Biological Systems Research Articles

Network analysis of the proteome and peptidome sheds light on human milk as a biological system

Proteins and peptides found in human milk have bioactive potential to benefit the newborn and support healthy development. Research has been carried out on the health benefits of proteins and peptides, but many questions still need to be answered about the nature of these components, how they are formed, and how they end up in the milk. This study explored and elucidated the complexity of the human milk proteome and peptidome. Proteins and peptides were analyzed with non-targeted nanoLC-Orbitrap-MS/MS in a selection of 297 milk samples from the CHILD Cohort Study. Protein and peptide abundances were determined, and a network was inferred using Gaussian graphical modeling (GGM), allowing an investigation of direct associations. This study showed that signatures of (1) specific mechanisms of transport of different groups of proteins, (2) proteolytic degradation by proteases and aminopeptidases, and (3) coagulation and complement activation are present in human milk. These results show the value of an integrated approach in evaluating large-scale omics data sets and provide valuable information for studies that aim to associate protein or peptide profiles from biofluids such as milk with specific physiological characteristics.

Fourth industrial revolution and Human Resources Management: Evidence from developing economies

There is no gainsaying that Industry 4.0 further scales up human resources management capability and enable upper hand to organization, such that the Fourth Industrial Revolution (4IR), characterizes the integration of digital, physical, and biological systems, with profound influence on HRM through the utilization of machine learning (ML) and the Internet of Things (IoT) from recruitment and selection, employee training and development, performance management, employee engagement and satisfaction, workforce planning and optimization, and data-driven decision making. It was against this background that this study engaged the Resource-based view to explain internet of things (IoT) and machine learning (ML) as constructs of human resource management to measure influence of Industry 4.0. Survey research design was adopted, and census sampling technique was used in the study. Sixty six (66) respondents were administered structured questionnaire that underwent validity and reliability test to ascertain survey validity, accuracy and consistency. The findings showed that there is significant effect of internet of things and machine learning on human resource management. Hence this study recommends that existing software, IoT, and sensors should be taken delivery of by the institution for the ICT unit to optimize her IoT interface. The study also recommends that ICT staff should be trained and re-trained on trending machine learning algorithms so they can build and use computer systems that are able to learn and adapt without explicit instructions.

Advancing wastewater treatment technologies: The role of chemical engineering simulations in environmental sustainability

Wastewater treatment stands as a critical component in mitigating environmental pollution and safeguarding public health. This review delves into the pivotal role of chemical engineering simulations in advancing wastewater treatment technologies towards enhanced environmental sustainability. The modernization of wastewater treatment processes necessitates a comprehensive understanding of the complex physical, chemical, and biological interactions involved. Chemical engineering simulations offer a powerful toolset for modeling and optimizing these processes with a focus on efficiency, effectiveness, and sustainability. Firstly, simulations enable the prediction and analysis of pollutant removal mechanisms within treatment systems. By simulating various operating conditions and configurations, engineers can optimize treatment processes to achieve higher removal efficiencies while minimizing resource consumption and waste generation. Secondly, simulations aid in the design and development of innovative treatment technologies, such as membrane filtration, advanced oxidation processes, and biological nutrient removal systems. Through computational modeling, engineers can assess the performance and feasibility of these technologies under different scenarios, facilitating informed decision-making and accelerating their implementation. Furthermore, chemical engineering simulations play a crucial role in addressing emerging challenges in wastewater treatment, including the removal of emerging contaminants such as pharmaceuticals, microplastics, and endocrine-disrupting chemicals. By simulating the behavior of these contaminants within treatment systems, engineers can devise targeted strategies for their removal, thus mitigating their adverse environmental and public health impacts. Chemical engineering simulations serve as indispensable tools for advancing wastewater treatment technologies towards greater environmental sustainability. By facilitating the optimization, design, and innovation of treatment processes, simulations contribute to the development of more efficient, cost-effective, and environmentally friendly solutions for managing wastewater and protecting our ecosystems. Embracing these simulation-driven approaches is essential for achieving the ambitious goals of sustainable development and ensuring a cleaner, healthier future for generations to come.

Application of Genetic Algorithms for Medical Diagnosis of Diabetes Mellitus

The system of glucose-insulin control and associated problems in diabetes mellitus were studied by mathematical modeling. It is a helpful theoretical tool for understanding the basic concepts of numerous distinct medical and biological functions. It delves into the various risk factors contributing to the onset of diabetes, such as sedentary lifestyle, obesity, family history, viruses, and increasing age. The study emphasizes the importance of mathematical models in understanding the dynamic characteristics of biological systems. The study emphasizes the increasing prevalence of diabetes, especially in India, where urbanization and lifestyle changes contribute to the rising incidence. The present investigation describes the use of John Holland's evolutionary computing approach and the Genetic Algorithm (GA) in diabetes mellitus. The Genetic Algorithm is applied to address issues related to diabetes, offering a generic solution and utilizing MATLAB's Genetic Algorithm tool. The Mathematical Model provides differential equations representing glucose and insulin concentrations in the blood. The results represent testing outcomes for normal, prediabetic, and diabetic individuals, optimized with Genetic Algorithm showcased through fitness value plots. The conclusion highlights the effectiveness of Genetic Algorithm as an optimization tool in predicting optimal samples for diabetes diagnosis. The paper encourages the use of heuristic algorithms, such as Genetic Algorithms, to address complex challenges in the field of diabetes research. Future scope includes further exploration of biomathematics and Genetic Algorithm applications for enhanced understanding and management of diabetes mellitus. It is critical for people with diabetes to consistently check their blood glucose levels and follow their treatment plan.

Multifactorial effects of <i>Lactobacillus paracasei DG</i> in the regulation of the microbial-tissue complex: A review

The human gut microbiome is a complex biological system whose functions and metabolic processes are the result of multiple interactions between microbial groups. Within these groups and between them, specific relationships are formed that allow duplicating and reserving individual functions, systematically managing their implementation and, in general, ensuring the reliable functioning of the entire microbiome, including in the interests of the host macroorganism. The functional and metabolic microbial nucleus plays a crucial role in the functioning of microbiocenosis as a whole system. Due to its natural properties, the modern probiotic Lactobacillus paracasei DG performs the function of a conductor of the microbiocenosis of the gastrointestinal tract, regulating the metabolic activity of the intestinal normoflora, realizing immunotropic effects due to the production of exopolysaccharides, including previously unknown exopolysaccharides b, maintaining the integrity of the intestinal epithelial barrier, exerting antiviral action, exerting distant effects against microbiocenoses of other ecological niches.

Study on ESIPT process of fluorescence probe BT-ITC for detecting H2S in DMF/H2O mixed solution

A probe molecule named BT-ITC with an isothiocyanate group was synthesized and evaluated for its H2S sensing ability based on the excited state intramolecular proton transfer (ESIPT) process J K Kim, S Y Bong, R Park, J Park, D Ok Jang 2022 An ESIPT-based fluorescent turn-on probe with isothiocyanate for detecting hydrogen sulfide in environmental and biological systems, Spectrochimica Acta Part A 278 121333. The BT-ITC molecule has a large Stokes shift, short response time, and low detection limit. The end result of the reaction between the molecules BT-ITC and H2S is the BTC-NH2 molecule. The hydrogen bond of the Enol structure BTC-NH2 molecule in excited-state (S1 state) is strengthened, compared to the ground-state (S0 state). The calculated absorption and fluorescence spectra were in good agreement with the experimental values. The frontier molecule orbitals (FMOs), the potential energy curve (PEC), and scatter plots of reduced density gradient (RDG) were calculated. According to aforementioned, it was discovered that the charges of BTC-NH2 molecule were rearranged via an electron transition brought on by photoexcitation. This changes the acidity and alkaline of the proton donor and acceptor, and thus promotes the ESIPT process.

Deciphering the Roles of Interfacial Amino Acids in Inter-Protein Charge Transport.

Elucidating charge transport (CT) through proteins is critical for gaining insights into ubiquitous CT chain reactions in biological systems and developing high-performance bioelectronic devices. While intra-protein CT has been extensively studied, crucial knowledge about inter-protein CT via interfacial amino acids is still absent due to the structural complexity. Herein, by loading cytochrome c (Cyt c) on well-defined peptide self-assembled monolayers to mimic the protein-protein interface, we provide a precisely controlled platform for identifying the roles of interfacial amino acids in solid-state CT via peptide-Cyt c junctions. The terminal amino acid of peptides serves as a fine-tuning factor for both the interfacial interaction between peptides and Cyt c and the immobilized Cyt c orientation, resulting in a nearly 10-fold difference in current through peptide-Cyt c junctions with varied asymmetry. This work provides a valuable platform for studying CT across proteins and contributes to the understanding of fundamental principles governing inter-protein CT.

Room temperature 3D carbon microprinting

Manufacturing custom three-dimensional (3D) carbon functional materials is of utmost importance for applications ranging from electronics and energy devices to medicine, and beyond. In lieu of viable eco-friendly synthesis pathways, conventional methods of carbon growth involve energy-intensive processes with inherent limitations of substrate compatibility. The yearning to produce complex structures, with ultra-high aspect ratios, further impedes the quest for eco-friendly and scalable paths toward 3D carbon-based materials patterning. Here, we demonstrate a facile process for carbon 3D printing at room temperature, using low-power visible light and a metal-free catalyst. Within seconds to minutes, this one-step photocatalytic growth yields rod-shaped microstructures with aspect ratios up to ~500 and diameters below 10 μm. The approach enables the rapid patterning of centimeter-size arrays of rods with tunable height and pitch, and of custom complex 3D structures. The patterned structures exhibit appealing luminescence properties and ohmic behavior, with great potential for optoelectronics and sensing applications, including those interfacing with biological systems.

Two-Photon Microscopy for the Study of Tendons.

Two-photon microscopy has emerged as a potent tool for evaluating deep tissue cells and characterizing the alignment of the extracellular matrix (ECM) in various biological systems. This technique relies on nonlinear light-matter interactions to detect two distinct signals: the second harmonic generated (SHG) diffusion signal, which facilitates the visualization of collagen fibers and their orientation, and the near-infrared excitation signal for imaging ultraviolet excited autofluorescence. SHG imaging proves especially effective in visualizing collagen fibers due to the non-centrosymmetric crystalline structure of fibrillar collagen I. Given that tendons are matrix-rich tissues with a limited number of cells, their high collagen content makes them ideal candidates for analysis using two-photon microscopy. Consequently, two-photon microscopy offers a valuable means to analyze and characterize collagen abnormalities in tendons. Its application extends to studying tendon development, injuries, healing, and aging, enabling the comprehensive characterization of tendon cells and their interactions with the ECM under various conditions using two-photon microscopy tools. This protocol outlines the use of two-photon microscopy in tendon biology and presents an adapted methodology to achieve effective imaging and characterization of tendon cells during development and after injury. The method allows the utilization of thin microscopic sections to create a comprehensive image of the ECM within tendons and the cells that interact with this matrix. Most notably, the article showcases a technique to generate 3D images using two-photon microscopy in animal models.

Two-Terminal Perovskite Optoelectronic Synapse for Rapid Trained Neuromorphic Computation with High Accuracy.

Emerging neural morphological vision sensors inspired by biological systems that integrate image perception, memory, and information computing are expected to transform the landscape of machine vision and artificial intelligence. However, stable and reconfigurable light-induced synaptic behavior always relies on independent gateport modulation. Despite its potential, the limitations of uncontrollable defects and ionic characteristics have led to simpler, smaller, and more integration-friendly two-terminal devices being used as sidelines. In this work, the synergy between ion migration barriers and readout voltage was proven to be the key to realizing stable, reconfigurable, and precisely controllable postsynaptic current in two-terminal devices. Following the same mechanism, optical and electrical signal synchronous triggering is proposed to serve as a preprocessing method to achieve a recognition accuracy of 96.5%. Impressively, the gradual ion accumulation during the training process induces photocurrent evolution, serving as a reference for the dynamic learning rate and boosting accuracy to 97.8% in just 10 epochs. The PSC modulation potential under short optical pulse of 20 ns is also revealed. This optoelectronic device with perception, memory, and computation capabilities can promote the development of new devices for future photonic neural morphological circuits and artificial vision. This article is protected by copyright. All rights reserved.

Solvation of Model Biomolecules in Choline-Aminoate Ionic Liquids: A Computational Simulation Using Polarizable Force Fields.

One can foresee a very near future where ionic liquids will be used in applications such as biomolecular chemistry or medicine. The molecular details of their interaction with biological matter, however, are difficult to investigate due to the vast number of combinations of both the biological systems and the variety of possible liquids. Here, we provide a computational study aimed at understanding the interaction of a special class of biocompatible ionic liquids (choline-aminoate) with two model biological systems: an oligopeptide and an oligonucleotide. We employed molecular dynamics with a polarizable force field. Our results are in line with previous experimental and computational evidence on analogous systems and show how these biocompatible ionic liquids, in their pure form, act as gentle solvents for protein structures while simultaneously destabilizing DNA structure.

Comparative lipidome study of maternal plasma, milk, and lamb plasma in sheep

Lipids play a critical role in neonate development and breastmilk is the newborn’s major source of lipids. Milk lipids directly influence the neonate plasma lipid profile. The milk lipidome is dynamic, influenced by maternal factors and related to the maternal plasma lipidome. The close inter-relationship between the maternal plasma, milk and neonate plasma lipidomes is critical to understanding maternal-child health and nutrition. In this exploratory study, lipidomes of blood and breast milk from Suffolk sheep and matched lamb blood (n = 13), were profiled on day 34 post birth by untargeted mass spectrometry. Comparative multivariate analysis of the three matrices identified distinct differences in lipids and class of lipids amongst them. Paired analysis identified 346 differential lipids (DL) and 31 correlated lipids (CL) in maternal plasma and milk, 340 DL and 32 CL in lamb plasma and milk and 295 DL and 16 CL in maternal plasma and lamb plasma. Conversion of phosphatidic acid to phosphatidyl inositol was the most active pathway in lamb plasma compared to maternal plasma. This exploratory study illustrates the partitioning of lipids across maternal plasma, milk and lamb plasma and the dynamic relationship between them, reiterating the need to study these three matrices as one biological system.

Water Molecules Confined in Cryptophane Nanocages: Structures and Dynamics Driven by Hydrogen Bonding and Water Chains.

Cryptophanes (Crs) are roughly spherical organic nanocages used as vehicles for hosting xenon atoms in 129Xe NMR biosensor (XBS) structures. Crs also bind other guests, importantly water, which is abundant in biological systems. In other host cages, it has been found that the release of "high-energy" water from confinement constitutes an important contribution to the binding affinity of nonwater guests. Despite that, the role of water has received little attention in the XBS field. Based on molecular dynamics simulations in explicit water solvent, we here study the properties of confined water in three different CrA cages that have an identical interior but are functionalized with 0, 3, or 6 water solubility-enhancing, hydrophilic CH2COOH moieties. The number of the solubility groups is found to be a decisive factor for the structures and dynamics of the confined water. Formation of stable water-molecule chains is predicted within the cage with six hydrophilic groups, starting with the anchoring of one water molecule at the portal between the cage and the bulk solution. We find that the experimentally measured differences in the Xe-binding affinities of the cages can be related to the average number of hydrogen bonds per confined water molecule. The rotational dynamics of the confined water is significantly slower than that in the bulk, suggesting NMR relaxation measurements to study the intracavity water. The present findings reveal new details about the microscopic cryptophane-H2O host-guest chemistry, which will become important in the design of improved XBS devices.

PEGylation of NIR Cd0.3Pb0.7S aqueous quantum dots for stabilization and reduction of nonspecific binding to cells

Cd0.3Pb0.7S (CdPbS) aqueous quantum dots (AQDs) made with 3-mercaptoproprionic acid (MPA) as a ligand have the advantages of emitting near-infrared light, well above 800 nm, that completely circumvents interference from tissue autofluorescence and have significant amounts of ligands for bioconjugation. However, retaining the right amount of MPA became a challenge when using CdPbS AQDs for bioimaging because retaining too much MPA could lead to significant nonspecific staining in cell imaging while insufficient MPA could cause AQDs instability in biological systems. Here we examined PEGylation (i.e. chemically linking amine-functionalized polyethylene glycol (PEG)) to modify MPA on the AQDs surface to improve AQDs stability and reduce nonspecific staining. In addition, for conjugation with antibodies, a bifunctional PEG with a carboxyl functionality was used to permit chemical linkage of a PEG to an antibody on the other end. It was found that performing PEGylation at the thiol concentration where the zeta potential becomes saturated stabilized the CdPbS AQDs suspension and reduced nonspecific binding to cells. Furthermore, with the bifunctional PEG, the CdPbS AQDs were conjugated with antibodies and the AQD-Ab conjugates were shown to stain cancer cells specifically against normal cells with a signal-to-noise ratio of 8.

Multiphotonic Ablation and Electro-Capacitive Effects Exhibited by Candida albicans Biofilms

This work reports the modification in the homogeneity of ablation effects with the assistance of nonlinear optical phenomena exhibited by C. albicans ATCC 10231, forming a biofilm. Equivalent optical energies with different levels of intensity were irradiated in comparative samples, and significant changes were observed. Nanosecond pulses provided by an Nd:YAG laser system at a 532 nm wavelength in a single-beam experiment were employed to explore the photodamage and the nonlinear optical transmittance. A nonlinear optical absorption coefficient −2 × 10−6 cm/W was measured in the samples studied. It is reported that multiphotonic interactions can promote more symmetric optical damage derived by faster changes in the evolution of fractional photoenergy transference. The electrochemical response of the sample was studied to further investigate the electronic dynamics dependent on electrical frequency, and an electro-capacitive behavior in the sample was identified. Fractional differential calculations were proposed to describe the thermal transport induced by nanosecond pulses in the fungi media. These results highlight the nonlinear optical effects to be considered as a base for developing photothermally activated phototechnology and high-precision photodamage in biological systems.

ROSPECTS FOR THE USE OF H-REFLEXOMETRY IN THE STUDY OF HUMAN MOTOR FUNCTION

SUMMARY. The article application of H-reflexometry in the study of the central mechanisms of random human movements, which is mainly carried out on healthy subjects, is demonstrated. It has been shown that the results of clinical trials performed by H-reflexometry with the participation of injured people or people with neurological disorders provide additional information about these mechanisms, reveal the causes of human motor function disorders, contribute to the improvement of methods of their study and provide opportunities for the implementation of rehabilitation measures.
 The aim –  to evaluate the prospects of using H-reflexometry in the study of central mechanisms of movements and means of restoring and maximizing the motor capabilities of people.
 Material and Methods. The analysis was carried out using the scientific biological and medical information search system PubMed.
 Results. H-reflexometry was used both for the study of motor functions of healthy people and patients with injuries and neurological disorders. The authors studied mainly H-reflexes m.soleus, m. flexor carpi radialis, m. quadriceps. The total number of publications with the results of studies performed on other muscles indicates the possibility of a wider use of H-reflexometry in the study of motor functions in humans than is generally accepted and currently implemented. It was found that H-reflexometry was used to the greatest extent in the researches of the mechanisms of motor disorders arising as a result of stroke and spinal cord injuries.
 Conclusions. The results of the review indicate that H-reflexometry provides ample opportunities to study human motor function in normal and pathological conditions, and it may be especially promising at present to examine injured people using this method, to implement and monitor their rehabilitation measures.

A putative design for the electromagnetic activation of split proteins for molecular and cellular manipulation.

The ability to manipulate cellular function using an external stimulus is a powerful strategy for studying complex biological phenomena. One approach to modulate the function of the cellular environment is split proteins. In this method, a biologically active protein or an enzyme is fragmented so that it reassembles only upon a specific stimulus. Although many tools are available to induce these systems, nature has provided other mechanisms to expand the split protein toolbox. Here, we show a novel method for reconstituting split proteins using magnetic stimulation. We found that the electromagnetic perceptive gene (EPG) changes conformation due to magnetic field stimulation. By fusing split fragments of a certain protein to both termini of the EPG, the fragments can be reassembled into a functional protein under magnetic stimulation due to conformational change. We show this effect with three separate split proteins: NanoLuc, APEX2, and herpes simplex virus type-1 thymidine kinase. Our results show, for the first time, that reconstitution of split proteins can be achieved only with magnetic fields. We anticipate that this study will be a starting point for future magnetically inducible split protein designs for cellular perturbation and manipulation. With this technology, we can help expand the toolbox of the split protein platform and allow better elucidation of complex biological systems.

Bio-Inspired Robotic Exoskeletons with Adaptive Electrical Control for Enhanced Upper Extremity Rehabilitation

Robotic exoskeletons are a new and hopeful technology for rehabbing the upper limbs. They offer exact control and adjustable help to make traditional treatment more effective. This study suggests a new way to improve the recovery process that combines bio-inspired design with flexible electrical control. It is based on the way biological systems work. The suggested exoskeleton design is biomimetic, meaning that it looks and works like a human arm. This is done to make sure that the person can move naturally and comfortably. Lightweight, flexible materials make up the exoskeleton, which has sensors that track the user's movements and muscle activity. These monitors send input to the control system in real time, which lets it make changes that are more helpful for the user while they do different recovery routines. The control system uses an adaptable electrical treatment method that is based on how the human body controls its muscles. The control system constantly checks the user's muscle action and changes the amount of electrical stimulation to give the best support and help during recovery exercises. This flexible method makes sure that the exoskeleton's help is tailored to the person using it's wants and skills, which helps them recover more quickly. A bio-inspired robotic suit with adjustable electrical control is tested in a set of tests with healthy people and people who have had a stroke. The data show that the exoskeleton improves therapy for the upper limbs by giving individualized help and encouraging natural movement patterns. The adjustable electrical control makes it a lot easier for the user to do recovery exercises, which leads to better performance and a higher quality of life.

A two-step Bayesian network approach to identify key SNPs associated to multiple phenotypic traits in four purebred laying hen lines.

When purebred laying hen chicks hatch, they remain at a rearing farm until approximately 17 weeks of age, after which they are transferred to a laying farm. Chicks or pullets are removed from the flocks during these 17 weeks if they display any rearing abnormality. The aim of this study was to investigate associations between single nucleotide polymorphisms (SNPs) and rearing success of 4 purebred White Leghorns layer lines by implementing a Bayesian network approach. Phenotypic traits and SNPs of four purebred genetic White Leghorn layer lines were available for 23,000 rearing batches obtained between 2010 and 2020. Associations between incubation traits (clutch size, embryo mortality), rearing traits (genetic line, first week mortality, rearing abnormalities, natural death, rearing success, pullet flock age, and season) and SNPs were analyzed, using a two-step Bayesian Network (BN) approach. Furthermore, the SNPs were connected to their corresponding genes, which were further explored in bioinformatics databases. BN analysis revealed a total of 28 SNPs associated with some of the traits: ten SNPs were associated with clutch size, another 10 with rearing abnormalities, a single SNP with natural death, and seven SNPs with first week mortality. Exploration via bioinformatics databases showed that one of the SNPs (ENAH) had a protein predicted network composed of 11 other proteins. The major hub of this SNP was CDC42 protein, which has a role in egg production and reproduction. The results highlight the power of BNs in knowledge discovery and how their application in complex biological systems can help getting a deeper understanding of functionality underlying genetic variation of rearing success in laying hens. Improved welfare and production might result from the identified SNPs. Selecting for these SNPs through breeding could reduce stress and increase livability during rearing.

Small molecule probes for the specific imaging of monoamine oxidase A and monoamine oxidase B

AbstractMonoamine oxidases (MAOs) are a class of flavin enzymes that are mainly present in the outer membrane of mitochondria and play a crucial role in maintaining the homeostasis of monoamine neurotransmitters in the central nervous system. Furthermore, expression of MAOs is associated with the functions of peripheral organs. Dysfunction of MAOs is relevant in a variety of diseases such as neurodegenerative diseases, heart failure, metabolic disorders, and cancers. Monoamine oxidases have two isoenzymes, namely, monoamine oxidase A (MAO‐A) and monoamine oxidase B (MAO‐B). Therefore, the development of reliable and specific methods to detect these two isoenzymes is of great significance for the in‐depth understanding of their functions in biological systems, and for further promoting the clinical diagnosis and treatment of MAO‐related diseases. This review mainly focuses on the advances in small molecular probes for the specific imaging of MAO‐A and MAO‐B, including radiolabeled probes, fluorescent probes, and a 19F magnetic resonance imaging probe. In addition, applications of these probes for detecting MAO expression levels in cells, tissues, animal models, and patients are described. Finally, the challenges and perspectives of developing novel MAO imaging probes are also highlighted.