An integrated method for phenotypic analysis of wheat based on multi-view image sequences: from seedling to grain filling stages.

Wheat exhibits complex characteristics during its growth, such as extensive tillering, slender and soft leaves, and severe organ cross-obscuration, posing a considerable challenge in full-cycle phenotypic monitoring. To address this, this study presents a synthesized method based on SFM-MVS (Structure-from-Motion, Multi-View Stereo) processing for handling and segmenting wheat point clouds, covering the entire growth cycle from seedling to grain filling stages. First, a multi-view image acquisition platform was constructed to capture image sequences of wheat plants, and dense point clouds were generated using SFM-MVS technology. High-quality dense point clouds were produced by implementing improved Euclidean clustering combined with centroids, color filtering, and statistical filtering methods. Subsequently, the segmentation of wheat plant stems and leaves was performed using the region growth segmentation algorithm. Although segmentation performance was suboptimal during the tillering, jointing, and booting stages due to the glut leaves and severe overlap, there was a salient improvement in wheat leaf segmentation efficiency over the entire growth cycle. Finally, phenotypic parameters were analyzed across different growth stages, comparing automated measurements of plant height, leaf length, and leaf width with actual measurements. The results demonstrated coefficients of determination ( R 2 ) of 0.9979, 0.9977, and 0.995; root mean square errors (RMSE) of 1.0773 cm, 0.2612 cm, and 0.0335 cm; and relative root mean square errors (RRMSE) of 2.1858%, 1.7483%, and 2.8462%, respectively. These results validate the reliability and accuracy of our proposed workflow in processing wheat point clouds and automatically extracting plant height, leaf length, and leaf width, indicating that our 3D reconstructed wheat model achieves high precision and can quickly, accurately, and non-destructively extract phenotypic parameters. Additionally, plant height, convex hull volume, plant surface area, and Crown area were extracted, providing a detailed analysis of dynamic changes in wheat throughout its growth cycle. ANOVA was conducted across different cultivars, accurately revealing significant differences at various growth stages. This study proposes a convenient, rapid, and quantitative analysis method, offering crucial technical support for wheat plant phenotypic analysis and growth dynamics monitoring, applicable for precise full-cycle phenotypic monitoring of wheat.

A generalized numerical model for clonal growth in scleractinian coral colonies.

Coral reefs, vital ecosystems supporting diverse marine life, are primarily shaped by the clonal expansion of coral colonies. Although the principles of coral clonal growth, involving polyp division for spatial extension, are well-understood, numerical modelling efforts are notably scarce in the literature. In this article, we present a parsimonious numerical model based on the cloning of polyps, using five key parameters to simulate a range of coral shapes. The model is agent-based, where each polyp represents an individual. The colony's surface expansion is dictated by the growth mode parameter (s), guiding the preferred growth direction. Varying s facilitates the emulation of diverse coral shapes, including massive, branching, cauliflower, columnar and tabular colonies. Additionally, we introduce a novel approach for self-regulatory branching, inspired by the intricate mesh-like canal system and internode regularity observed in Acropora species. Through a comprehensive sensitivity analysis, we demonstrate the robustness of our model, paving the way for future applications that incorporate environmental factors, such as light and water flow. Coral colonies are known for their high plasticity, and understanding how individual polyps interact with each other and their surroundings to create the reef structure has been a longstanding question in the field. This model offers a powerful framework for studying these interactions, enabling a future implementation of environmental factors and the possibility of identifying the key mechanisms influencing coral colonies' morphogenesis.

Controlled Morphological Growth and Photonic Lasing in Cesium Lead Bromide Microcrystals.

Morphology plays a crucial role in defining the optical, electronic, and mechanical properties of halide perovskite microcrystals. Therefore, developing strategies that offer precise control over crystal morphology during the growth process is highly desirable. This work presents a simple scheme to simultaneously grow distinct geometries of cesium lead bromide (CsPbBr3) microcrystals, including microrods (MR), microplates (MP), and microspheres (MS), in a single chemical vapor deposition (CVD) experiment. By strategically adjusting precursor evaporation temperatures, flux density, and the substrate temperature, we surpass previous techniques by achieving simultaneous yet selective growth of multiple CsPbBr3 geometries at distinct positions on the same substrate. This fine growth control is attributed to the synergistic variation in fluid flow dynamics, precursor substrate distance, and temperature across the substrate, offering regions suitable for the growth of different morphologies. Pertinently, perovskite MR are grown at the top, while MP and MS are observed at the center and bottom regions of the substrate, respectively. Structural analysis reveals high crystallinity and an orthorhombic phase of the as-grown perovskite microcrystals, while persistent photonic lasing manifests their nonlinear optical characteristics, underpinning their potential application for next-generation photonic and optoelectronic devices.

Non-Invasive Quality Control of Organoid Cultures Using Mesofluidic CSTR Bioreactors and High-Content Imaging.

Human brain organoids produce anatomically relevant cellular structures and recapitulate key aspects of in vivo brain function, which holds great potential to model neurological diseases and screen therapeutics. However, the long growth time of 3D systems complicates the culturing of brain organoids and results in heterogeneity across samples hampering their applications. We developed an integrated platform to enable robust and long-term culturing of 3D brain organoids. We designed a mesofluidic bioreactor device based on a reaction-diffusion scaling theory, which achieves robust media exchange for sufficient nutrient delivery in long-term culture. We integrated this device with longitudinal tracking and machine learning-based classification tools to enable non-invasive quality control of live organoids. This integrated platform allows for sample pre-selection for downstream molecular analysis. Transcriptome analyses of organoids revealed that our mesofluidic bioreactor promoted organoid development while reducing cell death. Our platform thus offers a generalizable tool to establish reproducible culture standards for 3D cellular systems for a variety of applications beyond brain organoids.

Growth dynamics of lung nodules: implications for classification in lung cancer screening.

BACKGROUND: Lung nodules observed in cancer screening are believed to grow exponentially, and their associated volume doubling time (VDT) has been proposed for nodule classification. This retrospective study aimed to elucidate the growth dynamics of lung nodules and determine the best classification as either benign or malignant. METHODS: Data were analyzed from 180 participants (73.7% male) enrolled in the I-ELCAP screening program (140 primary lung cancer and 40 benign) with three or more annual CT examinations before resection. Attenuation, volume, mass and growth patterns (decelerated, linear, subexponential, exponential and accelerated) were assessed and compared as classification methods. RESULTS: Most lung cancers (83/140) and few benign nodules (11/40) exhibited an accelerated, faster than exponential, growth pattern. Half (50%) of the benign nodules versus 26.4% of the malignant ones displayed decelerated growth. Differences in growth patterns allowed nodule malignancy to be classified, the most effective individual variable being the increase in volume between two-year-interval scans (ROC-AUC = 0.871). The same metric on the first two follow-ups yielded an AUC value of 0.769. Further classification into solid, part-solid or non-solid, improved results (ROC-AUC of 0.813 in the first year and 0.897 in the second year). CONCLUSIONS: In our dataset, most lung cancers exhibited accelerated growth in contrast to their benign counterparts. A measure of volumetric growth allowed discrimination between benign and malignant nodules. Its classification power increased when adding information on nodule compactness. The combination of these two meaningful and easily obtained variables could be used to assess malignancy of lung cancer nodules.

Dendrochronological Analysis of Pinus pinea in Central Chile and South Spain for Sustainable Forest Management.

Pinus pinea is an important Mediterranean species due to its adaptability and tolerance to aridity and its high-quality pine nuts. Different forest types located in Mediterranean native and non-native environments provide the opportunity to perform comparative studies on the species' response to climate change. The aims of this study were to elucidate growth patterns of the species growing in native and exotic habitats and to analyze its response to climatic fluctuations, particularly drought, in both geographical contexts. Understanding stone pine (Pinus pinea) growth responses to climate variability in native and exotic habitats by comparing natural stands and plantations may provide useful information to plan adequate management under climate change. By doing so, we enhance the understanding of P. pinea's adaptability and provide practical approaches to its sustainable management. In this study, we reconstructed and compared the stem radial growth of seven stone pine stands, two in southern Spain and five in central-southern Chile, growing under different climatic conditions. We quantified the relationships between growth variability and climate variables (total rainfall, mean temperature, and SPEI drought index). Growth was positively correlated with autumn rainfall in plantations and with autumn-winter rainfall in natural stands. Growth was also enhanced by high autumn-to-spring rainfall in the driest Chilean plantation, whereas in the wettest and coolest plantation, such correlation was found in winter and summer. A negative impact of summer temperature was found only in one of the five Chilean plantations and in a Spanish site. The correlation between SPEI and tree-ring width indices showed different patterns between and within countries. Overall, exotic plantations showed lower sensitivity to climate variability than native stands. Therefore, stone pine plantations may be useful to assist in mitigating climate change.

Followers do not dictate the virality of news outlets on social media.

Initially conceived for entertainment, social media platforms have profoundly transformed the dissemination of information and consequently reshaped the dynamics of agenda-setting. In this scenario, understanding the factors that capture audience attention and drive viral content is crucial. Employing Gibrat's Law, which posits that an entity's growth rate is unrelated to its size, we examine the engagement growth dynamics of news outlets on social media. Our analysis includes the Facebook historical data of over a thousand news outlets, encompassing approximately 57 million posts in four European languages from 2008 to the end of 2022. We discover universal growth dynamics according to which news virality is independent of the traditional size of the outlet. Moreover, our analysis reveals a significant long-term impact of news source reliability on engagement growth, with engagement induced by unreliable sources decreasing over time. We conclude the article by presenting a statistical model replicating the observed growth dynamics.

Modelling the colony growth dynamics of Listeria monocytogenes single cells after exposure to peracetic acid and acidic conditions.

Studies of classical microbiology rely on the average behaviour of large cell populations without considering that clonal bacterial populations may bifurcate into phenotypic distinct sub-populations by random switching mechanisms.Listeria monocytogenes exposure to sublethal stresses may induce different physiological states that co-exist (i.e., sublethal injury or dormancy) and present variable resuscitation capacity. Exposures to peracetic acid (PAA; 10-30 ppm; for 3 h), acetic acid and hydrochloric acid (AA and HCl; pH 3.0-2.5; for 5 h) at 20 °C were used to induce different physiological states in L. monocytogenes, Scott A strain. After stress exposure, colony growth of single cells was monitored, on Tryptic Soy Agar supplemented with 0.6 % Yeast Extract, using time-lapse microscopy, at 37 °C. Images were acquired every 5 min and were analyzed using BaSCA framework. Most of the obtained growth curves of the colonies were fitted to the model of Baranyi and Roberts for the estimation of lag time (λ) and maximum specific growth rate (µmax), except the ones obtained after exposure to AA pH 2.7 and 2.5 that were fitted to the Trilinear model. The data of λ and µmax that followed a multivariate normal distribution were used to predict growth variability using Monte Carlo simulations. Outgrowth kinetics after treatment with AA (pH 2.7 and 2.5; for 5 h at 20 °C), PAA (30 ppm; for 3 h at 20 °C) revealed that these stress conditions increase the skewness of the variability distributions to the right, meaning that the variability in lag times increases in favour of longer outgrowth. Exposures to AA pH 2.5 and 30 ppm PAA resulted in two distinct subpopulations per generation with different growth dynamics. This switching mechanism may have evolved as a survival strategy for L. monocytogenes cells, maximizing the chances of survival. Simulation of microbial growth showed that heterogeneity in growth dynamics is increased when cells are recovering from exposure to sublethal stresses (i.e. PAA and acidic conditions) that may induce injury or dormancy.

Intercropping maize (Zea mays L.) and field beans (Vicia faba L.) for forage, increases protein production.

In 2005-2007, a field study was conducted into intercropping of maize with faba bean at Pawlowice research station, Wroclaw University of Environmental and Life Sciences. The main aim of the multi-year field research was an investigation into the reactions of differing maize hybrid earliness to intercropping cultivation with faba bean. The field research evaluated the effect of three maize hybrids-Wilga (early-E), Blask (medium-M) and Iman (late-L)-and the sowing rate of faba bean-18 (Fb1), 27 (Fb2) and 36 (Fb3) seeds per 1 m2-on growth dynamics and yield structure, and biomass, protein, and energy yield. Cultivation of faba bean in maize inter-rows led to significant competition with maize and affected yields, causing a decrease in maize dry matter yield from 14.1 (Fb1) to 20.6% (FB3) compared with maize sown alone. In terms of total biomass yield from maize and faba beans, no significant differences were found, but a slight increase in yield of 1.1-4.2% (repective to Fb1 and Fb3) was noted compared to maize sown alone. The early maize hybrid had a significantly lower yield but was most suitable for intercropping with faba bean. The dry biomass yield of early hybrids increased in intercropping by 25% compared to pure maize cultivation. Total protein yield from both intercropping components was higher than in the pure sowing of maize: from 24 (Fb1) to 39% (Fb3). The increase in protein production resulted in an improvement in the energy-protein ratio. The number of UFL per kg of total protein decreased from 13.2 in pure maize cultivation (M-P) to 9.3 (Fb3). A more balanced forage biomass was produced from intercropping maize with faba bean, especially when an early maize hybrid was sown with faba beans.

A dynamic network model predicts the phenotypes of multicellular clusters from cellular properties.

Cell division without cell separation produces multicellular clusters in budding yeast. Two fundamental characteristics of these clusters are their size (the number of cells per cluster) and cellular composition: the fractions of cells with different phenotypes. Using cells as nodes and links between mother and daughter cells as edges, we model cluster growth and breakage by varying three parameters: the cell division rate, the rate at which intercellular connections break, and the kissing number (the maximum number of connections to one cell). We find that the kissing number sets the maximum possible cluster size. Below this limit, the ratio of the cell division rate to the connection breaking rate determines the cluster size. If links have a constant probability of breaking per unit time, the probability that a link survives decreases exponentially with its age. Modeling this behavior recapitulates experimental data. We then use this framework to examine synthetic, differentiating clusters with two cell types, faster-growing germ cells and their somatic derivatives. The fraction of clusters that contain both cell types increases as either of two parameters increase: the kissing number and difference between the growth rate of germ and somatic cells. In a population of clusters, the variation in cellular composition is inversely correlated (r2 = 0.87) with the average fraction of somatic cells in clusters. Our results show how a small number of cellular features can control the phenotypes of multicellular clusters that were potentially the ancestors of more complex forms of multicellular development, organization, and reproduction.

Suppress Austenite Grain Coarsening by Nb Alloying in High-Temperature-Pseudo-Carburized Bearing Steel.

The effect of Nb alloying on the suppression of austenite grain coarsening behavior during pseudo-carburizing is investigated in high-temperature-carburized SAE4320 bearing steel. To explore the role of the Nb element in the pseudo-carburizing process, the morphology, composition, size, and distribution of NbC precipitates were analyzed. The results show that the fine austenite grain observed in Nb micro-alloyed steel is caused by the pinning effect of NbC precipitates, which hinders the coarsening of austenite grains and changes the growth dynamics of austenite grains. After the SAE4320 carburized bearing steel with the addition of 0.45 wt.% Nb element is kept at 1150 °C for 4 h, the PAG size is still below 20 µm, which indicates the Nb element has obvious advantages in limiting PAG growth at high temperatures and shows great potential for the development of high-temperature carburized bearing steel.

Development, feeding, and sex shape the relative quantity of the nutritional obligatory symbiont Wolbachia in bed bugs.

The common bed bug, Cimex lectularius, is a hemipteran insect that feeds only on blood, and whose bites cause public health issues. Due to globalization and resistance to insecticides, this pest has undergone a significant and global resurgence in recent decades. Blood is an unbalanced diet, lacking notably sufficient B vitamins. Like all strict hematophagous arthropods, bed bugs host a nutritional symbiont supplying B vitamins. In C. lectularius, this nutritional symbiont is the intracellular bacterium Wolbachia (wCle). It is located in specific symbiotic organs, the bacteriomes, as well as in ovaries. Experimental depletion of wCle has been shown to result in longer nymphal development and lower fecundity. These phenotypes were rescued by B vitamin supplementation. Understanding the interaction between wCle and the bed bug may help to develop new pest control methods targeting the disruption of this symbiotic interaction. The objective of this work was thus to quantify accurately the density of wCle over the life cycle of the host and to describe potential associated morphological changes in the bacteriome. We also sought to determine the impact of sex, feeding status, and aging on the bacterial population dynamics. We showed that the relative quantity of wCle continuously increases during bed bug development, while the relative size of the bacteriome remains stable. We also showed that adult females harbor more wCle than males and that wCle relative quantity decreases slightly in adults with age, except in weekly-fed males. These results are discussed in the context of bed bug ecology and will help to define critical points of the symbiotic interaction during the bed bug life cycle.

How urban growth dynamics impact the air quality? A case of eight Indian metropolitan cities.

Air pollution is a matter of great significance that confronts the sustainable progress of urban areas. Against India's swift urbanization, several urban areas exhibit the coexistence of escalating populace and expansion in developed regions alongside extensive spatial heterogeneity. The interaction mechanism between the growth of urban areas and the expansion of cities holds immense importance for the remediation of air pollution. Henceforth, the present investigation utilizes geographically weighted regression (GWR) to examine the influence of urban expansion and population growth on air quality. The examination will use a decade of data on the variation in PM2.5 levels from 2010 to 2020 in eight Indian metropolitan cities. The study's findings demonstrate a spatial heterogeneity between urban growth dynamics and air pollution levels. Urban growth and the expansion of cities demonstrate notable positive impacts on air quality, although the growth of infilling within expanding urban areas can significantly affect air quality. Given the unique trajectories of urban development in developing countries, this research provides many suggestions for urban administrators to foster sustainable urban growth.

The Stability of Hydrogen-Bonded Ion-Pair Complex Unexpectedly Increases with Increasing Solvent Polarity.

The generally observed decrease of the electrostatic energy in the complex with increasing solvent polarity has led to the assumption that the stability of the complexes with ion-pair hydrogen bonds decreases with increasing solvent polarity. Besides, the smaller solvent-accessible surface area (SASA) of the complex in comparison with the isolated subsystems results in a smaller solvation energy of the latter, leading to a destabilization of the complex in the solvent compared to the gas phase. In our study, which combines Nuclear Magnetic Resonance, Infrared Spectroscopy experiments, quantum chemical calculations, and molecular dynamics (MD) simulations, we question the general validity of this statement. We demonstrate that the binding free energy of the ion-pair hydrogen-bonded complex between 2-fluoropropionic acid and n-butylamine (CH3CHFCOO-…NH3But+) increases with increased solvent polarity. This phenomenon is rationalized by a substantial charge transfer between the subsystems that constitute the ion-pair hydrogen-bonded complex. This unexpected finding introduces a new perspective to our understanding of solvation dynamics, emphasizing the interplay between solvent polarity and molecular stability within hydrogen-bonded systems.

Quantitative anatomy of the extensor digiti minimi muscle in the growing human fetus.

Introduction Age-specific reference intervals for the extensor digiti minimi muscle (EDMM) in the human fetus may be relevant in the detailed evaluation of the musculoskeletal systems with potential relevant aspects for surgical treatment. The aim of the study was to examine the age-specific reference intervals and growth dynamics of the EDMM in relation to its length, width, projection surface area and volume. Material and methods The examined material included 70 human formalin-fixed fetuses of both sexes (37♀, 33♂) aged from 17 to 29 weeks. With the use of anatomical dissection every EDMM was visualized, recorded in a form of JPG formats and analyzed by the digital image analysis system and statistical methods. Results No variability of the EDMM was found. All the morphometric parameters of the EDMM revealed neither sex nor laterality differences. With fetal age most linear parameters of the EDMM concerning its examined lengths and widths increased in accordance with natural logarithmic functions. The only two exceptions to this referred to the belly width of EDMM measured at its mid-length and the tendon width of EDMM measured proximal to the extensor retinaculum of wrist, which both followed square root functions. The projection surface areas of the EDMM followed natural logarithmic functions, while the volumetric growth of the EDMM was proportionate to fetal age. Conclusions The variability of the EDMM in the human fetus is minimal. The morphometric data of the EDMM represents age-specific reference intervals of clinical significance. Morphometric parameters of the EDMM reveal neither sex nor laterality differences. The EDMM displays three different growth dynamics: from gradual growth deceleration according to both natural logarithmic functions (total length of the muscle and its tendons, belly length, tendon lengths, belly width at its origin, tendon width at its insertion, and projection surface areas) and square root functions (belly width at its mid-length and tendon width in the pre-retinacular segment) to a proportionate growth (total volume).

Monitoring tree canopy dynamics across heterogeneous urban habitats: A longitudinal study using multi-source remote sensing data.

Urban trees have attracted increasing attention to serve as a green prescription for addressing various challenges facing human society like climate change and environmental deterioration. However, without healthy growth of urban trees, they cannot service any environmental, social, and economic benefits in a sustainable manner. By monitoring the canopy development, the tree growth dynamics in different urban habitats can be detected and appropriate management approaches can be executed. Using the Kowloon Peninsula, Hong Kong, as a case, this study explores how remote sensing data can help monitor and understand the impacts of heterogeneous urban habitats on tree canopy dynamics. Four algorithms based on WorldView-2 satellite image are compared to optimize the canopy segmentation. Then the individual tree canopy is integrated with Sentinel-2 satellite data to obtain canopy growth dynamics for each season from 2016 to 2020. Three indicators are applied to reflect tree canopy status, including the fluorescence correction vegetation index (FCVI, tracking leaf chlorophyll density), the soil adjusted total vegetation index (SATVI, measuring the density of woody branches and twigs), and the normalised difference phenology index (NDPI, capturing canopy water content). And four heterogeneous habitats where urban trees stand are specified. The results revealed that urban trees show varying canopy growth status, in a descending order from natural terrains, parks, residential lands, to road verges, suggesting that urban habitats curtail trees' growth significantly. Additionally, two super-typhoons in 2017 and 2018, respectively, caused serious damages to tree canopy. Relevant resiliency of tree varies, echoing the sequence of canopy growth status with those in road verges the least resilient. This study shows how remote sensing data can be used to provide a better understanding of long-term tree canopy dynamics across large-scale heterogeneous urban habitats, which is key to monitoring and maintaining the health and growth of urban trees.

Rapid growth in a large Cambrian apex predator.

Despite the importance of ontogenetic data on early diverging euarthropods to our understanding of the ecology and evolution of past life, the data are distinctly lacking, as reconstructing life histories of fossil animals is often challenging. Here we report the growth trajectory of frontal appendages of the apex predator Amplectobelua symbrachiata, one of the most common radiodont arthropods from the early Cambrian Chengjiang biota (c. 520 Ma) of China. Analysis of 432 specimens (9.1-137.1 mm length; 1.3-25.6 mm height) reveals that appendages grew isometrically, with an estimated maximum size of the whole animal of c. 90 cm. Individuals grew rapidly compared to extant arthropods, as assessed using the electronic length-frequency analysis (ELEFAN) approach. Therefore, we show that the Cambrian apex predator A. symbrachiata was an extremely fast-growing arthropod, with an unusual life history strategy that formed as part of the escalatory 'arms race' that shaped the Cambrian explosion over 500 Ma.

Bridging responses to a human telomerase reverse transcriptase-based peptide cancer vaccine candidate in a mechanism-based model.

Therapeutic cancer vaccines are novel immuno-therapeutics, aiming to improve clinical outcomes with other immunotherapies. However, obstacles to their successful clinical development remain, which model-informed drug development approaches may address. UV1 is a telomerase based therapeutic cancer vaccine candidate being investigated in phase I clinical trials for multiple indications. We developed a mechanism-based model structure, using a nonlinear mixed-effects modeling techniques, based on longitudinal tumor sizes (sum of the longest diameters, SLD), UV1-specific immunological assessment (stimulation index, SI) and overall survival (OS) data obtained from a UV1 phase I trial including non-small cell lung cancer (NSCLC) patients and a phase I/IIa trial including malignant melanoma (MM) patients. The final structure comprised a mechanistic tumor growth dynamics (TGD) model, a model describing the probability of observing a UV1-specific immune response (SI ≥ 3) and a time-to-event model for OS. The mechanistic TGD model accounted for the interplay between the vaccine peptides, immune system and tumor. The model-predicted UV1-specific effector CD4+ T cells induced tumor shrinkage with half-lives of 103 and 154 days in NSCLC and MM patients, respectively. The probability of observing a UV1-specific immune response was mainly driven by the model-predicted UV1-specific effector and memory CD4+ T cells. A high baseline SLD and a high relative increase from nadir were identified as main predictors for a reduced OS in NSCLC and MM patients, respectively. Our model predictions highlighted that additional maintenance doses, i.e. UV1 administration for longer periods, may result in more sustained tumor size shrinkage.

Effect of temperature on the protective efficacy of a live attenuated vaccine against herpesviral haematopoietic necrosis in goldfish.

The live attenuated vaccine P7-P8 strain against herpesviral haematopoietic necrosis, which is caused by cyprinid herpesvirus 2 (CyHV-2), exhibits high protective efficacy in goldfish at 25°C, the predominant temperature for this disease; however, the effect of water temperature during the vaccination period on efficacy has not been determined. In this study, an in vitro experiment revealed that the vaccine strain grew between 15 and 30°C in the goldfish cell line RyuF-2. Subsequent in vivo efficacy tests were conducted with vaccination temperatures ranging from 15 to 30°C. During the vaccination period, organs were sampled to determine the vaccine growth dynamics. Blood plasma was collected to assess anti-CyHV-2 antibody titres. The protective efficacy of the vaccine at 15, 20, 25, and 30°C after subsequent virulent CyHV-2 challenge resulted in a relative percentage survival of 73.3%, 77.8%, 100%, and 77.8%, respectively, which indicated that the vaccine is effective over this temperature range. The vaccine virus load in the spleen was lowest at 15°C (103.7 DNA copies/mg) and highest at 25°C (106.5 DNA copies/mg). This indicates that the vaccine virus load over 104 DNA copies/mg may elicit sufficient acquired immunity. No significant differences in antibody titre were observed between groups, which suggests that cell-mediated immunity can be fundamentally involved in protection.

Comparative assessment of microalgal growth kinetic models based on light intensity and biomass concentration.

The comprehensive evaluation and validation of mathematical models for microalgal growth dynamics are essential for improving cultivation efficiency and optimising photobioreactor design. A considerable gap in comprehending the relation between microalgal growth, light intensity and biomass concentration arises since many studies focus solely on associating one of these factors. This paper compares microalgal growth kinetic models, specifically focusing on the combined impact of light intensity and biomass concentration. Considering a dataset (experimental results and literature values) concerning Chlorella vulgaris, nine kinetic models were assessed. Bannister and Grima models presented the best fitting performance to experimental data (RMSE ≤ 0.050 d-1; R2≥0.804; d2≥0.943). Cultivation conditions conducting photoinhibition were identified in some kinetic models. After testing these models on independent datasets, Bannister and Grima models presented superior predictive performance (RMSE = 0.022-0.023 d-1; R2 = 0.878-0.884; d2: 0.976-0.975). The models provide valuable tools for predicting microalgal growth and optimising operational parameters, reducing the need for time-consuming and costly experiments.