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This paper aims to study the existence of traveling wave solutions (TWS) for a three-component noncooperative systems with nonlocal diffusion. Our main results reveal that when a threshold ℜ > 1 , there exists a critical wave speed c ∗ > 0. By using sub- and super-solution methods and Schauder's fixed point theorem, we prove that the system admits a nontrivial TWS for each c ≥ c ∗ . Meanwhile, we show that there exists no nontrivial TWS for c < c ∗ by detailed analysis. Finally, we apply our results to a nonlocal diffusive epidemic model with vaccination, and the boundary asymptotic behavior of TWS for the special case is obtained by constructing a suitable Lyapunov functional. Our research provides some insights on how to deal with the problem of TWS for the nonlocal diffusive epidemic models with bilinear incidence, which extends some results in the previous studies. [ABSTRACT FROM AUTHOR]

The number of chromosomes varies tremendously across species. It is not clear whether having more or fewer chromosomes could be advantageous. The probability of non-disjunction should theoretically decrease with smaller karyotypes, but too long chromosomes should enforce spatial constraint for their segregation during the mitotic anaphase. Here, we propose a new experimental cell system to acquire novel insights into the mechanisms underlying chromosome segregation. We collected the endemic Australian ant Myrmecia croslandi, the only known species with the simplest possible karyotype of a single chromosome in the haploid males (and one pair of chromosomes in the diploid females), since males are typically haploid in hymenopteran insects. Five colonies, each with a queen and a few hundreds of workers, were collected in the Canberra district (Australia), underwent karyotype analysis to confirm the presence of a single pair of chromosomes in worker pupae, and were subsequently maintained in the laboratory in Paris (France). Starting from dissociated male embryos, we successfully conducted primary cell cultures comprised of single-chromosome cells. This could be developed into a unique model that will be of great interest for future genomic and cell biology studies related to mitosis. [ABSTRACT FROM AUTHOR]

In aquaculture, the cost of feeding is the main factor affecting the efficiency of breeding, accounting for 40 to 80 percent of the total cost. Therefore, how to do scientific feeding is the key to reducing the cost of breeding and increase the economic benefits of breeding. Intelligent feeding is a feeding method of using all kinds of sensors to get the global information in the process of feeding, and combining with the relevant algorithm and model, the information is fed back to the control system to adjust the feeding strategy. It is also an effective means to achieve scientific feeding and improve efficiency. In recent years, some achievements have been made in the research of intelligent feeding in aquaculture, but there are still challenges in the realization of intelligent feeding due to many uncertain factors in aquaculture. The research status of automatic feeding machine and automatic feeding system is introduced. The intelligent feeding methods based on machine vision, acoustics, water quality parameters and biological model are summarized, the advantages and disadvantages of these methods are also summarized. In the future, in order to improve the accuracy of feeding intensity assessment and the adaptability of the intelligent feeding system to the breeding environment, we should strengthen the comprehensive analysis and application of the information such as image, voice, environmental factors and biological models in the process of fish feeding. [ABSTRACT FROM AUTHOR]

In this paper, stochastic analysis of interaction between palm leaf and caterpillar life-cycle is presented analytically and numerically. Existence, stabilities and extinction are analysed theoretically. Further, the results explained theoretically are simulated by using numerical representation. [ABSTRACT FROM AUTHOR]

This article discusses the importance of using a standardized synthetic microbial community, such as the oligo-mouse-microbiota (OMM12), in zebrafish models for research purposes. It highlights the advantages of the OMM12 consortium and explores the potential use of other synthetic microbiota in zebrafish research. The article also mentions the benefits of using zebrafish as a model organism in scientific research, including their external embryonic development, well-developed immune system, and anatomical and genetic similarities to humans. It discusses the challenges of developing a synthetic microbial community for zebrafish and provides a list of references related to the study of gut microbiota in zebrafish and other animal models. These references cover various topics, including the diversity of gut microbiota in zebrafish, the use of zebrafish as a model for studying xenobiotics and toxic agents, and the impact of probiotics on the gut microbiota. Overall, this article and the accompanying references provide valuable information for researchers interested in studying the gut microbiota and its role in various biological processes. [Extracted from the article]

Metal-based nanomaterials (MNMs) possess exceptional properties that have led to their widespread use in various fields, including medicine, energy, electronics, and agriculture. However, this increased utilization of MNMs also raises concerns about their potential release into environmental compartments, such as soil, water bodies, and the atmosphere, which could adversely affect the environmental system and living organisms. Hence, it is crucial to investigate the environmental risks associated with MNMs. This review comprehensively discusses the adverse effects of MNMs at different levels, including organismal, tissue, metabolic, molecular, and genetic levels. Additionally, it offers a holistic perspective on their overall impact. Specifically, biological models are categorized based on the environmental medium, and the effects of MNMs on tissues, organs, growth, development, and reproduction of individual biological models are summarized. Furthermore, the mechanisms underlying the toxicity of different MNMs toward biological models are also discussed. By doing so, this review provides a comprehensive and system-level understanding of nanotoxicity. [ABSTRACT FROM AUTHOR]

Background. Modeling allows investigating both existing and predicted processes and is widely used in basic science and in many industries. The aim is to develop a mathematical model for determining the size of the foreign bodies (FB) and their radiographic density in non-biological and biological models to improve the results of diagnosis for gunshot ricochet wounds. Materials and methods. In the biological non-living model (a piece of pork) and non-biological models (polystyrene, foam rubber), we place the FB made of paper, leather, rubber, plastic, and lithium-ion batteries. The number of the FB is 9 of each type. Number of models is 3 each: pork, polystyrene, foam rubber. We measure the dimensions of the FB and models with a metric ruler. For each model, we select the FB, which we label with the study number. We immerse the FB to the same depth using a Billroth general surgical medium hemostatic clamp in the following sequence: paper, leather, rubber, plastic, and lithium-ion battery. Multislice computed tomography (MSCT) of the models is performed on the Revolution EVO (2021) apparatus with measurement of the sizes and radiographic density of the FB and models. Radiographic density was measured in conventional units on the Hounsfield scale. For each study group, the ratio of the actual sizes of the removed FB and according to MSCT data was determined in the MathCad 15 computer math software, depending on the radiological density of the FB and the model. Results. According to MSCT data, the radiographic density of the models on the Hounsfield scale is as follows: polystyrene — –990.0 ± 0.3 units; foam rubber — –985.0 ± 0.2 units; pork — 62.0 ± 0.3 units; radiographic density of the foreign bodies: paper — –743.0 ± 10.3 units, leather — –258.0 ± 14.2 units, rubber — –12.0 ± 2.6 units, plastic — 183.0 ± 14.6 units, lithium-ion batteries — 3071 units. Visualization of paper in non-biological and biological models and leather in non-biological models is problematic due to the similar radiographic density of the models and the inability to measure the dimensions. When the FB (rubber, plastic, battery) is immersed in polystyrene, the coefficient of length (CL) is 1.0612, the coefficient of width (CW) is 1.928; in foam rubber: CL is 0.9926, CW is 1.9641; in pork: CL is 0.8394, CW is 1.534. Comparing the average coefficients of the ratio (CL and CW), we find that the coefficient in a biological model is closest to 1. This means that the FB from rubber, plastic, and batteries are best detected in pork. Conclusions. The actual dimensions of the FB placed in biological and non-biological models differ from those obtained by MSCT. Data correction is performed through calculated coefficients for length and width. The radiographic density of the model affects the radial visualization of the FB. The use of mathematical modeling in determining the sizes and radiographic density allows reducing the measurement error and determine the structure of the FB.

Introduction. At the beginning of December 2019, humanity has faced a new problem caused by coronavirus. In Hubei province of central China, epidemic events associated with severe primary viral pneumonia in humans began to develop. The isolated etiological agent was identified as a representative of Coronaviridae family. The global pandemic associated with the new coronavirus infection, acute respiratory syndrome type 2 (Severe acute respiratory syndrome 2, SARS-CoV-2), has become a challenge for humanity. Objective. In our work, we assessed the replicative ability and pathogenesis of the SARS-CoV-2 virus in hamsters. Materials and methods. Syrian hamsters (n=16) randomly divided into two groups were used in experiment. The first group was infected intranasally with the SARS-CoV-2 virus, strain SARS-CoV-2/human/KAZ/KZ_Almaty/2020 deposited in GenBank under number MZ379258.1. The second group remained as a control group. Clinical manifestations of the disease in hamsters were observed within 14 days. Samples were collected on days 3, 5, 7, 9, 12, and 14 postinfection. The obtained samples were tested for viral isolation in cell culture, histological examination and analysis of viral RNA by RT-PCR. Results. SARS-CoV-2 virus isolates showed efficient replication in the lungs of hamsters, causing pathological lung lesions in animals infected intranasally. Clinical manifestations of the disease in hamsters infected with this virus were characterized by a decrease in temperature and body weight, wetness and ruffled fur, and frequent stroking of the nasal planum. High virus titers were observed following the virus isolation in cell cultures from nasal, oral swabs and lungs of animals infected intranasally. Pathological autopsy demonstrated pathological changes in the lungs. Moreover, transmission by airborne droplets has been established when a healthy hamster was kept together with animals infected using the intranasal method. Conclusion. In conclusion, our study showed that the Syrian hamster model is a useful tool for studying the SARS-CoV-2 pathogenesis, as well as testing vaccine candidates against acute respiratory syndrome type 2.

Cell lines are important bioresources to study the key biological processes in the areas like virology, pathology, immunology, toxicology, biotechnology, endocrinology and developmental biology. Cell lines developed from fish organs are utilized as a model in vitro system in disease surveillance programs, pharmacology, drug screening and resolving cases of metabolic abnormalities. During last decade, there were consistent efforts made globally to develop new fish cell lines from different organs like brain, eye muscles, fin, gill, heart, kidney, liver, skin, spleen, swim bladder, testes, vertebra etc. This increased use and development of cell lines necessitated the establishment of cell line depositories to store/preserve them and assure their availability to the researchers. These depositories are a source of authenticated and characterized cell lines with set protocols for material transfer agreements, maintenance and shipping as well as logistics enabling cellular research. Hence, it is important to cryopreserve and maintain cell lines in depositories and make them available to the research community. The present article reviews the current status of the fish cell lines available in different depositories across the world, along with the prominent role of cell lines in conservation of life on land or below water. [ABSTRACT FROM AUTHOR]

Degeneration of the intervertebral disc (IVD) results in a range of symptomatic (i.e., painful) and asymptomatic experiences. Components of the degenerative environment, including structural disruption and inflammatory cytokine production, often correlate with pain severity. However, the role of inflammation in the activation of pain and degenerative changes has been complex to delineate. The most common IVD injury model is puncture; however, it initiates structural damage that is not representative of the natural degenerative cascade. In this study, we utilized in vivo injection of lipopolysaccharide (LPS), a pro‐inflammatory stimulus, into rat caudal IVDs using 33G needles to induce inflammatory activation without the physical tissue disruption caused by puncture using larger needles. LPS injection increased gene expression of pro‐inflammatory cytokines (Tnfa, Il1b) and macrophage markers (Inos, Arg1), supported by immunostaining of macrophages (CD68, CCR7, Arg1) and systemic changes in blood cytokine and chemokine levels. Disruption of the IVD structural integrity after LPS injection was also evident through changes in histological grading, disc height, and ECM biochemistry. Ultimately, intradiscal inflammatory stimulation led to local mechanical hyperalgesia, demonstrating that pain can be initiated by inflammatory stimulation of the IVD. Gene expression of nociceptive markers (Ngf, Bdnf, Cgrp) and immunostaining for neuron ingrowth (PGP9.5) and sensitization (CGRP) in the IVD were also shown, suggesting a mechanism for the pain exhibited. To our knowledge, this rat IVD injury model is the first to demonstrate local pain behavior resulting from inflammatory stimulation of caudal IVDs. Future studies will examine the mechanistic contributions of inflammation in mediating pain. [ABSTRACT FROM AUTHOR]

The lack of economic funds commonly represents a limiting factor in scientific research and prevents scientists from developing brilliant ideas. Indeed, a new project may involve using appropriate scientific instruments and concurrently dealing with the costs before pursuing new research fields. The innovative concept of investigating the effects of electric fields, as a simulation of marine electrical pollution, on benthic organisms such as foraminifera (marine protozoa) has been recently explored by our research group. This pioneering research has resulted in the development of a cost-effective instrument capable of generating customized electric stimulation patterns with accuracy and reliability. Here, we describe the construction of a low-intensity electrical stimulator based on an Arduino programmable board and a few electronic components. The instrument results very stable and precise regarding the stimulation times and the regulation of the current intensity applied to the biological preparation. Moreover, the setup can stimulate the preparation in constant or pulsed direct current. This homemade stimulation apparatus can be improved or modified according to the researchers’ needs, as possibilities and fields of application can be innumerable.

In this article application of neural network using Levenberg–Marquardt Back-propagation is implemented on differential model to study and analyze ringworm infectious disease. The formulated system of differential equations is consisting of following parts, namely; S(t) population which is at verge of being infected by ringworm, E(t) shows the environment effected by dermetophytosis fungus, I(t) whereas represent the infected individuals, R(t) and shows the population which has recovered from the infection. The solutions of different categories are represented by considering distinct datasets modeled and designed using LMB neural network. The numerical scheme Adam has been employed to establish a reference data set of the designed LMB neural network. The approximate outcomes of the SEIR based on dispersing and curing are discussed using the authentication, testing and training procedures to truncate the mean square error in function with help of LMB. The mean square error, regression, error histograms are generated to produce efficiency, effectiveness and correctness of proposed LMB neural network scheme.

The biological models used in the study of generalized peritonitis can be subdivided into 5 groups (introduction of foreign bodies, cultures of microorganisms, suspensions of feces, chemicals, and mechanical damage to the gastrointestinal tract) or into 4 groups (introduction of foreign bodies, chemicals, bacterial contamination of the abdominal cavity, and combined methods). After analysis of published reports, the most justified classification of methods of peritonitis modelling is based on the type of peritonitis-inducing agent and the administration route and on the nature of peritonitis developing in the abdominal cavity. The choice of the model maximally close reproducing clinical conditions of peritonitis should be based on the specific objectives of the study, focusing on the etiology, pathogenesis, and severity of the disease course, planned measures aimed at eliminating the process, and other factors. [ABSTRACT FROM AUTHOR]

Changes in homeostatic balance of the body, primarily at the cellular-molecular level, are a relevant research object in fundamental and applied studies. They can be eligible indicators for predicting negative effects under exposure to chemical risk factors. The aim of this study was to substantiate markers of a transformed plasma proteomic profile in children. These markers should have prognostic value and an evidence-based association with combined aerogenic exposure to metal oxides (copper and nickel oxides used as an example). We propose an innovative methodical approach based on plasma proteomic profiling that includes the following: identification of identical proteins and genes encoding their expression; quantification of indicators within the ‘identical protein – a chemical concentration in blood’ system; prediction of negative effects as per indicators of homeostasis destabilization at the cellular-molecular level under chronic aerogenic exposure to chemicals. The proposed algorithm was tested by comparing changed proteins and peptides identified in plasma proteomic profiles of children exposed simultaneously to nickel and copper oxides in ambient air in actual conditions and small rodents under experimental combined and isolated exposure to the analyzed chemicals in levels equal to real ones. Long-term aerogenic exposure simultaneously to copper and nickel oxides was established to create elevated nickel and copper levels in blood of exposed children substantiated as markers of exposure. They were up to 2.4 times higher against the same indicators in unexposed children and reference levels as well. The results of field observations were verified by elevated levels of the same chemicals in blood under experimental modelling of an equivalent combined exposure performed on biological models. APOBEC1 complement factor (the А1CF gene) was substantiated as an identical proteomic marker based on plasma proteomic profiling in experimental and field investigations. It has an evidence-based association with markers of exposure (nickel and copper simultaneously identified in blood). Lower expression of this protein under persistent combined aerogenic exposure to nickel and copper oxides makes it possible to predict such a negative effect as modification of low density lipoproteins with further induction of atherosclerotic changes in vessels, the latter being a risk factor of cardiovascular diseases.

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The objective of this work is to model a population management in which two species intervene. There is an interdependence predator-prey relationship between them. It will be assumed, as a descriptive biological model, the Lotka-Volterra one with the application of an Allee effect in one of the dynamics of the species. This incorporation into the system make the model more realistic. In view of the advantages, the model will be in its fractional version, that is, where derivatives of Caputo of fractional order are considered, with the fractional order in (0,1]. Existence and uniqueness of the model solution will be explicitly proved, and a non-negative invariance of the solution and the stability of the resulting equilibrium will be studied. In order to solve the problem, the use of fractional numerical techniques will be of fundamental importance and absolutely essential to conclude the analysis. Some examples of great importance will be shown. [ABSTRACT FROM AUTHOR]

An oxygen-effect-incorporated stochastic microdosimetric kinetic (OSMK) model was previously developed to estimate the survival fraction of cells exposed to charged-particle beams with wide dose and linear energy transfer (LET) ranges under various oxygen conditions. In the model, hypoxia-induced radioresistance was formulated based on the dose-averaged radiation quality. This approximation may cause inaccuracy in the estimation of the biological effectiveness of the radiation with wide variation in energy deposited to a sensitive volume per event, such as spread-out Bragg peak (SOBP) beams. The purpose of this study was to apply an alternative approach so as to consider the energy depositions on an event-by-event basis. The production probability of radiation-induced lesions per energy was formulated with oxygen partial pressure to account for the hypoxia-induced radioresistance. The reduction in the oxygen enhancement ratio for high-LET radiations was modeled by reducing the sensitive-volume size and increasing the saturation energy in microdosimetry. The modified OSMK model was tested against the reported survival data of three cell lines exposed to six species of ions with wide dose and LET ranges under aerobic and hypoxic conditions. The model reasonably reproduced the reported cell survival data. To evaluate the event-by-event approach, survival distributions of Chinese hamster ovary cells exposed to SOBP beams were estimated using the original and modified OSMK models. The differences in the estimated survival distributions between the models were marginal even under extreme hypoxia. The event-by-event approach improved the theoretical validity of the OSMK model. However, the original OSMK model can still provide an accurate estimation of the biological effectiveness of therapeutic radiations. [ABSTRACT FROM AUTHOR]

During past decades, the study of the interaction between predator and prey species has become one of the most exciting topics in computational biology and mathematical ecology. In this paper, we aim to investigate the stability of a diseased model of susceptible, infected prey and predators around an internal steady state. To this end, the fractional derivatives based on the Mittag‐Leffler kernels in the Liouville‐Caputo concept has been taken into consideration. The existence and uniqueness of the acquired solutions to the model are also studied in this paper. In order to investigate the effects of the fractional‐order along with other existing parameters in the model, several possible scenarios have been examined. As it is seen in the proposed graphical simulations, the employed fractional operator is capable of capturing all anticipated theoretical features of the model. The numerical technique employed in this contribution is precise and efficient and can be easily adopted to investigate many fractional‐order models in biology. It is found that new proposed operators of fractional‐order can describe the real‐world phenomena even better than integer‐order differential equations because of their memory‐related properties. [ABSTRACT FROM AUTHOR]

The time-fractional generalized biological population model and the (2, 2, 2) Zakharov–Kuznetsov (ZK) equation are significant modeling equations to analyse biological population, ion-acoustic waves in plasma, electromagnetic waves, viscoelasticity waves, material science, probability and statistics, signal processing, etc. The new generalized G ′ / G -expansion method is consistent, computer algebra friendly, worthwhile through yielding closed-form general soliton solutions in terms of trigonometric, rational and hyperbolic functions associated to subjective parameters. For the definite values of the parameters, some well-established and advanced solutions are accessible from the general solution. The solutions have been analysed by means of diagrams to understand the intricate internal structures. It can be asserted that the method can be used to compute solitary wave solutions to other fractional nonlinear differential equations by means of fractional complex transformation. [ABSTRACT FROM AUTHOR]

The purpose of these investigations is to find the numerical outcomes of the fractional kind of biological system based on Leptospirosis by exploiting the strength of artificial neural networks aided by scale conjugate gradient, called ANNs-SCG. The fractional derivatives have been applied to get more reliable performances of the system. The mathematical form of the biological Leptospirosis system is divided into five categories, and the numerical performances of each model class will be provided by using the ANNs-SCG. The exactness of the ANNs-SCG is performed using the comparison of the reference and obtained results. The reference solutions have been obtained by using theAdams numerical scheme. For these investigations, the data selection is performed at 82% for training, while the statics for both testing and authentication is selected as 9%. The procedures based on the recurrence, mean square error, error histograms, regression, state transitions, and correlation will be accomplished to validate the fitness, accuracy, and reliability of the ANNs-SCG scheme. [ABSTRACT FROM AUTHOR]

The release of the cardiac troponin T (cTnT) in patients with acute myocardial infarction (AMI) has been analyzed through a methodology based on nonlinear mixed-effects (NME) models. The aim of this work concerns the investigation of any possible relationship between clinical covariates and the dynamics of the release of cTnT to derive more detailed and useful clinical information for the correct treatment of these patients. An ad-hoc mechanistic model describing the biomarker release process after AMI has been devised, assessed, and exploited to evaluate the impact of the available clinical covariates on the cTnT release dynamic. The following approach was tested on a preliminary dataset composed of a small number of potential clinical covariates: employing an unsupervised approach, and despite the limited sample size, dyslipidemia, a known risk factor for cardiovascular disease, was found to be a statistically significant covariate. By increasing the number of covariates considered in the model, and patient cohort, we envisage that this approach may provide an effective means to automatically classify AMI patients and to investigate the role of interactions between clinical covariates and cTnT release. [ABSTRACT FROM AUTHOR]

This article explores numerically the biotechnological performances of microalgae biofaçade. The model computes the system's thermal behavior using a radiative-convective approach accounting for location on Earth and actual weather data. In a coupled manner, it simulates the microalgae culture behavior, i.e. light-driven growth and cell pigment content acclimation. In addition, it features refinement such as wavelength-dependent biomass optical properties and thermal-modulated biological rates. Thanks to this model, operation strategies and design possibilities were evaluated using actual weather data for a biofaçade module deployed in Marseille in 2023. Investigations revealed that a semi-batch mode of operation, while simplistic, is the most efficient way to operate a biofaçade if sole biological production is considered (about 18.0 ± 0.9 kg per year, 2.44 ± 0.12 g/L output concentration). However, if intended as an office glazing, turbidostat mode of operation should be preferred for aesthetic and visual comfort reasons (about 19.1 ± 1.1 kg per year, 0.64 ± 0.07 g/L output concentration). System optimization also confirmed the experimental observation that the system could be prone to overheating. Nevertheless, while overheating can be mitigated by increasing the reservoir thickness, this strategy is detrimental to the average output concentration. Finally, location-specific optimization revealed that a standard biofaçade module could be deployed over France, and system performances are derived for the whole country thanks to the weather forecast agency data. [Display omitted] • Biofaçades are considered a potential synergy between buildings and microalgae. • A model coupling weather, illumination, temperature, and cell growth was used to describe system behavior. • Bioprocess control procedures (semi-batch, turbidostat, continuous) are investigated. • Particle Swarm Optimizer coupled with a Genetic Algorithm is used to optimized the system. • Biofaçade module standardization can be envisioned with minimal impact on biotechnological performances. [ABSTRACT FROM AUTHOR]

A meta-analytic approach deciphered the taxonomic profile of the zebrafish gut microbiota at different developmental stages. Data (16S rDNA) were systematically searched in databases, selecting those with intestine samples of fish not exposed to a particular treatment or challenge (e.g., pathogens, dietetic tests, xenobiotics, etc.) and obtaining 340 samples to be processed. Results revealed marked differences between the developmental phases. Proteobacteria was the dominant phylum in the larval phase, with a relative abundance of 90%, while the rest of the phyla did not exceed 2%. Vibrio, Aeromonas, Plesiomonas, Pseudomonas, Shewanella, and Acinetobacter were the dominant genera in this phase. Transitional changes were observed after the larvae stage. Proteobacteria still registered high abundance (48%) in the juvenile phase, but Fusobacteria (40%) and Bacteriodota (5.9%) registered considerable increases. Genera, including Cetobacterium, Plesiomonas, Aeromonas, Vibrio, and Flavobacterium, dominated this stage. The phyla Proteobacteria (48%) and Fusobacteria (35%) were strongly established in the adult phase. Cetobacterium was registered as the most abundant genus, followed by Aeromonas, Acinetobacter, Plesiomonas, Vibrio, and ZOR0006 (Firmicutes; 6%). In conclusion, the composition of the intestinal microbiota of zebrafish is consistently determined by two primary phyla, Proteobacteria and Fusobacteria; however, this composition varies depending on the developmental stage. Cetobacterium and Aeromonas are the most relevant genera in juveniles and adults. Finally, these results reveal a consistent pattern of certain bacterial groups in the zebrafish microbiota that could help shape gnotobiotic models (colonized with a specific known bacterial community) or synthetic microbiota (in vitro assembly of microbes), among other approaches. [Display omitted] • Zebrafish gut microbiota relies on its developmental stage. • Vibrio and Aeromonas play a major role in the larval zebrafish gut microbiota. • Cetobacterium has a relevant role in the juvenile and adult zebrafish microbiota. [ABSTRACT FROM AUTHOR]

In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order mathematical model will be presented using stochastic artificial neural network (ANN)techniques in conjunction with theLevenberg-Marquardt backpropagation (LMBP), referred to as ANN-LMBP. To illustrate the preciseness of the ANN-LMBP method, mathematical presentations of three different values focused on fractional order will be performed. These statics performances are taken in these investigations are 78% and 11% for both learning and certification. The accuracy of the ANN-LMBP method is determined by comparing the values obtained by the database Adams-Bash forth-Moulton scheme. The simulation-based error histograms (EHs), MSE, recurrence, and state transitions (STs) will be offered to achieve the capability, accuracy, steadiness, abilities, and finesse of the ANN-LMBP method. [ABSTRACT FROM AUTHOR]

The purpose of the present study was to assess the ovicidal and larvicidal activity of a hydroalcoholic extract (HAE) and their fractions (aqueous, Aq-F and organic, EtOAc-F) from Guazuma ulmifolia leaves using Haemonchus contortus as a biological model. The egg hatching inhibition (EHI) and larval mortality against infective larvae (L3) tests were used to determine the anthelmintic effect of the treatments. The extract and fractions were tested at different concentrations against eggs and L3. Additionally, distilled water and methanol were used as negative controls and ivermectin as a positive control. The extract and fractions were subjected to HPLC analysis to identify the major compounds. The HAE displayed the highest ovicidal activity (100% EHI at 10 mg/mL). Fractionation of the HA extract allowed increasing the nematicidal effect in the EtOAc-F (100% EHI at 0.62 mg/mL and 85.35% mortality at 25 mg/mL). The phytochemical analysis of the extract and fractions revealed the presence of kaempferol, ethyl ferulate, ethyl coumarate, flavonol, luteolin, ferulic acid, luteolin rhamnoside, apigenin rutinoside, coumaric acid derivative, luteolin glucoside, and quercetin glucoside. These results suggest that G. ulmifolia leaves could be potential candidates for the control of H. contortus or other gastrointestinal parasitic nematodes. [ABSTRACT FROM AUTHOR]

This paper investigates two non-instantaneous impulsive biological models. First, a non-instantaneous impulsive hematopoiesis model with pure delay and a non-instantaneous impulsive n-dimensional biological model with pure delay have been proposed. Next, the existence and uniqueness of almost periodic solutions for these two models are proved by us respectively. Then, we prove that all solutions converge exponentially to the positive almost periodic solution respectively. Finally, some simulations are given to show the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This article studies a biological population model in the context of a fractional Caputo-Fabrizio operator using double Laplace transform combined with the Adomian method. The conditions for the existence and uniqueness of solution of the problem under consideration is established with the use of the Banach principle and some theorems from fixed point theory. Furthermore, the convergence analysis is presented. For the accuracy and validation of the technique, some applications are presented. The numerical simulations present the obtained approximate solutions with a variety of fractional orders. From the numerical simulations, it is observed that when the fractional order is large, then the population density is also large; on the other hand, population density decreases with the decrease in the fractional order. The obtained results reveal that the considered technique is suitable and highly accurate in terms of the cost of computing, and can be used to analyze a wide range of complex non-linear fractional differential equations. [ABSTRACT FROM AUTHOR]

Advancements in stem cell technology together with an improved understanding of in vitro organogenesis have enabled new routes that exploit cell-autonomous self-organization responses of adult stem cells (ASCs) and homogenous pluripotent stem cells (PSCs) to grow complex, three-dimensional (3D), mini-organ like structures on demand, the so-called organoids. Conventional optical and electrical neurophysiological techniques to acquire functional data from brain organoids, however, are not adequate for chronic recordings of neural activity from these model systems, and are not ideal approaches for throughput screenings applied to drug discovery. To overcome these issues, new emerging approaches aim at fusing sensing mechanisms and/or actuating artificial devices within organoids. Here we introduce and develop the concept of the Lab-in-Organoid (LIO) technology for in-tissue sensing and actuation within 3D cell aggregates. This challenging technology grounds on the self-aggregation of brain cells and on integrated bioelectronic micro-scale devices to provide an advanced tool for generating 3D biological brain models with in-tissue artificial functionalities adapted for routine, label-free functional measurements and for assay's development. We complete previously reported results on the implementation of the integrated self-standing wireless silicon micro-devices with experiments aiming at investigating the impact on neuronal spheroids of sinusoidal electro-magnetic fields as those required for wireless power and data transmission. Finally, we discuss the technology headway and future perspectives. [ABSTRACT FROM AUTHOR]

Advancements in stem cell technology together with an improved understanding of in vitro organogenesis have enabled new routes that exploit cell-autonomous self-organization responses of adult stem cells (ASCs) and homogenous pluripotent stem cells (PSCs) to grow complex, three-dimensional (3D), mini-organ like structures on demand, the so-called organoids. Conventional optical and electrical neurophysiological techniques to acquire functional data from brain organoids, however, are not adequate for chronic recordings of neural activity from these model systems, and are not ideal approaches for throughput screenings applied to drug discovery. To overcome these issues, new emerging approaches aim at fusing sensing mechanisms and/or actuating artificial devices within organoids. Here we introduce and develop the concept of the Lab-in-Organoid (LIO) technology for in-tissue sensing and actuation within 3D cell aggregates. This challenging technology grounds on the self-aggregation of brain cells and on integrated bioelectronic micro-scale devices to provide an advanced tool for generating 3D biological brain models with in-tissue artificial functionalities adapted for routine, label-free functional measurements and for assay’s development. We complete previously reported results on the implementation of the integrated self-standing wireless silicon micro-devices with experiments aiming at investigating the impact on neuronal spheroids of sinusoidal electro-magnetic fields as those required for wireless power and data transmission. Finally, we discuss the technology headway and future perspectives.

Background: Third Fork Creek is a historically impaired urban stream that flows through the city of Durham, North Carolina. Caenorhabditis elegans (C. elegans) are non-parasitic, soil and aquatic dwelling nematodes that have been used frequently as a biological and ecotoxicity model. We hypothesize that exposure to Third Fork Creek surface water will inhibit the growth and chemotaxis of C. elegans. Using our ring assay model, nematodes were enticed to cross the water samples to reach a bacterial food source which allowed observation of chemotaxis. The total number of nematodes found in the bacterial food source and the middle of the plate with the water source was recorded for 3 days. Results: Our findings suggest a reduction in chemotaxis and growth on day three in nematodes exposed to Third Fork Creek water samples when compared to the control (p value < 0.05). These exploratory data provide meaningful insight to the quality of Third Fork Creek located near a Historically Black University. Conclusions: Further studies are necessary to elucidate the concentrations of the water contaminants and implications for human health. The relevance of this study lies within the model C. elegans that has been used in a plethora of human diseases and exposure research but can be utilized as an environmental indicator of water quality impairment. [ABSTRACT FROM AUTHOR]

Agricultural models, agricultural artificial intelligent, and data analysis technology, etc., exist in whole processes of information perceiving, transmission, processing and control for smart agriculture， thus they are the core technology of smart agriculture. To furtherly make the substances and functions of agricultural models clear, facilitate its further research and application, drive smart agriculture development with healthy, steady, and sustainable, methods of systematic analysis, comparison, and chart for relationship, etc. were used in this research. The definition, classification, functions of the agricultural models were theoretically analyzed. The relationships between the agricultural models and the elements and processes of the smart agriculture were expounded, which made the functions of agricultural models clear, provided some agricultural models examples applied in the smart agriculture. The important studies and application progresses of agricultural models were reviewed. The comparison results of agricultural models showed that the 4 levels of agricultural biological elements, 6 scales of agricultural environmental elements, 6 administrative levels of agricultural technological and economic elements, and the relevant approaches for modeling agricultural system need to be considered. The research and application of multi-space scales on environment elements in the agricultural models would have the larger potential. The combination of agricultural models with molecular genetics, perceiving, and artificial intelligence, the collaboration among public and private researchers, and food security challenges have been an important power for further development of agricultural models, linking agricultural models with various agricultural system modeling, databases, harmonious and open data, and decision-making support systems (DSS) would be focus on. The research and application of the agricultural models in China have formed crop model series with Chinese characteristics, joined in the world trends of the Agricultural Model Intercomparison and Improvement Project (AgMIP), the smart agriculture, and so on. They should be speedy graspe chances and accelerate development. The agricultural models is a quantitative express of relationships within or among the agricultural system elements. An important method with epistemological values of quantifying and synthesizing agricultural sciences, and will play an indispensible role in data achieving and processing for the smart agriculture combining perceiving techniques, and become a significant bridge and bond.

Background and Objectives: Effective microsurgical training necessitates dedicated practice, prompting the development of simulation models that mitigate the hygiene risks, regulatory challenges, and storage difficulties associated with conventional biological models. This study aims to evaluate the preferences of microsurgeons and medical students regarding self-made silicone simulation vessels, comparing them to standard biological models., Methods: A three-part jig, comprising of a two-part metal clamp component and a transparent acrylic block with 4x4 channels, was designed. This assembly produced 16 vessels with a 1 ​mm inner diameter. Liquid silicone (Ecoflex 00-30), readily accessible from online distributors, was injected into the channels using a syringe. After tightening the clamp component and inserting 16 1 ​mm k-wires, the vessels were left to set for approximately 24 ​h 20 medical students with no prior microsurgical experience and 10 microsurgery-trained surgeons then evaluated these silicone vessels against a commonly used biological model (chicken brachial artery for surgeons or chicken aorta for students). Participants were then surveyed about their preference for a specific model for frequent practice using a 10-point Likert scale., Results and Conclusion: In assessing ideal microsurgical training models, all participants highlighted the importance of realism. Surgeons' main practical considerations were hygiene, availability, and setup and storage ease, while medical students were primarily concerned with cost-effectiveness. Both surgeons and medical students perceived the biological model as more realistic, yet less hygienic and harder to set up and store. Conversely, the silicone model, though deemed less realistic, offered advantages in hygiene, availability, cost-effectiveness, and setup and storage simplicity. The silicone model emerged as the overall favorite amongst all participants for frequent practice. Silicone vessels may serve as a complementary adjunct to biological models, allowing surgeons-in-training to practice their skills outside of the operating room and lab settings., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 Society for Indian Hand Surgery and Micro Surgeons. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)

The release of the cardiac troponin T (cTnT) in patients with acute myocardial infarction (AMI) has been analyzed through a methodology based on nonlinear mixed-effects (NME) models. The aim of this work concerns the investigation of any possible relationship between clinical covariates and the dynamics of the release of cTnT to derive more detailed and useful clinical information for the correct treatment of these patients. An ad-hoc mechanistic model describing the biomarker release process after AMI has been devised, assessed, and exploited to evaluate the impact of the available clinical covariates on the cTnT release dynamic. The following approach was tested on a preliminary dataset composed of a small number of potential clinical covariates: employing an unsupervised approach, and despite the limited sample size, dyslipidemia, a known risk factor for cardiovascular disease, was found to be a statistically significant covariate. By increasing the number of covariates considered in the model, and patient cohort, we envisage that this approach may provide an effective means to automatically classify AMI patients and to investigate the role of interactions between clinical covariates and cTnT release.

In order to quantify the invasiveness of melanoma tumor cells in vitro, a modification of the amniotic basement membrane (BM) model, described by Liotta et al. (Cancer Letters, 11, 141, 1980), was used in combination with radiolabeled tumor cells. B16-F10 metastatic murine melanoma cells and a derived clone (B16-F10L) were prelabeled with 0.1 muCi/ml of [14C]thymidine for 20-24 h in serum-free medium at 37 degrees C. Following incubation, fetal bovine serum was added to a concentration of 5 per cent, and the cells were allowed to grow to confluency for the next 24-28 h. The labeled cells were seeded onto amniotic membranes situated in Membrane Invasion Culture System (MICS) chambers at a density of 2.5 X 10(4) per well. At various times points, radioactivity of tumor cells that completely traversed the membrane was determined using an under-the-membrane sampling method. The average percent invasion demonstrated by the B16-F10 line was 2.75 per cent, and 3.65 per cent exhibited by the B16-F10L cell line after 48-53 h in vitro. Since it was apparent that some variability in thickness existed among membrane samples, a morphological analysis was performed on five sectors of a three-inch-diameter sample from four different placentae. Differences and similarities in BM thickness within the same sector were noted by this technique and could possibly contribute to some variability observed in tumor cell invasion in this model. Another parameter examined was the proliferation of tumor cells in the upper and lower wells of the MICS chambers. By 48 h, approximately 32.1 per cent of the B16-F10 cell line as well as the clone had replicated in the upper wells associated with the BMs compared with a 32.9 per cent replication in the lower wells, which reaffirmed the viability of the tumor cells under experimental conditions and insured similarly replicating populations of cells. In order to quantify the invasiveness of radiolabeled tumor cells accurately through a biological membranous barrier, the proper concentration of cells must be used, tumor cell heterogeneity should be taken into consideration, the technique of sampling radiolabeled invasive cells should be critically analysed, and thickness of the membranous barrier should all be considered as possible important factors in the quantitative analyses.

Thimerosal (TM) is a toxic, organometallic mercury compound (which releases ethyl-mercury-containing compounds in aqueous solutions) used as a preservative in vaccines. Mitochondria are organelle which are highly vulnerable to many chemical compounds, including mercury (Hg) and its derivatives. Wistar rats (at 21 days of age) were used to model a child's TM exposure following childhood vaccination, divided in two groups: TM exposed (20 μg/kg/day) and unexposed controls (saline solution), both for 24 h. Atomic Fluorescence Spectrometry was used to quantify the amounts of mercury in tissues. The electron transport chain (ETC) from isolated mitochondria was evaluated using an oxygen electrode. The mitochondrial membrane potential and H 2 O 2 production were analyzed using selective fluorescence probes. The activity of some enzymes (SOD, CAT, GPx, and AChE) and secondary markers of oxidative stress (GSH, GSSG, total free thiol) were also examined in tissues. Hg accumulation in the brain and liver was higher in exposed animals when compared to the control. Liver-isolated mitochondria showed that TM improved respiratory control by 23%; however, states 3 and 4 of the ETC presented a decrease of 16% and 37%, respectively. Furthermore, brain-isolated mitochondria presented an improvement of 61% in respiratory control. Brain enzyme activities were significantly impacted in TM-exposed rats compared to unexposed rats as follows: decreases in SOD (32%) and AChE (42%) and increases in GPx (79%) and CAT (100%). GPx enzyme activity in the liver was significantly increased (37%). Among secondary oxidative stress markers, the brain's total reduced thiol (SH) concentration was significantly increased (41%). Acute TM treatment exposure in a Wistar rat model mimicking TM exposure in an infant following childhood vaccination significantly damaged brain bioenergetic pathways. This study supports the ability of TM exposure to preferentially damage the nervous system. [Display omitted] • Thimerosal (TM) significantly affects mitochondrial bioenergetics in the brain. • Mitochondrial integrity (membrane potential) was maintained after acute TM treatment. • Ethylmercury released after the breakdown of TM compromised the cholinergic system. • The brain is more sensitive to oxidative stress induced by TM compared to the liver. [ABSTRACT FROM AUTHOR]

Abstract Background Gene regulatory networks with different topological and/or dynamical properties might exhibit similar behavior. System that is less perceptive for the perturbations of its internal and external factors should be preferred. Methods for sensitivity and robustness assessment have already been developed and can be roughly divided into local and global approaches. Local methods focus only on the local area around nominal parameter values. This can be problematic when parameters exhibits the desired behavior over a large range of parameter perturbations or when parameter values are unknown. Global methods, on the other hand, investigate the whole space of parameter values and mostly rely on different sampling techniques. This can be computationally inefficient. To address these shortcomings ’glocal’ approaches were developed that apply global and local approaches in an effective and rigorous manner. Results Herein, we present a computational approach for ’glocal’ analysis of viable parameter regions in biological models. The methodology is based on the exploration of high-dimensional viable parameter spaces with global and local sampling, clustering and dimensionality reduction techniques. The proposed methodology allows us to efficiently investigate the viable parameter space regions, evaluate the regions which exhibit the largest robustness, and to gather new insights regarding the size and connectivity of the viable parameter regions. We evaluate the proposed methodology on three different synthetic gene regulatory network models, i.e. the repressilator model, the model of the AC-DC circuit and the model of the edge-triggered master-slave D flip-flop. Conclusions The proposed methodology provides a rigorous assessment of the shape and size of viable parameter regions based on (1) the mathematical description of the biological system of interest, (2) constraints that define feasible parameter regions and (3) cost function that defines the desired or observed behavior of the system. These insights can be used to assess the robustness of biological systems, even in the case when parameter values are unknown and more importantly, even when there are multiple poorly connected viable parameter regions in the solution space. Moreover, the methodology can be efficiently applied to the analysis of biological systems that exhibit multiple modes of the targeted behavior.

This article studies a biological population model in the context of a fractional Caputo-Fabrizio operator using double Laplace transform combined with the Adomian method. The conditions for the existence and uniqueness of solution of the problem under consideration is established with the use of the Banach principle and some theorems from fixed point theory. Furthermore, the convergence analysis is presented. For the accuracy and validation of the technique, some applications are presented. The numerical simulations present the obtained approximate solutions with a variety of fractional orders. From the numerical simulations, it is observed that when the fractional order is large, then the population density is also large; on the other hand, population density decreases with the decrease in the fractional order. The obtained results reveal that the considered technique is suitable and highly accurate in terms of the cost of computing, and can be used to analyze a wide range of complex non-linear fractional differential equations.

Sustainable production in aquaculture requires integrating new technologies that maximize economic benefits while minimizing environmental impacts. In shrimp production, probiotics improve larval survival and reduce environmental impacts, but their use also increases total production costs. In this study, the economic feasibility of using probiotics in larval whiteleg shrimp production was assessed, as well as the optimal concentration to maximize the economic performance of a laboratory for larval whiteleg shrimp rearing. A bioeconomic model was developed based on the laboratory production data. Then, a marginal approach was applied to identify the optimal economic points. Probiotics led to a significant increase in survival, reducing unit production costs by 44%. However, they were also associated with a 6% increase in total production costs. Thus, profitability also depends on the capability of the laboratory to sustain this type of investment. At a constant price of 2.89 USD, thousand‐1 postlarvae‐1 2.96 x 1010 colony forming units (CFU) m‐3 day‐1 of homemade probiotic inoculum optimized the economic performance of the laboratory, increasing net benefits by 26% for each production cycle. A dosage increase of up to 6.8 x 1010 CFU/m3 day‐1 increased survival even more, but the economic benefits obtained with the use of probiotics were equal to those obtained without them. [ABSTRACT FROM AUTHOR]

• Establish 4He beam mixed radiation field spectra for the 1st clinical TPS with active beam delivery. • Fast GPU-accelerated mMKM – based RBE predications in 4He ion beam therapy. • Sensitivity study towards patient treatment with 4He ion beam therapy. To develop and verify effective dose (D RBE) calculation in 4He ion beam therapy based on the modified microdosimetric kinetic model (mMKM) and evaluate the bio-sensitivity of mMKM-based plans to clinical parameters using a fast analytical dose engine. Mixed radiation field particle spectra (MRFS) databases have been generated with Monte-Carlo (MC) simulations for 4He-ion beams. Relative biological effectiveness (RBE) and D RBE calculation using MRFS were established within a fast analytical engine. Spread-out Bragg-Peaks (SOBPs) in water were optimized for two dose levels and two tissue types with photon linear-quadratic model parameters α ph , β ph , and (α/β) ph to verify MRFS-derived database implementation against computations with MC-generated mixed-field α and β databases. Bio-sensitivity of the SOBPs was investigated by varying absolute values of β ph , while keeping (α/β) ph constant. Additionally, dose, dose-averaged linear energy transfer, and bio-sensitivity were investigated for two patient cases. Using MRFS-derived databases, dose differences ≲2% in the plateau and SOBP are observed compared to computations with MC-generated databases. Bio-sensitivity studies show larger deviations when altering the absolute β ph value, with maximum D 50% changes of ~5%, with similar results for patient cases. Bio-sensitivity analysis indicates a greater impact on D RBE varying (α/β) ph than β ph in mMKM. The MRSF approach yielded negligible differences in the target and small differences in the plateau compared to MC-generated databases. The presented analyses provide guidance for proper implementation of RBE-weighted 4He ion dose prescription and planning with mMKM. The MRFS-D RBE calculation approach using mMKM will be implemented in a clinical treatment planning system. [ABSTRACT FROM AUTHOR]

Objective. Treatment plans of ion-beam therapy have been made under an assumption that all cancer cells within a tumour equally respond to a given radiation dose. However, an intra-tumoural cellular radiosensitivity heterogeneity clearly exists, and it may lead to an overestimation of therapeutic effects of the radiation. The purpose of this study is to develop a biological model that can incorporate the radiosensitivity heterogeneity into biological optimization for ion-beam therapy treatment planning. Approach. The radiosensitivity heterogeneity was modeled as the variability of a cell-line specific parameter in the microdosimetric kinetic model following the gamma distribution. To validate the developed intra-tumoural-radiosensitivity-heterogeneity-incorporated microdosimetric kinetic (HMK) model, a treatment plan with H-ion beams was made for a chordoma case, assuming a radiosensitivity heterogeneous region within the tumour. To investigate the effects of the radiosensitivity heterogeneity on the biological effectiveness of H-, He-, C-, O-, and Ne-ion beams, the relative biological effectiveness (RBE)-weighted dose distributions were planned for a cuboid target with the stated ion beams without considering the heterogeneity. The planned dose distributions were then recalculated by taking the heterogeneity into account. Main results . The cell survival fraction and corresponding RBE-weighted dose were formulated based on the HMK model. The first derivative of the RBE-weighted dose distribution was also derived, which is needed for fast biological optimization. For the patient plan, the biological optimization increased the dose to the radiosensitivity heterogeneous region to compensate for the heterogeneity-induced reduction in biological effectiveness of the H-ion beams. The reduction in biological effectiveness due to the heterogeneity was pronounced for low linear energy transfer (LET) beams but moderate for high-LET beams. The RBE-weighted dose in the cuboid target decreased by 7.6% for the H-ion beam, while it decreased by just 1.4% for the Ne-ion beam. Significance. Optimal treatment plans that consider intra-tumoural cellular radiosensitivity heterogeneity can be devised using the HMK model., (© 2024 Institute of Physics and Engineering in Medicine.)

ObjectivesAntagonists in the debate over whether the maternal stress response during pregnancy damages or culls fetuses have invoked the theory of selection in utero to support opposing positions. We describe how these opposing arguments arise from the same theory and offer a novel test to discriminate between them. Our test, rooted in reports from population endocrinology that human chorionic gonadotropin (hCG) signals fetal fitness, contributes not only to the debate over the fetal origins of illness, but also to the more basic literature concerned with whether and how natural selection in utero affects contemporary human populations.MethodsWe linked maternal serum hCG measurements from prenatal screening tests with data from the California Department of Public Health birth registry for the years 2001–2007. We used time series analysis to test the association between the number of live born male singletons and median hCG concentration among males in monthly gestational cohorts.ResultsAmong the 1.56 million gestations in our analysis, we find that median hCG levels among male survivors of monthly conception cohorts rise as the number of male survivors falls.ConclusionsElevated median hCG among relatively small male birth cohorts supports the theory of selection in utero and suggests that the maternal stress response culls cohorts in gestation by raising the fitness criterion for survival to birth.