed structures in the scale of tens of microns such as closed microfluidic channels remains a challenge as channel structures often are clogged by residual cured resin. Dual‐curing systems based on off‐stoichiometric thiol‐ene and thiol‐ene/epoxy chemistry are well‐known for adhesive‐free bonding in the fabrication of cast or injection molded microfluidic devices. Herein, the first high‐resolution stereolithography 3D printing of a dual‐curing thiol‐ene/epoxy system in the microscale for the fabrication of customized microfluidic devices is presented. In the first curing step, by high‐resolution 3D printing open microfluidic structures are produced. Consecutively, the microchannels are sealed by adhesive‐free dry bonding upon thermal initiation, producing well‐controlled structures with channel sizes down to 80 µm. Before bonding, the intermediate material allows for tailored surface modification with biotin, which allows for consecutive immobilization of various biomolecules. A DNA‐bioassay with specific patterning is shown in the sealed chip. The presented work paves the way toward the fabrication of customized microfluidic devices for a large range of specific bioassays.

GO@ZnO/CuO sensitive selective detection of lactic acid photoelectrochemistry design of sensors

The photoelectrochemical lactate sensor is a sensor that integrates electrochemical and optoelectronic principles for detecting lactate concentration. Lactic acid is a metabolic product in organisms, and its concentration changes are closely related to the health status of the body. The development of highly sensitive and selective lactic acid sensors is of great significance for fields such as medical diagnosis, exercise physiology, and the food industry. This study used a simple hydrothermal method to prepare CuO and ZnO composite electrodes, with GO flake structures covering the surface of nanoparticles, providing a larger surface area and enhanced interaction. Advanced nanomaterials were used as the working electrode materials for electrochemical sensors, which generate current signals through specific reactions with lactic acid to enhance the sensitivity and stability of the sensors. The limit of detection (LOD) is 0.203 mM. Efficient monitoring of lactate concentration provides a novel and multifunctional method, which is of great significance for promoting research in the fields of medicine and life sciences.