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Objectives: This study aimed to elucidate the connection between osteoclastic forkhead transcription factor O1 (FoxO1) and periodontitis and explore the underlying mechanism by which FoxO1 knockdown regulates osteoclast formation. Materials and Methods: A conventional ligature‐induced periodontitis model was constructed to reveal the alterations in the proportion of osteoclastic FoxO1 in periodontitis via immunofluorescence staining. Additionally, RNA sequencing (RNA‐seq) was performed to explore the underlying mechanisms of FoxO1 knockdown‐mediated osteoclastogenesis, followed by western blotting, quantitative polymerase chain reaction, and enzyme‐linked immunosorbent assay. Results: FoxO1+ osteoclasts were enriched in the alveolar bone in experimental periodontitis. Moreover, FoxO1 knockdown led to impaired osteoclastogenesis with low expression of osteoclast differentiation‐related genes, accompanied by an insufficient osteoclast maturation phenotype. Mechanistically, RNA‐seq revealed that the nuclear factor kappa B (NF‐κB) and nucleotide‐binding oligomerization domain‐like receptor family pyrin domain containing 3 (NLRP3) inflammasome signaling pathways were inhibited in FoxO1‐knockdown osteoclasts. Consistent with this, MCC950, an effective inhibitor of the NLRP3 inflammasome, substantially attenuated osteoclast formation. Conclusions: FoxO1 knockdown contributed to the inhibition of osteoclastogenesis by effectively suppressing NF‐κB signaling and NLRP3 inflammasome activation. This prospective study reveals the role of FoxO1 in mediating osteoclastogenesis and provides a viable therapeutic target for periodontitis treatment. [ABSTRACT FROM AUTHOR]

In automata networks, it is well known that the way entities update their states over time has a major impact on their dynamics. In particular, depending on the chosen update schedule, the underlying dynamical systems may exhibit more or less asymptotic dynamical behaviours such as fixed points or limit cycles. Since such mathematical models have been used in the framework of biological networks modelling, the question of choosing appropriate update schedules has arised soon. In this note, focusing on Boolean networks, our aim is to emphasise that the adequate way of thinking regulations and genetic expression over time is certainly not to consider a wall segregating synchronicity from asynchronicity because they actually complement rather well. In particular, we highlight that specific update schedules, namely block-parallel update schedules, whose intrinsic features are still not known from a theoretical point of view, admit realistic and pertinent properties in the context of biological modelling and deserve certainly more attention from the community. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to identify and characterize the 100 most cited articles on Parkinson's disease (PD) and phenolic compounds (PCs). Methods: Articles were selected in the Web of Science Core Collection up to June 2022 based on predetermined inclusion criteria, and the following bibliometric parameters were extracted: the number of citations, title, keywords, authors, year, study design, tested PC and therapeutic target. MapChart was used to create worldwide networks, and VOSviewer software was used to create bibliometric networks. Descriptive statistical analysis was used to identify the most researched PCs and therapeutic targets in PD. Results: The most cited article was also the oldest. The most recent article was published in 2020. Asia and China were the continent and the country with the most articles in the list (55 and 29%, respectively). In vitro studies were the most common experimental designs among the 100 most cited articles (46%). The most evaluated PC was epigallocatechin. Oxidative stress was the most studied therapeutic target. Conclusion: Despite the demonstrations in laboratorial studies, the results obtained point to the need for clinical studies to better elucidate this association. [ABSTRACT FROM AUTHOR]

As heart failure with preserved ejection fraction (HFpEF) rises to epidemic proportions, major steps in patient management and therapeutic development are badly needed. With the current position paper we seek to update our view on HFpEF as a highly complex systemic syndrome, from risk factors and mechanisms to long-term clinical manifestations. We will revise recent advances in animal model development, experimental set-ups and basic and translational science approaches to HFpEF research, highlighting their drawbacks and advantages. Directions are provided for proper model selection as well as for integrative functional evaluation from the in vivo setting to in vitro cell function testing. Additionally, we address new research challenges that require integration of higher-order inter-organ and inter-cell communication to achieve a full systems biology perspective of HFpEF. [ABSTRACT FROM AUTHOR]

Purpose: Over 20 years ago the term non-specific low back pain became popular to convey the limitations of our knowledge of the pathological source of most people's low back pain. Knowledge of underlying pathology has advanced little since then, despite limited improvements in outcomes for patients with low back pain. Methods: This paper discusses potential misunderstandings related to diagnostic studies in the field of low back pain and argues that future diagnostic studies should include and investigate pathological sources of low back pain. Results: Six potential misunderstandings are discussed. (1) Until diagnosis is shown to improve outcomes it is not worth investigating; (2) without a gold standard it is not possible to investigate diagnosis of low back pain; (3) the presence of pathology in some people without low back pain means it is not important; (4) dismissal of the ability to diagnose low back pain in clinical guidelines is supported by the same level of evidence as recommendations for therapy; (5) suggesting use of a diagnostic test in research is misinterpreted as endorsing its use in current clinical practice; (6) we seem to have forgotten the 'bio' in biopsychosocial low back pain. Conclusions: We believe the misunderstandings presented in this paper partly explain the lack of investigation into pathology as an important component of the low back pain experience. A better understanding of the biological component of low back pain in relation, and in addition, to psychosocial factors is important for a more rational approach to management of low back pain. [ABSTRACT FROM AUTHOR]

BACKGROUND: Schizophrenia is a highly heritable neurodevelopmental disorder. A genetic variant of microRNA-137 (miR-137) has yielded significant genome-wide association with schizophrenia, suggesting that this miRNA plays a key role in its etiology. Therefore, a molecular network of interacting miR-137 targets may provide insights into the biological processes underlying schizophrenia. METHODS: We first used bioinformatics tools to obtain and analyze predicted human and mouse miR-137 targets. We then determined miR-137 levels in rat barrel cortex after environmental enrichment (EE), a neuronal plasticity model that induces upregulation of several predicted miR-137 targets. Subsequently, expression changes of these predicted targets were examined through loss of miR-137 function experiments in rat cortical neurons. Finally, we conducted bioinformatics and literature analyses to examine the targets that were upregulated upon miR-137 downregulation. RESULTS: Predicted human and mouse miR-137 targets were enriched in neuronal processes, such as axon guidance, neuritogenesis and neurotransmission. The miR-137 levels were significantly downregulated after EE, and we identified 5 novel miR-137 targets through loss of miR-137 function experiments. These targets fit into a glucocorticoid receptor-dependent signalling network that also includes 3 known miR-137 targets with genome-wide significant association with schizophrenia. LIMITATIONS: The bioinformatics analyses involved predicted human and mouse miR-137 targets owing to lack of information on predicted rat miR-137 targets, whereas follow-up experiments were performed with rats. Furthermore, indirect effects in the loss of miR-137 function experiments cannot be excluded. CONCLUSION: We have identified a miR-137-regulated protein network that contributes to our understanding of the molecular basis of schizophrenia and provides clues for future research into psychopharmacological treatments for schizophrenia. [ABSTRACT FROM AUTHOR]

Porous Al SB 2 sb O SB 3 sb -Fap-TiO SB 2 sb composite ceramics were fabricated with a porosity of 50% to 53% and interconnected pores ranging between 43 and 280 µm. The compressive strength of the composites was measured to be 14 MPa to 18 MPa, which is higher than those of the human cancellous bone. Guidara et al. contributed a paper titled "Structural and mechanical properties of porous Al SB 2 sb O SB 3 sb -Fap-TiO SB 2 sb composite as a promising material for bone implants." The first part of this special topic on multiscale experiments and modeling in biomaterials and biological materials was published in June 2021. [Extracted from the article]

Adenostemma lavenia is a perennial herb belonging to the Compositae family and is widely distributed in the tropical parts of Asia. It has been widely used as medicine in Taiwan with the whole plant used to treat pulmonary congestion, pneumonia, bacterial infections of the respiratory tract, edema, and inflammation. This study sought to investigate the anti-inflammatory effects of A. lavenia in vitro and in animal models. The anti-inflammatory effects of ethyl acetate fractions of A. lavenia (EAAL) were stimulated with lipopolysaccharide (LPS) murine macrophages (RAW 264.7) and lung injury in mice. EAAL reduced proinflammatory cytokine responses. Preoral EAAL alleviated LPS-induced histological alterations in lung tissue and inhibited the infiltration of inflammatory cells and protein concentrations in bronchoalveolar lavage fluid (BALF). EAAL prevented protein expression of inducible NO synthase (iNOS) and cyclooxygenase-2 (COX-2); phosphorylation of I κ B- α , MAPKs, and AMP-activated protein kinase (AMPK); and activated anti-oxidant enzymes (catalase, SOD, and GPx), heme oxygenase-1 (HO-1), and nuclear factor E2-related factor 2 (Nrf2) in LPS-stimulated cells and lung tissues. Fingerprinting of EAAL was performed with HPLC to control its quality, and p -coumaric acid was found to be a major constituent. This study suggests that EAAL is a potential therapeutic agent to treat inflammatory disorders. [ABSTRACT FROM AUTHOR]

In situ observations showed phytoplankton blooms appear during winter in the Taiwan Strait (TWS), but the mechanism for bloom initiation was unclear. With the use of a coupled physical--biological numerical model, we find the winter bloom is triggered by the relaxation of the northeasterly monsoon. Thus, the aim of this study is to investigate the mechanism for bloom formation using the model. The model results show the weakening of the northeasterly wind generates a current that carries the fresh eutrophic Min-Zhe coastal water (MZCW) off the west coast of the TWS; then a stable stratification is formed in the upper ocean of the western strait, which significantly limits the turbulence. Via diagnostic analysis of the model output, we illustrate that the reduced turbulence allows the phytoplankton to accumulate within the upper layer of the western strait, which leads to an increase in chlorophyll. The analysis is further verified by the critical turbulence theory about the bloom. In addition to reduced turbulence, the lag between zooplankton and phytoplankton responses to the offshore extension of the MZCW is responsible for the formation of the bloom at the front. Therefore, we propose the observed offshore bloom in winter in the TWS is induced by the stable water stratification and the biological processes during the relaxation of the northeasterly wind. [ABSTRACT FROM AUTHOR]

The Raman spectroscopy analysis technique has found extensive applications across various disciplines due to its exceptional convenience and efficiency, facilitating the analysis and identification of diverse substances. In recent years, owing to the escalating demand for high-efficiency analytical methods, deep learning models have progressively been introduced into the realm of Raman spectroscopy. However, the application of these models to portable Raman spectrometers has posed a series of challenges due to the computational intensity inherent to deep learning approaches. This paper proposes a lightweight classification model, named RepDwNet, for identifying 28 different types of biological blood. The model integrates advanced techniques such as multi-scale convolutional kernels, depth-wise separable convolutions, and residual connections. These innovations enable the model to capture features at different scales while preserving the coherence of feature data to the maximum extent. The experimental results demonstrate that the average recognition accuracy of the model on the reflective Raman blood dataset and the transmissive Raman blood dataset are 97.31% and 97.10%, respectively. Furthermore, by applying structural reparameterization to compress the well-trained model, it maintains high classification accuracy while significantly reducing the parameter size, thereby enhancing the speed of classification inference. This makes the model more suitable for deployment in portable and mobile devices. Additionally, the proposed model can be extended to various Raman spectroscopy classification scenarios. [ABSTRACT FROM AUTHOR]

Tardigrades, with over 1450 species, are important organisms in ecological understanding and are valuable biological models (e.g., due to their extremotolerant capabilities). While their biodiversity is better known in Europe and North America, Central and South America have only recently started making significant contributions. Through a comprehensive review of scientific literature, biological collections, web portal consultations, and the addition of new records, this study clarifies the current knowledge of tardigrade biodiversity in Colombia. Past research started in the early 20th century, but most data are unreliable due to information gaps and the absence of specimens in biological collections. The last decade has witnessed a resurgence in tardigrade research in Colombia, leading to new species descriptions and a more robust understanding of their biodiversity. Nevertheless, the majority of the territory remains unexplored. A total of 43 known species from our analysis are present in Colombia: 26 records accepted by the literature and 17 questioned in the literature but representing distinct taxa surely present in Colombia. Other species records are considered doubtful. Our study recommends considering mostly scientific records based on verifiable material deposited in scientific collections (highlighting their importance in studying and safeguarding biodiversity) and encourages future researchers to contribute while adhering to legal requirements. [ABSTRACT FROM AUTHOR]

In recent years, fractional calculus (FC) has filled in a hole in traditional calculus in terms of the effect of memory, which lets us know things about the past and present and guess what will happen in the future. It is very important to have this function, especially when studying biological models and integral equations. This paper introduces developed mathematical strategies for understanding a direct arrangement of fractional integro-differential equations (FIDEs). We have presented the least squares procedure and the Legendre strategy for discussing FIDEs. We have given the form of the Caputo concept fractional order operator and the properties. We have presented the properties of the shifted Legendre polynomials. We have shown the steps of the technique to display the solution. Some test examples are given to exhibit the precision and relevance of the introduced strategies. Mathematical outcomes show that this methodology is a comparison between the exact solution and the methods suggested. To show the theoretical results gained, the simulation of suggested strategies is given in eye-catching figures and tables. Program Mathematica 12 was used to get all of the results from the techniques that were shown. [ABSTRACT FROM AUTHOR]

Dynamical system models typically involve numerous input parameters whose "effects" and orthogonality need to be quantified through sensitivity analysis, to identify inputs contributing the greatest uncertainty. Whilst prior art has compared total-order estimators' role in recovering "true" effects, assessing their ability to recover robust parameter orthogonality for use in identifiability metrics has not been investigated. In this paper, we perform: (i) an assessment using a different class of numerical models representing the cardiovascular system, (ii) a wider evaluation of sampling methodologies and their interactions with estimators, (iii) an investigation of the consequences of permuting estimators and sampling methodologies on input parameter orthogonality, (iv) a study of sample convergence through resampling, and (v) an assessment of whether positive outcomes are sustained when model input dimensionality increases. Our results indicate that Jansen or Janon estimators display efficient convergence with minimum uncertainty when coupled with Sobol and the lattice rule sampling methods, making them prime choices for calculating parameter orthogonality and influence. This study reveals that global sensitivity analysis is convergence driven. Unconverged indices are subject to error and therefore the true influence or orthogonality of the input parameters are not recovered. This investigation importantly clarifies the interactions of the estimator and the sampling methodology by reducing the associated ambiguities, defining novel practices for modelling in the life sciences. Author summary: In order to gain new insight into a biological system, one often uses mathematical models to predict possible responses from the system. One vital step when using such models is to gain knowledge of the uncertainty associated with the model responses, for any input changes. Utilising two non-linear and stiff cardiovascular models as test cases, we investigate the effects of different choices made when quantifying the uncertainty of mathematical models. Leveraging efficient solving of the mathematical model, we show that in order to truly quantify the effects of inputs on a set of outputs, one must ensure converged estimates of the inputs' influence. Our detailed study provides a robust workflow of good modelling practice for biological systems, thus ensuring a true interpretation of the uncertainty associated with model inputs. [ABSTRACT FROM AUTHOR]

Computational biological models have proven to be an invaluable tool for understanding and predicting the behaviour of many biological systems. While it may not be too challenging for experienced researchers to construct such models from scratch, it is not a straightforward task for early stage researchers. Design patterns are well-known techniques widely applied in software engineering as they provide a set of typical solutions to common problems in software design. In this paper, we collect and discuss common patterns that are usually used during the construction and execution of computational biological models. We adopt Petri nets as a modelling language to provide a visual illustration of each pattern; however, the ideas presented in this paper can also be implemented using other modelling formalisms. We provide two case studies for illustration purposes and show how these models can be built up from the presented smaller modules. We hope that the ideas discussed in this paper will help many researchers in building their own future models. [ABSTRACT FROM AUTHOR]

Neurons within the pre-Bötzinger complex have been found experimentally to exhibit different firing activities. Mixed bursting is a special firing activities which has been found in neuron model and biological experiments. The traditional fast and slow dynamics analysis method encounters some difficulties in analyzing mixed bursting. Therefore, how to analyze the dynamic mechanism of mixed bursting generation and transition is a very important issue. In this paper, based on fast-slow decomposition, multiple timescale dynamics and one- and two-parameter bifurcation analysis, we investigate the mixed bursting and their transition mechanisms in pre-Bötzinger complex neurons. The results show that the generation mechanism of the mixed bursting is related to the multiple timescale of the neuron model. The results obtained in this paper is instructive for further understanding the dynamical behaviours and generation mechanisms of complex firing activities in biological nervous systems. [ABSTRACT FROM AUTHOR]

Due to factors such as climate change, natural disasters, and deforestation, most measurement processes and initial data may have errors. Therefore, models with imprecise parameters are more realistic. This paper constructed a new predator-prey model with an interval biological coefficient by using the interval number as the model parameter. First, the stability of the solution of the fractional order model without a diffusion term and the Hopf bifurcation of the fractional order α were analyzed theoretically. Then, taking the diffusion coefficient of prey as the key parameter, the Turing stability at the equilibrium point was discussed. The amplitude equation near the threshold of the Turing instability was given by using the weak nonlinear analysis method, and different mode selections were classified by using the amplitude equation. Finally, we numerically proved that the dispersal rate of the prey population suppressed the spatiotemporal chaos of the model. [ABSTRACT FROM AUTHOR]

Bisphosphonates (BPs) have been widely, efficiently, and safely used for the treatment of osteoporosis, malignant hypercalcemia, bone metastasis of solid cancers, and multiple myeloma bone diseases. Accumulating recent reports describe that surgical dental treatments in patients with cancer or osteoporosis who have been receiving intravenous or oral BPs are associated with osteonecrosis of the jaw (bisphosphonate-related osteonecrosis of the jaw, BRONJ). The accurate incidence, clinical backgrounds, and pathogenesis of BRONJ have been unclear and appropriate approaches for prevention and treatment have not been established to date. To address the current situation of BRONJ in Japan, the "Allied Task Force Committee of Bisphosphonate-Related Osteonecrosis of the Jaw," consisting of physicians specializing in bone biology, orthopedic surgery, rheumatology, obstetrics/gynecology, and medical oncology and dentists specializing in oral surgery, periodontology, dental radiology, and oral pathology, was organized. The committee attempted to propose a standard position paper for the treatment of BRONJ. The committee expects that this proposal will provide objective and correct scientific information on BRONJ and will serve as a reference for conducting dental procedures for patients receiving BPs and in designing prevention and treatment of BRONJ. However, because this position paper is not based on direct clinical evidence, it should be used as a reference, and a decision on treatment in each case should be made after an extensive discussion among physicians, dentists/oral surgeons, and the patients. [ABSTRACT FROM AUTHOR]

Vibrational spectroscopy is a useful technique for probing chemical environments. The development of models that can reproduce the spectra of nitriles and azides is valuable because these probes are uniquely suited for investigating complex systems. Empirical vibrational spectroscopic maps are commonly employed to obtain the instantaneous vibrational frequencies during molecular dynamics simulations but often fail to adequately describe the behavior of these probes, especially in its transferability to a diverse range of environments. In this paper, we demonstrate several reasons for the difficulty in constructing a general-purpose vibrational map for methyl thiocyanate (MeSCN), a model for cyanylated biological probes. In particular, we found that electrostatics alone are not a sufficient metric to categorize the environments of different solvents, and the dominant features in intermolecular interactions in the energy landscape vary from solvent to solvent. Consequently, common vibrational mapping schemes do not cover all essential interaction terms adequately, especially in the treatment of van der Waals interactions. Quantum vibrational perturbation (QVP) theory, along with a combined quantum mechanical and molecular mechanical potential for solute–solvent interactions, is an alternative and efficient modeling technique, which is compared in this paper, to yield spectroscopic results in good agreement with experimental FTIR. QVP has been used to analyze the computational data, revealing the shortcomings of the vibrational maps for MeSCN in different solvents. The results indicate that insights from QVP analysis can be used to enhance the transferability of vibrational maps in future studies. [ABSTRACT FROM AUTHOR]

Many studies have shown that personalized exergames have a positive effect on promoting regular and proper exercise. However, there is no consensus on the design characteristics and evaluation of exergames. This systematic review of published research literature aimed to explore the general characteristics, personalization characteristics, and evaluation of personalized exergames for middle-aged and older people. We screened published studies in the Web of Science, Scopus, PubMed, ACM, and IEEE Xplore databases, extracted data, and performed a thematic analysis according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. Three main themes and nine subthemes were generated from 24 included papers. Moreover, a personalization model (FACTS) and evaluation system (PMSS) of exergames were developed. Personalized exergames had potential positive effects on motivating middle-aged and older people to exercise and improve their health, particularly physical, mental, and social health. However, more fine-grained studies on personalized exergames are necessary in the future. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization of the generalized Lotka–Volterra (GLV) biological model, which is affected by the asymptotically unbounded external disturbances, and presents some new results. Firstly, two stabilizers are proposed for the nominal GLV system. Then, some appropriate filters are designed and applied to asymptotically track the corresponding disturbances. Based on these filters, two disturbance-estimator (DE)-based controllers are presented to cancel the corresponding disturbances. Compared to the existing results, the advantage of this paper is in handling the asymptotically unbounded external disturbances effectively. Finally, the correctness and effectiveness of the proposed results are verified by computer simulation. [ABSTRACT FROM AUTHOR]

This paper presents an analytical solution to the model. By solving the system of nonlinear reaction-diffusion equations using Akbari–Ganji's method (AGM), we can derive the semi-analytical expressions for substrate and oxidized and reduced mediator concentrations. These models provide information about enzyme electrode mechanisms and their kinetics. These modeling results can be helpful for sensor design, optimization, and determining how the electrode will react. Further, we studied the effects of many physical and biological parameters on model prediction. The mathematical equations, which are nonlinear partial differential equations, are solved using AGM. Also, we derived the semi-analytical results for concentrations for saturated and unsaturated kinetics. It is verified that the proposed solution is validated by comparing it with numerical solutions. [ABSTRACT FROM AUTHOR]

We examine a biological population model of fractional order (FBPM) in this paper using the Riccati-Bernoulli sub-ODE approach. Many scenarios in computational biology make use of this fundamental fractional model. Of particular note is that our study's FBPM uses fractional derivatives to track changes in the density populations. The study is concerned with the construction of new solitary wave solutions for the FBPM, a system of two nonlinear fractional ordinary differential equations. In this investigation, we use the conformable derivative as the fractional derivative. The Backlund transformation is the foundation of the solution process. We create a variety of families of soliton wave solutions and explain different physical behaviours that are inherent in the problems we explore. In particular, we apply the suggested methods to investigate rational, periodic, and hyperbolic solutions. The solutions found in various classes provide insightful information about the underlying physical mechanisms. To sum up, our current methods are superior instruments for analyzing different families of solutions in fractional-order issues. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient Newton linearized numerical method for the nonlinear time-fractional parabolic equations with distributed delay based on the Galerkin finite element method in space and the nonuniform L1 scheme in time. The term of distributed delay is approximated by using the compound trapezoidal formula. For the constructed numerical scheme, we mainly focus on the unconditional convergence and superconvergence without any time–space ratio restrictions, the key of which is the use of fractional discrete Grönwall inequality and time–space error splitting technique. Numerical tests for several biological models, including the fractional single-species population model with distributed delay, the fractional diffusive Nicholson's blowflies equation with distributed delay, and the fractional diffusive Mackey-Glass equation with distributed delay, are conducted to confirm the theoretical results. Finally, combined with the nonunifom Alikhanov scheme in time and the FEM in space, we extend a higher-order Newton linearized numerical scheme for the nonlinear time-fractional parabolic equations with distributed delay and give some numerical tests for some biological models. [ABSTRACT FROM AUTHOR]

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: The aims of this study were to label the versatile amino acid l-lysine with 99mTc using 2,3-dimercapto-succinic acid (DMSA) as a chelator, and to assess its tumor imaging feasibility under in vivo and in vitro conditions, and finally to determine the subcellular biodistribution of this radiopharmaceutical. Materials and Methods: DMSA-l-lysine was chemically synthesized and labeled with sodium pertechnetate. Nuclear magnetic resonance (NMR) and mass spectral analysis of DMSA-l-lysine were conducted. Radiochemical purity was determined by thin-layer chromatography (TLC) and paper chromatography. Cellular uptake, competition and subcellular localization studies were performed in rat breast cancer cells (13762). In vivo studies of planar imaging and biodistribution studies were performed on female Fischer 344 rats. Medical Internal Radiation Dose (MIRD) dosimetry estimates were calculated. Results: Radiochemical purity (determined by radio-TLC and high-performance liquid chromatography) of these compounds was >95%. 99mTc-DMSA-l-lysine showed good uptake in in vitro cell culture assays and uptake was reduced in competition studies. 99mTc-DMSA-l-lysine accumulates in the nucleus as much as in the cytoplasm and it was also shown that accumulation of the 99mTc-DMSA-l-lysine in the nucleus increases as a function of a time. There was an increase in tumor-to-blood and tumor-to-muscle count density ratios. Tumor/background ratios were 5.75 at 1 hour and 6.87 at 2 hours. In vivo tissue distribution studies revealed that radiation dosimetry of blood-forming organs were within radiation dose limits. Conclusion: DMSA-l-lysine kits can be labeled with 99mTc easily and efficiently, with high radiochemical purity and cost-effectiveness. In vitro cellular uptake and scintigraphic imaging studies demonstrated the pharmacokinetic distribution and feasibility of using 99mTc-DMSA-l-lysine for tumor imaging. [Copyright &y& Elsevier]

Currently, many methods that could estimate the effects of conditions on a given biological target require either strong modelling assumptions or separate screens. Traditionally, many conditions and targets, without doing all possible experiments, could be achieved by driven experimentation or several mathematical methods, especially conversational machine learning methods. However, these methods still could not avoid and replace manual labels completely. This paper presented a meta-active machine learning method to resolve this problem. This project has used nine traditional machine learning methods to compare their accuracy and running time. In addition, this paper analyzes the meta-active machine learning method (MAML) compared with a classical screening method and progressive experiments. The obtained results show that applying this method yields the best experimental results on the current dataset. [ABSTRACT FROM AUTHOR]

Background: Myocardial infarction (MI) is a major cause of heart failure. The carboxypeptidase cathepsin A is a novel target in the treatment of cardiac failure. We aim to show that recently developed inhibitors of the protease cathepsin A attenuate post-MI heart failure.Methods: Mice were subjected to permanent left anterior descending artery (LAD) ligation or sham operation. 24 h post-surgery, LAD-ligated animals were treated with daily doses of the cathepsin A inhibitor SAR1 or placebo. After 4 weeks, the three groups (sham, MI-placebo, MI-SAR1) were evaluated.Results: Compared to sham-operated animals, placebo-treated mice showed significantly impaired cardiac function and increased plasma BNP levels. Cathepsin A inhibition prevented the increase of plasma BNP levels and displayed a trend towards improved cardiac functionality. Proteomic profiling was performed for the three groups (sham, MI-placebo, MI-SAR1). More than 100 proteins were significantly altered in placebo-treated LAD ligation compared to the sham operation, including known markers of cardiac failure as well as extracellular/matricellular proteins. This ensemble constitutes a proteome fingerprint of myocardial infarction induced by LAD ligation in mice. Cathepsin A inhibitor treatment normalized the marked increase of the muscle stress marker CA3 as well as of Igγ 2b and fatty acid synthase. For numerous further proteins, cathepsin A inhibition partially dampened the LAD ligation-induced proteome alterations.Conclusions: Our proteomic and functional data suggest that cathepsin A inhibition has cardioprotective properties and support a beneficial effect of cathepsin A inhibition in the treatment of heart failure after myocardial infarction. [ABSTRACT FROM AUTHOR]

Controller motifs are simple biomolecular reaction networks with negative feedback. They can explain how regulatory function is achieved and are often used as building blocks in mathematical models of biological systems. In this paper we perform an extensive investigation into structural identifiability of controller motifs, specifically the so–called basic and antithetic controller motifs. Structural identifiability analysis is a useful tool in the creation and evaluation of mathematical models: it can be used to ensure that model parameters can be determined uniquely and to examine which measurements are necessary for this purpose. This is especially useful for biological models where parameter estimation can be difficult due to limited availability of measureable outputs. Our aim with this work is to investigate how structural identifiability is affected by controller motif complexity and choice of measurements. To increase the number of potential outputs we propose two methods for including flow measurements and show how this affects structural identifiability in combination with, or in the absence of, concentration measurements. In our investigation, we analyze 128 different controller motif structures using a combination of flow and/or concentration measurements, giving a total of 3648 instances. Among all instances, 34% of the measurement combinations provided structural identifiability. Our main findings for the controller motifs include: i) a single measurement is insufficient for structural identifiability, ii) measurements related to different chemical species are necessary for structural identifiability. Applying these findings result in a reduced subset of 1568 instances, where 80% are structurally identifiable, and more complex/interconnected motifs appear easier to structurally identify. The model structures we have investigated are commonly used in models of biological systems, and our results demonstrate how different model structures and measurement combinations affect structural identifiability of controller motifs. Author summary: Creating a mathematical model of a biological system can be a powerful way to gain insight into the behavior of the system. However, the accuracy and quality of model predictions depend heavily on model parameters. Compared to traditional human–engineered systems, such as mechanical or electrical systems, the availability of measurable outputs is severely limited for many biological systems. Furthermore, parameter estimation for biological models is often both challenging and associated with high cost. In this context, structural identifiability analysis is a helpful tool for finding the smallest or easiest to perform set of measurements that is sufficient to uniquely determine the model parameters. In this paper, we investigate a group of biological models called controller motifs, and we examine how varying model complexity and choice of measurements affect structural identifiability. We propose two alternative ways to include flow measurements as model output and show that structural identifiability can be achieved using a combination of concentration and/or flow measurements. Controller motifs can be used in a wide range of biological models, and our results can contribute to create structurally identifiable models. [ABSTRACT FROM AUTHOR]

Discrete fractional models with reaction-diffusion have gained significance in the scientific field in recent years, not only due to the need for numerical simulation but also due to the stated biological processes. In this paper, we investigate the problem of synchronization-control in a fractional discrete nonlinear bacterial culture reaction-diffusion model using the Caputo h-difference operator and a second-order central difference scheme and an L1 finite difference scheme after deriving the discrete fractional version of the well-known Degn–Harrison system and Lengyel–Epstein system. Using appropriate techniques and the direct Lyapunov method, the conditions for full synchronization are determined.Furthermore, this research shows that the L1 finite difference scheme and the second-order central difference scheme may successfully retain the properties of the related continuous system. The conclusions are proven throughout the paper using two major biological models, and numerical simulations are carried out to demonstrate the practical use of the recommended technique. [ABSTRACT FROM AUTHOR]

Combining different features inspired by biological systems is necessary to obtain uncommon and unique multifunctional biologically inspired conceptual designs. The Expandable Domain Integrated Design (xDID) model is proposed to facilitate the multifunctional concept generation process. The xDID model extends the previously defined Domain Integrated Design (DID) method. The xDID model classifies biological features by their feature characteristics taken from various case-based bio-inspired design examples into their respective geometric designations called domains. The classified biological features are mapped to the respective plant and animal tissues from which they originate. Furthermore, the paper proposes a representation of the functions exhibited by the biological features at the embodiment level as a combination of the integrated structure (multiscale) and the structural strategy associated with the integrated structure. The xDID model is validated using three multifunctional bio-inspired design case studies at the end of the paper. [ABSTRACT FROM AUTHOR]

Simple Summary: The word "model" can be used with different meanings and different contexts, like a model student, clay models or a model railway. In some cases, the context can clarify exactly what is meant by "model", but sometimes several meanings of model can be present in one area. For instance, with reference to cancer research, there can be ambiguity for what is meant by model. This paper reviews the use of the word model as related to cancer research and within the specific area of the microenvironment that surrounds a cancer tumour. The review grouped different definitions of model into four categories (model organisms, in vitro models, mathematical models and computational models) and explored what is meant in each case, mentioning the advantages and disadvantages of the different models Next, a quantitative investigation of the scientific publications listed in the database of the United States National Library of Medicine was performed by counting the frequencies of use of these terms, as well as the components of the microenvironments and the organs modelled with these techniques. The Oxford English Dictionary includes 17 definitions for the word "model" as a noun and another 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For instance, "model railways" refer to replicas of railways and trains at a smaller scale and a "model student" refers to an exemplary individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning for model. Even if the context is narrowed, specifically, to research related to the tumour microenvironment, "model" can be understood in a wide variety of ways, from an animal model to a mathematical expression. This paper presents a review of different "models" of the tumour microenvironment, as grouped by different definitions of the word into four categories: model organisms, in vitro models, mathematical models and computational models. Then, the frequencies of different meanings of the word "model" related to the tumour microenvironment are measured from numbers of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequencies of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, particularly xenografts and mouse models, are the most commonly used "models", the number of these entries has been slowly decreasing. Mathematical models, as well as prognostic and risk models, follow in frequency, and these have been growing in use. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 has posed a threat to the health of people around the world because of its strong transmission and high virulence. Currently, there is no specific medicine for the treatment of COVID-19. However, for a wide variety of medicines used to treat COVID-19, traditional Chinese medicine (TCM) plays a major role. In this paper, the effective treatment of COVID-19 using TCM was consulted first, and several Chinese medicines that were frequently used apart from their huge role in treating it were found. Then, when exploring the active ingredients of these herbs, it was discovered that most of them contained flavonoids. Therefore, the structure and function of the potential active substances of flavonoids, including flavonols, flavonoids, and flavanes, respectively, are discussed in this paper. According to the screening data, these flavonoids can bind to the key proteins of SARS-CoV-2, 3CLpro, PLpro, and RdRp, respectively, or block the interface between the viral spike protein and ACE2 receptor, which could inhibit the proliferation of coronavirus and prevent the virus from entering human cells. Besides, the effects of flavonoids on the human body systems are expounded on in this paper, including the respiratory system, digestive system, and immune system, respectively. Normally, flavonoids boost the body's immune system. However, they can suppress the immune system when over immunized. Ultimately, this study hopes to provide a reference for the clinical drug treatment of COVID-19 patients, and more TCM can be put into the market accordingly, which is expected to promote the development of TCM on the international stage. [ABSTRACT FROM AUTHOR]

Background: Marijuana and alcohol are both substances that, when used during pregnancy, may have profound effects on the developing fetus. There is evidence to suggest that both drugs have the capacity to affect working memory, one function of the hippocampal formation; however, there is a paucity of data on how perinatal exposure to alcohol or cannabis impacts the process of adult neurogenesis. Methods: This systematic review examines immunohistochemical data from adult rat and mouse models that assess perinatal alcohol or perinatal marijuana exposure. A comprehensive list of search terms was designed and used to search 3 separate databases. All results were imported to Mendeley and screened by 2 authors. Consensus was reached on a set of final papers that met the inclusion criteria, and their results were summarized. Results: Twelve papers were identified as relevant, 10 of which pertained to the effects of perinatal alcohol on the adult hippocampus, and 2 pertained to the effects of perinatal marijuana on the adult hippocampus. Cellular proliferation in the dentate gyrus was not affected in adult rats and mice exposed to alcohol perinatally. In general, perinatal alcohol exposure did not have a significant and reliable effect on the maturation and survival of adult born granule neurons in the dentate gyrus. In contrast, interneuron numbers appear to be reduced in the dentate gyrus of adult rats and mice exposed perinatally to alcohol. Perinatal marijuana exposure was also found to reduce inhibitory interneuron numbers in the dentate gyrus. Conclusions: Perinatal alcohol exposure and perinatal marijuana exposure both act on inhibitory interneurons in the hippocampal formation of adult rats. These findings suggest simultaneous perinatal alcohol and marijuana exposure (SAM) may have a dramatic impact on inhibitory processes in the dentate gyrus. [ABSTRACT FROM AUTHOR]

In the past few years Micron has revised the scope of the journal, bringing it back to its original core values when it was founded in 1969. Micron's aim is to be the leading international microscopy and microanalysis journal, covering the latest advances in the fields of biological and physical science. In order to achieve this, the editorial team carefully revised the guidelines to authors in 2011. As a team we now find it timely to report on the outcomes of this policy change. [ABSTRACT FROM AUTHOR]

An eddy-resolving coupled physical-biological ocean model has been employed to investigate the physical influences on phytoplankton blooms in the South China Sea during 2000-2007. The model captures the seasonal and interannual variability of surface chlorophyll distribution associated with mesoscale eddies, ocean circulation and up-welling generated by the monsoon winds. The model also reproduces the high chlorophyll distributions in two coastal upwelling regions: the northwestern Luzon in winter and the eastern coast of Vietnam in summer. To the northwest of Luzon, the monsoon driven-upwelling, anticyclonic eddies, and the intrusion of the Kuroshio have a large impact on the winter phytoplankton bloom. The model shows the winter phytoplankton bloom is induced by the shallow nutricline depth under the northeast monsoon. Strong vertical motions at the edge of anticyclonic eddies enhance the phytoplankton bloom and produce the filamentary structure. Off the eastern coast of Vietnam, the monsoon-driven upwelling and anticyclonic circulation control the high chlorophyll distribution in summer. During the southwest monsoon, strong offshore Ekman transport and up-welling occur and increase the surface chlorophyll. The high chlorophyll is advected from the coast to open ocean by the strong offshore circulation. [ABSTRACT FROM AUTHOR]

This discussion paper focuses on validity and reliability concerns associated with the PCK methodology. Examples of subtle validity issues from the product-testing arena are presented to illustrate the importance of validity issues, even with use of the strongest of all experimental designs, the randomized controlled clinical trial. Findings from two specific profile models are presented to illustrate the need for validating that a surrogate marker for dental caries is indeed a marker. Careful use of the two-stage PCK testing procedure is recommended, but only for intra-oral model response measures which are bona fide surrogate markers for dental caries in humans. [ABSTRACT FROM AUTHOR]

It is essential that we understand the dose-response mechanisms of fluoride delivered intra-orally at sites in intimate contact with dental tissues. Many studies show that extremely low levels of fluoride can inhibit caries. However, few of these studies provide a direct comparison between fluoride release and the inhibition of secondary caries. For this, laboratory, animal, and in situ caries models are required which can predict clinical efficacy. This paper supplements Dr. Erickson's presentation (Erickson and Glasspoole, 1995) by illustrating the adaptation of currently used demineralization and caries models to the development and evaluation of fluoride-containing resin materials. As representative of this class of material, those which release by ion-exchange are reviewed. It is concluded that model systems designed for topical fluorides and non-fluoride dental materials can be adapted for use with fluoride-releasing materials. Further, the use of materials with a long history of clinical efficacy as inhibitors of marginal caries, such as the silicates, is a useful means of determining target values for developing new fluoride-releasing materials. The minimum concentration of F- that must be maintained in the immediate vicinity of a material to provide caries protection at localized sites is not yet known. Nor is it known what combination of release rate, pattern of release, and duration of release is needed to optimize either localized or full-mouth protection. These issues deserve closer examination to aid our understanding of F- action when delivered from dental materials, so that improved caries model systems can be designed for use with dental materials. [ABSTRACT FROM AUTHOR]

In his conference presentation, Proskin discussed the concepts of validity and reliability of caries models, and reviewed the Proskin-Chilton-Kingman procedure for using models to assess the clinical efficacy of a therapeutic agent. He presented a generally positive view of caries models as substitutes for clinical studies under certain conditions. In this reaction paper I propose a stronger definition of validity, and discuss conceptual and practical requirements that caries models must meet before they can be used in place of clinical studies. Meeting these requirements may depend on obtaining new clinical data; making greater use of existing clinical data; and a willingness to adopt a limited set of standardized models for demonstrating clinical efficacy. [ABSTRACT FROM AUTHOR]

In situ caries models can be found in all shapes and sizes and designed for many purposes. Building on previous conferences, Dr. Zero has done a remarkable job in summarizing the many aspects of in situ models, and as such this reactor's paper will be restricted to only several aspects of the model. One of the most important steps in using in situ models involves the reporting of enough details and reasons for choices in model parameters so that the reviewer or reader can judge clinical relevance and applicability. This approach tends to broaden the field as much as restrict it to only one substrate, evaluative technique, or appliance type. Continued work needs to be done on both surface and subsurface lesions; there is a need to establish "gold standards" for model validation in areas such as salivary flow, antimicrobials, food sequencing, etc., and the clinical relevance of each model needs to be explored. [ABSTRACT FROM AUTHOR]

Objective. In this paper, we present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations of microdosimetric distributions with radiobiological microdosimetry-based models for predicting cell survival curves and dose-dependent RBE. Approach. MONAS expands TOPAS microdosimetric extension, by including novel specific energy scorers to calculate the single- and multi-event specific energy microdosimetric distributions at different micrometer scales. These spectra are used as physical input to three different formulations of the microdosimetric kinetic m odel, and to the generalized stochastic microdosimetric model (GSM2), to predict dose-dependent cell survival fraction and RBE. MONAS predictions are then validated against experimental microdosimetric spectra and in vitro survival fraction data. To show the MONAS features, we present two different applications of the code: (i) the depth-RBE curve calculation from a passively scattered proton SOBP and monoenergetic 12C-ion beam by using experimentally validated spectra as physical input, and (ii) the calculation of the 3D RBE distribution on a real head and neck patient geometry treated with protons. Main results. MONAS can estimate dose-dependent RBE and cell survival curves from experimentally validated microdosimetric spectra with four clinically relevant radiobiological models. From the radiobiological characterization of a proton SOBP and 12C fields, we observe the well-known trend of increasing RBE values at the distal edge of the radiation field. The 3D RBE map calculated confirmed the trend observed in the analysis of the SOBP, with the highest RBE values found in the distal edge of the target. Significance. MONAS extension offers a comprehensive microdosimetry-based framework for assessing the biological effects of particle radiation in both research and clinical environments, pushing closer the experimental physics-based description to the biological damage assessment, contributing to bridging the gap between a microdosimetric description of the radiation field and its application in proton therapy treatment with variable RBE. [ABSTRACT FROM AUTHOR]

Successful bioinspired design depends on practitioners' access to biological data in a relevant form. Although multiple open-access biodiversity databases exist, their presentation is often adapted to life scientists, rather than bioinspired designers. In this paper, we present a new tool, "Bioinspire-Explore", for navigating biodiversity data in order to uncover biological systems of interest for a range of sectors. Bioinspire-Explore allows users to search for inspiring biological models via taxa (species, genera, etc.) as an entry point. It provides information on a taxon's position in the "tree of life", its distribution and climatic niche, as well as its appearance. Bioinspire-Explore also shows users connections in the bioinspiration literature between their taxon of interest and associated biological processes, habitats, and physical measurements by way of their semantic proximity. We believe Bioinspire-Explore has the potential to become an indispensable resource for both biologists and bioinspired designers in different fields. [ABSTRACT FROM AUTHOR]

For patients who had testicular tissue cryopreserved before receiving gonadotoxic therapies, transplantation of testicular tissues and cells has been recommended as a potential therapeutic option. There are no studies that indicate the generation of sperm after human immature testicular tissue (ITT) or spermatogonial stem cells (SSCs) transplantation. The use of releasing scaffolds and localized drug delivery systems as well as the optimizing transplantation site can play an effective role in increasing the efficiency and improving the quality of testicular tissue and cell transplantation in animal models. Current research is focused on optimizing ITT and cell transplantation, the use of releasing scaffolds, and the selection of the right transplantation site that might restore sperm production or male infertility treatment. By searching the PubMed and Google Scholar databases, original and review papers were collected. Search terms were relevant for SSCs and tissue transplantation. In this review, we'll focus on the potential advantages of using scaffolds and choosing the right transplantation site to improve transplantation outcomes. [ABSTRACT FROM AUTHOR]

Analysis of the method of using sonography during surgery in animals with polycystic kidney disease is an urgent task since firstly, sonography is a safe and non-invasive method of examination, which allows determining the structural features of the kidneys before, during, and after surgery. Secondly, from the standpoint of improving the results of surgery, sonography helps to clarify the localisation of cysts and determine their size. Thirdly, an important factor in the use of sonography is the reduction of pain and the risk of postoperative complications. In addition, due to this method of kidney examination, it is possible to more accurately determine the optimal route of access to cysts, which helps to reduce tissue injury and ensures rapid recovery of the animal after surgery. The purpose of the study is to analyse in detail and describe the method of using sonography during surgery in animals with polycystic kidney disease. The study focuses on the need to determine how sonography affects reducing the duration of surgery, improving the quality of cyst removal, and reducing the risk of complications during abdominal surgery. The approach in this study is based on the analysis of scientific papers on this subject, in particular on the experience of veterinarians who have already used sonography during abdominal operations in animals with polycystic kidney disease. Thus, special techniques of sonography and surgical treatment of kidney cysts include dopplerography, colour dopplerography, 3D and 4D sonography, elastography, introperative sonography, intraperitoneal sonography, and duplex scanning of renal arteries and veins. Surgical methods of treatment include extraction of individual cysts, drainage of cysts, resection, and nephrectomy. The use of sonography at different stages of surgical intervention helps to optimise the operation process, reduce the risk of complications, and contribute to the introduction of new approaches in the treatment of animals with polycystic kidney disease, which will substantially improve their quality of life [ABSTRACT FROM AUTHOR]

The gut microbiota (GM), as a forgotten organ, refers to the microbial community that resides in the gastrointestinal tract and plays a critical role in a variety of physiological activities in different body organs. The GM affects its targets through neurological, metabolic, immune, and endocrine pathways. The GM is a dynamic system for which exogenous and endogenous factors have negative or positive effects on its density and composition. Since the mid-twentieth century, laboratory animals are known as the major tools for preclinical research; however, each model has its own limitations. So far, two main models have been used to explore the effects of the GM under normal and abnormal conditions: the isolated germ-free and antibiotic-treated models. Both methods have strengths and weaknesses. In many fields of host-microbe interactions, research on these animal models are known as appropriate experimental subjects that enable investigators to directly assess the role of the microbiota on all features of physiology. These animal models present biological model systems to either study outcomes of the absence of microbes, or to verify the effects of colonization with specific and known microbial species. This paper reviews these current approaches and gives advantages and disadvantages of both models. [ABSTRACT FROM AUTHOR]