Biological Systems Research Articles

A taxonomy of multiple stable states in complex ecological communities.

Natural systems are built from multiple interconnected units, making their dynamics, functioning and fragility notoriously hard to predict. A fragility scenario of particular relevance concerns so-called regime shifts: abrupt transitions from healthy to degraded ecosystem states. An explanation for these shifts is that they arise as transitions between alternative stable states, a process that is well-understood in few-species models. However, how multistability upscales with system complexity remains a debated question. Here, we identify that four different multistability regimes generically emerge in models of species-rich communities and other archetypical complex biological systems assuming random interactions. Across the studied models, each regime consistently emerges under a specific interaction scheme and leaves a distinct set of fingerprints in terms of the number of observed states, their species richness and their response to perturbations. Our results help clarify the conditions and types of multistability that can be expected to occur in complex ecological communities.

Simultaneous removal of caesium and strontium using different removal mechanisms of probiotic bacteria

When radioactive materials are released into the environment due to nuclear power plant accidents, they may enter into the body, and exposing it to internal radiation for long periods of time. Although several agents have been developed that help excrete radioactive elements from the digestive tract, only one type of radioactive element can be removed using a single agent. Therefore, we considered the simultaneous removal of caesium (Cs) and strontium (Sr) by utilising the multiple metal removal mechanisms of probiotic bacteria. In this study, the Cs and Sr removal capacities of lactobacilli and bifidobacteria were investigated. Observation using an electron probe micro analyser suggested that Cs was accumulated within the bacterial cells. Since Sr was removed non metabolically, it is likely that it was removed by a mechanism different from that of Cs. The amount of Cs and Sr that the cells could simultaneously retain decreased when compared to that for each element alone, but some strains showed only a slight reduction in removal. For example, Bifidobacterium adolescentis JCM1275 could simultaneously retain 55.7 mg-Cs/g-dry cell and 8.1 mg-Sr/g-dry cell. These results demonstrated the potentials of utilizing complex biological system in simultaneous removal of multiple metal species.

Dicyanoisophorone-based near-infrared fluorescent probe with large Stokes shift for the monitoring and bioimaging of hypochlorite

Hypochlorite (ClO−), as one of reactive oxygen species (ROS), is closely linked to various illnesses and is essential for the proper functioning of immune system. Hence, monitoring and assessing ClO− levels in organisms are extremely important for the clinical diagnosis of ClO−-related disorders. In this study, a novel ClO−-selective fluorescent probe, DCP-ClO, was synthesized with dicyanoisophorone-xanthene unit as parent fluorophore, which displayed excellent selectivity towards ClO−, near-infrared emission (755 nm), large Stokes shift (100 nm), real-time response to ClO−, high sensitivity (LOD = 3.95 × 10−8 M), and low cytotoxicity. The recognition mechanism of DCP-ClO towards ClO− was confirmed to be a typical ICT process by HPLC-MS, HR-MS, 1H NMR and theoretical calculations. Meanwhile, DCP-ClO demonstrated remarkable efficacy in monitoring ClO− levels in water samples and eye-catching ability in imaging endogenous/exogenous ClO− in living organisms, which verified its potential as a powerful tool for the recognition of ClO− in complex biological systems.

Sr6Y(PO4)5: Nd3+ a novel whitlockite-type phosphor for optical temperature sensing applications: Synthesis and luminescence properties

Active research in science and technology is improving the development of materials that emit infrared light, with the aim of better optical thermometric sensors. In this paper we report the synthesis of a new NIR-emitting phosphate phosphor, Sr6Y(PO4)5:Nd3+ (SYP: Nd3+), at differing concentrations of Nd3+ using a conventional solid-state reaction route. X-ray diffraction analysis showed that the prepared phosphors exhibit a singular phase with a monoclinic whitlockite structure (space group I2/a). SEM images show micrometer-sized particle. FTIR and Raman spectroscopies confirm the presence of PO43− groups in the examined phosphates. Luminescence features, comprising emission spectra, concentration quenching, and fluorescence lifetime, were investigated for the prepared SYP: Nd3+ samples at various Nd3+ doping concentrations. Excited at 808 nm, the phosphors emitted near-infrared light with four distinct bands corresponding to specific Nd3+ transitions from 4F3/2 to (4I9/2,4I11/2 and 4I13/2) and 4F5/2 to 4I11/2, falling within the first and second biological windows (NIR-I and NIR-II). Importantly, Nd3+ emission characteristics are affected by concentration and temperature. The powders' effectiveness as optical temperature sensors using fluorescence intensity ratio (FIR) between coupled and non-coupled levels was researched across 303–473 K, resulting in two distinctive FIR-based temperature sensor strategies employing emissions at 874.8 nm (4F3/2 → 4I9/2) and 956 nm (4F5/2 → 4I11/2) transitions, all within the first biological window for excitation and emission. Using this method, SYP: Nd3+ revealed a notably elevated sensitivity of approximately 1.16 %K−1 at 303 K, surpassing other Nd3+-doped materials when stimulated within the infrared range. These results strongly suggest the prospective applicability of the analyzed material in monitoring the temperature of biological systems.

One World Chemistry—IOCD Call for Volunteers

Abstract The International Organization for Chemical Sciences in Development (IOCD) is committed to working in partnership with others to ensure that chemistry fulfils its potential of contributing to sustainability for people and for the physical and biological systems of the planet. A new orientation, “One-World” Chemistry has been proposed, which recognises the interconnectedness of human, animal, and planetary health and embraces the need for chemistry to adopt systems thinking and crossdisciplinary working to tackle the planetary challenges.

Protein Aggregation on Metal Oxides Governs Catalytic Activity and Cellular Uptake.

Engineering of catalytically active inorganic nanomaterials holds promising prospects for biomedicine. Catalytically active metal oxides show applications in enhancing wound healing but have also been employed to induce cell death in photodynamic or radiation therapy. Upon introduction into a biological system, nanomaterials are exposed to complex fluids, causing interaction and adsorption of ions and proteins. While protein corona formation on nanomaterials is acknowledged, its modulation of nanomaterial catalytic efficacy is less understood. In this study, proteomic analyses and nano-analytic methodologies quantify and characterize adsorbed proteins, correlating this protein layer with metal oxide catalytic activity in vitro and in vivo. The protein corona comprises up to 280 different proteins, constituting up to 38% by weight. Enhanced complement factors and other opsonins on nanocatalyst surfaces lead to their uptake into macrophages when applied topically, localizing >99% of the nanomaterials in tissue-resident macrophages. Initially, the formation of the protein corona significantly reduces the nanocatalysts' activity, but this activity can be partially recovered in endosomal conditions due to the proteolytic degradation of the corona. Overall, the research reveals the complex relationship between physisorbed proteins and the catalytic characteristics of specific metal oxide nanoparticles, providing design parameters for optimizing nanocatalysts in complex biological environments.

AI and ML in IR4.0: A Short Review of Applications and Challenges

Artificial intelligence and machine learning are essential for the development of IR4.0 due to their ability to analyse vast amounts of data, automate processes, and drive innovation across various sectors. These technologies enable intelligent decision-making, predictive analytics, and automation, leading to increased efficiency, productivity, and competitiveness in the digital age. In IR4.0, AI and ML power smart systems and connected devices, transforming industries. They facilitate the integration of digital, physical, and biological systems, enabling the creation of personalized medicine and medical diagnosis smart manufacturing, self-autonomous driving vehicles, smart cities, and smart home. Hence, this review aims to address the contribution of AI and ML in the development of medical diagnosis, smart manufacturing, smart cars, smart cities, and smart homes as well as to highlight the existing challenges faced by AI and ML in these fields. This review also showcases the relevant prospects of AI and ML applications in the fields mentioned.

A G-quadruplex/thioflavin T-based label-free biosensor to detect ClO− in stress-induced hypertension

Hypochlorous acid (HClO), as an essential reactive oxygen species (ROS) in biological systems, plays a pivotal role in processes of physiology and pathology. Abnormal fluctuations in HClO concentration can lead to various diseases, such as inflammation, cardiovascular diseases, and neurodegeneration. Therefore, developing an approach to rapidly and sensitively quantify ClO− content is vital to biomedicine development and bioassays. Herein, we fabricated a novel “turn-on” label-free fluorescence DNA probe to specifically detect hypochlorite ion (ClO−) based on G-quadruplex formation. To this end, we designed a G-rich signal DNA sequence (S-DNA) and a block DNA sequence (B-DNA), followed by the introduction of ClO−-responsive phosphorothioate (PS) into B-DNA. In the absence of ClO−, B-DNA hybridized with S-DNA, preventing G-quadruplex formation from S-DNA; this resulted in the relatively low fluorescence intensity of ThT. Once ClO− was added, the hydrolysis between PS and ClO− split the B-DNA into two fragments, resulting in B-DNA breaking away from S-DNA, allowing G-quadruplex formation from S-DNA and increasing the fluorescence intensity of ThT. Using this method, we can detect ClO− without the interference of additional reactive oxygen species. The detection limit of ClO− was as low as 10 nM. Furthermore, this method facilitates the detection of ClO− within the tissues of rats with stress-induced hypertension.

Compare the Performance of Distinct Neural Networks Techniques to diagnose the kidney stone disease

Artificial Neural Networks are excellent at identifying patterns or trends in data, which makes them perfect for forecasting or prediction. Thus, neural networks have extensive application in biological systems. The application of neural networks to kidney stone diagnosis is emphasized in this article. Kidney stone issues can be diagnosed with neural networks by applying technological concepts such as MLP, SVM, RBF, and BPA. The purpose of this research is to use three different neural network algorithms—each with its own specific design and set of properties to identify kidney stone disease. The performance of the three neural networks is compared in this research with respect to training data set size, model creation time, and accuracy. Kidney stone sickness will be diagnosed using radial basis function (RBF) networks, two layers feed forward perceptrons trained with the back propagation training algorithm, and learning vector quantization (LVQ). However, determining the best approach for any particular diagnostic had never been an easy task. Like many other illnesses, kidney stones have already been diagnosed using neural network algorithms. The main objective of this work is to recommend the best medical diagnostic instrument, such as kidney stone detection, to reduce diagnosis times and improve accuracy and efficiency.

Physicochemical characterization of university campus’ wastewater for internal treatment system installation (Casablanca, Morocco)

Today, protecting water resources and their sustainable use has become an obligation of people and organizations. Wastewater management and reclamation are the most important solutions to protect these resources. This study aims to determine the wastewater physicochemical quality of the Faculty of Sciences Ben M'Sick (FSBM) (Casablanca, Morocco) to establish the appropriate system for their treatment and internal reclamation. The results show that averages of FSBM's wastewater temperature vary between 17.64 and 19.55 °C, 7.18 and 8.18 for pH, and 2.47 and 3.98 mS.cm-1 for electrical conductivity.. The COD, BOD5, and TSS average values oscillate respectively between 967.44-1,151.08 mg.L-1, 70.5-119.05 mg.L-1, and 223.64-1,659.74 mg.L-1, and those of total phosphorus between 2 and 3.99 mg.L-1. The determination of the biodegradability degree of the discharge, through the calculation of COD/BOD5, BOD5/COD, TSS/BOD5, COD/TP, COD/NH4+ ratios, and oxidizable matters (OM,) reveals that the FSBM's wastewater has a heterogeneous character with a high load of oxidizable matter difficult to biodegrade. Despite its low biodegradability, the FSBM’s wastewater could be treated using a biological treatment system, preceded by a physicochemical treatment to eliminate non-biodegradable chemical substances. Such a choice of wastewater treatment system requires prior experimental investigations and laboratory tests.

A novel colormetric and light-up fluorescent sensor from flavonol derivative grafted cellulose for rapid and sensitive detection of Hg2+ and its applications in biological and environmental system

Mercury ion (Hg2+) is one of harmful heavy metal ions that can accumulate inside the human organism and cause some health problems. In the article, a highly effective fluorescent probe named EC-T-PCBM was prepared by grafting flavonol derivatives onto ethyl cellulose for the specific recognition of Hg2+. EC-T-PCBM exhibited a remarkable fluorescence light-up response toward Hg2+ with excellent sensitivity. EC-T-PCBM possessed several prominent sensing properties for Hg2+, such as low detection limit (43.9 nM), short response time (5 min), and wide detection pH range (6–9). The response mechanism of EC-T-PCBM to Hg2+ has been verified through 1H NMR titration and DFT computation. Additionally, EC-T-PCBM not only can be used for accurately determining trace amount of Hg2+ in actual environmental water samples, but also can serve as a portable and rapid device by loading it on test strips for sensitive and selective visualization of Hg2+. More importantly, the confocal fluorescence imaging of onion cells suggested the favorable cell membrane permeability of EC-T-PCBM and its prominent ability to continuously monitor the enrichment from Hg2+ within fresh plant tissues.

Environmental Protection Through Sustainable Land Management

Sustainable land planning and successful land use change methods are essential as the world faces rising environmental challenges. This study examines the transformative potential of biomimicry and biophilia in addressing these challenges and the potential of bio-collaboration, bio-utilization, bio-inspiration, biophilic design, and biomimicry in creating a sustainable environment. The argument is that such integration can potentially create creative ways to lessen the effects of human activity on the environment by utilising the knowledge of nature and combining biological system concepts. This study argues that by incorporating the above environmental factors into land planning practises, a holistic and sustainable approach can be achieved, fostering peaceful coexistence between human activities and the natural environment. This will also improve the resilience of urban and rural environments while offering practical solutions for a climate change-conscious world. As the main theoretical contribution, this study synthesizes a theoretical framework in the form of a conceptual structure for understanding, analyzing, and interpreting sustainability by adopting an ecosystem theoretical framework for achieving sustainable land management.
 Keywords: Biophilic Design, Biomimicry, Sustainable Design Strategy, Bio-Collaboration, Biodiversity, Land use Management, Sustainable Land Management, Environmental Protection, Global Climate.
  

Analysis and modeling of forced-damped vibrations and their applications in medicine

Forced-damped vibrations are pivotal in various medical applications, significantly contributing to the examination of tissue mechanical properties, development of medical devices, and understanding of biological systems’ complexities. These vibrations represent the dynamic behavior of systems subjected to external forces and damping, where an external force continues to act, and damping determines the rate of energy dissipation. Advanced exploration of damping properties has led to the creation of novel technologies and methods, enhancing our ability to probe and manipulate the complex mechanical dynamics of biological tissues.

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.

Antioxidant Activity of Bilirubin in Micellar and Liposomal Systems Is pH-Dependent

Bilirubin (BR), a product of heme catabolism, plays a critical role in biological systems. Although increased levels of BR result in hyperbilirubinemia or jaundice, there is increasing evidence that lower concentrations substantially decrease the risk of oxidative stress-mediated diseases due to antioxidant functions of BR. We studied the radical-trapping ability of BR in two model systems, micellar and liposomal, at a broad pH range. At pH < 6.0, BR behaves as a retardant; however, at pH ≥ 6.0, BR becomes strong radical trapping antioxidant, with rate constants for reaction with lipidperoxyl radicals (kinh) within the range from 1.2 × 104 M−1 s−1 to 3.5 × 104 M−1 s−1, and in liposomal system, the activity of BR is comparable to α-tocopherol. This transition is likely facilitated by the ionization of carboxyl groups, leading to a conformational shift in BR and improved solubility/localization at the water/lipid interface. This is the first experimental evidence of the role of pH on the antioxidant activity of bilirubin, and the observed pH-dependent radical-trapping ability of BR holds practical significance, particularly in jaundice treatment where light therapy targets the skin’s weakly acidic surface. Minor adjustments toward neutral or alkaline pH can enhance radical-trapping action of BR, thereby mitigating oxidative stress induced with blue or violet light exposure.

Advances in exploration of photoinduced electron transfer reactions involving small molecules probed by magnetic field effect

The review focuses on photoinduced electron transfer (PET) reactions between small molecules and various kinds of chemical and biological systems using a weak external magnetic field (MF). Laser flash photolysis is a competent tool to characterize the intermediates which are formed due to PET. A weak MF, very close to the hyperfine interaction of the system, has the potential to inhibit or enhance reaction channels for singlet and triplet states, which eventually effects the product distribution. At first, well-documented examples of PET involving small molecules like derivatives of phenazines, carbazoles and acridines with classical electron donors in varying homogeneous and heterogeneous media have been discussed and the influence of a weak MF on the dynamics of PET is highlighted. Secondly, utilization of magnetic field effect (MFE) to probe PET in protein pockets has been described. Thirdly, an extensive discussion on PET involving nucleobases, nucleosides, nucleotides and nucleic acids and subsequent MFE on such reactions has been reported. Next, MFE has been exploited to study PET involving nanomaterials. Finally, some very recent studies of MFE have been discussed. Thus, this review is an attempt to unravel various aspects of PET in a large number of systems of varying dimensions by means of several facets of MFE like B1/2 parameter, its capability to authenticate the initial spin state and distance dependence property.

MHD nanofluid flow between porous convergent-divergent channel with velocity slip and nanoparticle aggregation

The aggregation of nanoparticles is a major phenomenon having broad consequences in many fields. In order to fully utilize the capabilities of nanoparticles in a variety of applications and to evaluate the effects that they will have on the environment and biological systems, it is crucial to comprehend and manage aggregation. To develop and improve nanoparticle-based technology, researchers are still learning more about the aggregation processes. Thus, the present study investigates the combined effects of velocity slip and nanoparticle aggregation on Heat transfer (HT) analysis of MHD nanofluid (i.e., TiO2-C2H6O2) flow between porous convergent, divergent channel. The modified Krieger–Dougarty and Maxwell–Bruggeman models were utilized for nanoparticle aggregation. The modeling is based on nonlinear PDEs such as continuity, momentum, and heat equations. These equations are transformed into a system of nonlinear ODEs using similarity transformations and then solved numerically and analytically. The analytical solution has been constructed using the ADM method. The present results in particular cases are compared to results obtained by the HAM- package and by the Runge- Kutta Fehlberg 4th–5th order (RKF-45) for validation. The effects of active parameters on the velocity, temperature, concentration, skin friction, and Nusselt numbers are investigated. It is found that nanoparticle aggregation can limit fluid velocity in converging channels by increasing flow resistance through aggregate formation. Individual nanoparticles generate friction and lower velocity, while aggregated nanoparticles boost fluid density and velocity. In addition, it is found that the magnetic field lowers skin friction and increases HT due to Lorentz force, while porosity increases friction and HT. Nanoparticle concentration inversely affects friction, increasing friction without aggregation and decreasing friction with aggregation, with the HT rate rising with increased nanoparticle concentrations.

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.