Slow Growth Rate Research Articles

Response of Propsilocerus akamusi (Diptera: Chironomidae) to the leachates from AMD-contaminated sediments: Implications for metal bioremediation of AMD-polluted areas

Acid mine water (AMD) is a global environmental problem caused by coal mining with the characteristics of low pH and high concentrations of metals and sulfates. It is a pertinent topic to seek both economical and environmentally friendly approaches to minimize the harmful effects of AMD on the environment. Insect larvae are considered a promising solution for pollution treatment. Chironomidae is the most tolerant family to contaminants in pools and its larvae have a strong capacity for metal accumulation from sediment. This paper aimed to evaluate the larvae of Propsilocerus akamusi, a dominant species in the chironomid community, as a new species for entomoremediation in AMD-polluted areas. We detected the toxic effects of AMD on P. akamusi larvae based on their survival and the trace metals bioaccumulation capabilities of P. akamusi larvae. Moreover, we analyzed the expression patterns of four stress-response genes, HSP70, Eno1, HbV, and Hb VII in P. akamusi larvae. Our results revealed that AMD exposure did not significantly affect the survival of the P. akamusi larvae and individuals exposed to some AMD gradients even exhibited higher survival. We also observed the significantly accumulated concentrations of Fe, Ni, and Zn as well as higher bioaccumulation factors (BAFs) for Ni and Zn in the P. akamusi larvae exposure to AMD. Induced expression of Eno1 and Hb VII may play important roles in the AMD tolerance of P. akamusi larvae. This study indicated the potential application of P. akamusi larvae in the metal bioremediation of AMD-polluted areas. Statement of environmental implicationAcid mine drainage (AMD) is a global environmental problem related to coal mining activities. AMD pollution has become a long-term, worldwide issue for its interactive and complex stress factors. Bioremediation is an effective method to remove the metals of AMD from wastewater to prevent downstream pollution. However, the disadvantages of the slow growth rate, susceptibility to seasonal changes, difficult post-harvest management, and small biomass of hyperaccumulating plants greatly limit the usefulness of phytoremediation. Insect larvae may be useful candidate organisms to overcome these shortcomings and have been considered a promising pollution solution. Propsilocerus akamusi is a dominant species in the chironomid community and is distributed widely in many lakes of eastern Asia. This species has extraordinary abilities to resist various stresses. This research is the first time to our knowledge to evaluate the application of P. akamusi as a new species in entomoremediation in AMD-contaminated areas.

Seasonal SIMS δ18O record in Astarte borealis from the Baltic Sea tracks a modern regime shift in the NAO

IntroductionAstarte borealis holds great potential as an archive of seasonal paleoclimate, especially due to its long lifespan (several decades to more than a century) and ubiquitous distribution across high northern latitudes. Furthermore, recent work demonstrates that the isotope geochemistry of the aragonite shell is a faithful proxy of environmental conditions. However, the exceedingly slow growth rates of A. borealis in some locations (<0.2mm/year) make it difficult to achieve seasonal resolution using standard micromilling techniques for conventional stable isotope analysis. Moreover, oxygen isotope (δ18O) records from species inhabiting brackish environments are notoriously difficult to use as paleoclimate archives because of the simultaneous variation in temperature and δ18Owater values.MethodsHere we use secondary ion mass spectrometry (SIMS) to microsample an A. borealis specimen from the southern Baltic Sea, yielding 451 SIMS δ18Oshell values at sub-monthly resolution.ResultsSIMS δ18Oshell values exhibit a quasi-sinusoidal pattern with 24 local maxima and minima coinciding with 24 annual growth increments between March 1977 and the month before specimen collection in May 2001.DiscussionAge-modeled SIMS δ18Oshell values correlate significantly with both in situ temperature measured from shipborne CTD casts (r2 = 0.52, p<0.001) and sea surface temperature from the ORAS5-SST global reanalysis product for the Baltic Sea region (r2 = 0.42, p<0.001). We observe the strongest correlation between SIMS δ18Oshell values and salinity when both datasets are run through a 36-month LOWESS function (r2 = 0.71, p < 0.001). Similarly, we find that LOWESS-smoothed SIMS δ18Oshell values exhibit a moderate correlation with the LOWESS-smoothed North Atlantic Oscillation (NAO) Index (r2 = 0.46, p<0.001). Change point analysis supports that SIMS δ18Oshell values capture a well-documented regime shift in the NAO circa 1989. We hypothesize that the correlation between the SIMS δ18Oshell time series and the NAO is enhanced by the latter’s influence on the regional covariance of water temperature and δ18Owater values on interannual and longer timescales in the Baltic Sea. These results showcase the potential for SIMS δ18Oshell values in A. borealis shells to provide robust paleoclimate information regarding hydroclimate variability from seasonal to decadal timescales.

Evaluation of the Genetic Diversity and Population Structure of Four Native Pig Populations in Gansu Province.

Indigenous pig populations, including Bamei pigs (BM), Hezuo pigs (HZ), Huixian Qingni Black pigs (HX), and Minxian Black pigs (MX) in Gansu Province, live in a particular climate and a relatively closed geographical environment. These local pig breeds are characterized by excellent characteristics (e.g., cold tolerance, robust disease resistance, and superior meat quality). In the past few years, pig populations in Gansu Province have decreased significantly because of their poor lean meat percentage, high fat content, and slow growth rate. Maintaining the diversity of these four breeds can act as a source of new alleles to be incorporated into commercial breeds which are more susceptible to disease and less adaptable to changing conditions because of inbreeding. Genomic data analysis is adequate for determining the genetic diversity and livestock breeding population structure, even in local pig populations. However, the genetic diversity and population structure of the four native pig populations in Gansu Province are still unknown. Thus, we used "Zhongxin-I" porcine chip for the SNP detection of 102 individuals living on four pig conservation farms. A total of 57,466 SNPs were identified among the four pig breeds. The linkage disequilibrium (LD) plot showed that MX had the highest level of LD, followed by BM, HZ, and HX. The observed heterozygosity (Ho) in all four populations was higher than the expected heterozygosity (He). A principal component analysis (PCA) demonstrated that the four local pig populations were isolated. The identity displayed by the state matrix and G matrix heat map results indicated that small numbers of individuals among the four pig breeds had a high genetic distance and weak genetic relationships. The results of the population genetic structure of BM, HZ, HX, and MX pigs showed a slight genetic diversity loss. Our findings enabled us to better understand the genome characteristics of these four indigenous pig populations, which will provide novel insights for the future germplasm conservation and utilization of these indigenous pig populations.

A simplified chemical model for RBCC engines operating in ejector mode

The ejector mode in rocket-based combined-cycle (RBCC) engines involves complex mixing and combustion processes between the primary and secondary streams and second fuel, which poses a challenge to numerical simulation. This paper introduces an efficient model to predict RBCC engine performance in ejector mode. Given the slow growth rate of compressible mixing layers with strong compressibility effects and high chemical reactivity of immediate species within the primary stream, the combustion intensity is primarily governed by the mixing process. The model converts residual chemical energy within the primary stream into suitable mass flow rates of H2 and CO and simplifies the intricate chemical kinetics into single-step models. The model was tested on hydrogen- and kerosene-fueled RBCC engine experiments involving diffusion and afterburning (DAB) and simultaneous mixing and combustion cycles. Simulation results align well with experimental data regarding wall pressure distributions, entrainment ratio, and axial thrust. The model suggests intense combustion occurs in both the mixer and afterburner, even in the DAB cycle, which notably reduces the entrainment ratio. Additionally, early combustion within the mixing process incurs extra Rayleigh loss and impairs pressurization performance. The secondary fuel exhibits a jet-wake stabilized combustion mode under a high-temperature and low Mach number environment. In conclusion, the proposed model provides an efficient way of predicting RBCC engine performance in the ejector mode.

Abstract B096: A comparative assessment of selinexor with trabectedin or lurbinectedin in patient-derived xenografts (PDX) of dedifferentiated liposarcoma (DDLPS) highlights the effectiveness of their sequential or concomitant combination

Abstract Introduction: Trabectedin or selinexor as single agent showed limited effectiveness in patients with metastatic DDLPS in clinical trials. We conducted a preclinical study on two patient-derived xenografts (PDXs) of DDLPS to test the activity of combined and sequential treatment with selinexor and trabectedin or lurbinectedin, following evidence of clinical benefit from a rechallenge to trabectedin after selinexor in two patients with metastatic DDLPS. Methods: Two PDXs (LPS-BZ; LPS-NV) from two patients with primary localized DDLPS treated with surgery were established in SCID mice. These models represented the DD component of DDLPS and were histomorphologically and molecularly (by FISH and RNAseq) characterized for consistency with the originating clinical tumors. Antitumor activity of single-agent selinexor and either trabectedin or lurbinectedin as well as of the selinexor-trabectedin sequence and both selinexor-lurbinectedin sequence and combination was assessed. Drug activity was evaluated as maximum tumor volume inhibition percentage (max TVI%). Results: The anti-cancer activity of a re-challenge to trabectedin following treatment with selinexor, which was observed in two patients, let to the design of in-vivo experiments on PDXs of DDLPS to investigate the activity of a sequential treatment with selinexor plus trabectedin/luribinectedin or their combination. The histomorphological and molecular characteristics of PDXs of DDLPS (LPS-BZ and LPS-NV) were confirmed to reproduce the clinical tumor. In the PDX model (LPS-BZ) with the faster growth rate (doubling time: 5 days), the sequence of selinexor followed by trabectedin was more effective (max TVI 61%) than each single-agent (maxTVI 46% and 33% for selinexor and trabectedin, respectively). A further experiment was conducted in a PDX model (LPS-NV) characterized by a slower growth rate (doubling time: 12 days) and results consistently showed a greater activity for the selinexor and trabectedin sequence (mTVI 73%) compared to selinexor (mTVI 53%) or trabectedin (mTVI 35%) alone. Finally, we tested lurbinectedin instead of trabectedin in the LPS-NV PDX model. The sequence selinexor and lurbinectedin (mTVI 81%) or their combination (mTVI 74%) showed a greater anti-tumor effect compared to single agent selinexor (mTVI 65%) or lurbinectedin (mTVI 24%). RNA-seq analysis of control and treated tumors is ongoing to investigate the determinants of the positive interactions between trabectedin/lurbinectedin and selinexor as a function of treatment schedule. Conclusion: The combination of selinexor with either trabectedin or lurbinectedin in DDLPS showed anti-tumor activity. Further analyses are ongoing to investigate the mechanisms underpinning the interaction of these drugs. Citation Format: Sandro Pasquali, Noemi Arrighetti, Valentina Zuco, Cesare Soffientini, Monica Tortoreto, Silvia Brich, Marta Barisella, Paola Collini, Chiara Fabbroni, Sara Cingarlini, Alessandro Gronchi, Silvia Stacchiotti, Roberta Sanfilippo, Nadia Zaffaroni. A comparative assessment of selinexor with trabectedin or lurbinectedin in patient-derived xenografts (PDX) of dedifferentiated liposarcoma (DDLPS) highlights the effectiveness of their sequential or concomitant combination [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B096.

Staphylococcus aureus Dormancy: Waiting for Insurgency.

Relapse infection usually results from resistance to the antibiotic, acquired genes, or persister cells. Persister cells are formed through mutation, reduced activity or metabolically inactive pathways induced by antibiotics, harassing conditions, low ATP, and malnutrition. These factors provide the ground for bacteria to grow slowly. Such a slow growth rate makes traditional antibiotics ineffective against persister cells. Staphylococcus aureus (S. aureus), in addition to this form, can be observed in Small Colony Variants (SCVs), L-forms, and dormant, all of which are characterized by at least one feature, i.e., slow growth. Despite their slow growth, they are metabolically active in terms of stringent SOS and cell wall stress responses. The stress response involves resistance against harassing conditions, and it survives until it is reactivated later. The present study aims to discuss the mechanisms of all persister cell formations, circumstances involved, gene mutation, and adoptable strategies against it.

The establishment of evaluation systems and an index for energy superpower

Building an energy superpower is a major development strategy for China at present and long-term goal for other countries. This study aims to propose an ideal evaluation system, and construct a quantifiable index for energy superpower. 7 weight allocation schemes and 16 weight sets were employed to test the impacts of different weights on energy superpower index (ESPI), ensuring authenticity, rationality, and accuracy, and finally the subjective entropy weight method was adopted to determine the weights. The ESPI of 11 economies, including China, the United States, Canada, Russia, Australia, Germany, Japan, the United Kingdom, South Korea, Argentina, and the European Union, was computed for a period of 21 years (2000−2020). China's index demonstrated a remarkable increase from the second-to-last place in 2000 to second place in 2020, surpassing the other 10 countries. The United States and Argentina's energy superpower indices consistently ranked first and last respectively from 2000 to 2020, while the early European Union's index ranked second, but was later surpassed by China, falling to third. The energy superpower indices of Canada, Russia, Australia, Germany, the United Kingdom, Japan, and South Korea share similar values with slow growth rates, roughly ranking in between the European Union and Argentina.

Effects of acclimation temperature on growth, physiology and thermal tolerance of the juvenile grass carp Ctenopharyngodon idella

Aquatic ichthyofauna are facing unfavourable temperature fluctuations due to the anthropogenic activities and global climate change. Effects of temperature in aquatic environments need to be explored for revealing its potential effects on the aquatic organisms. In present study, the effects of different acclimation temperatures on the oxidative stress, metabolism, thermal tolerance and growth of the grass carp Ctenopharyngodon idella were studied. Grass carp fingerlings (10.40 ± 0.37 g) were reared for 60 days under different acclimation temperatures, i.e., 22 °C, 26 °C, 30 °C, 34 °C and 38 °C respectively. Significantly higher growth rate (weight gain and specific growth rate) and improved FCR of fish reared at 30 °C were observed, while under higher or lower acclimation temperatures, fish showed slow growth rate and high FCR. Growth rate in term of % weight gain and specific growth rate showed positive correlation with pyruvate kinase activity. Moreover, antioxidant parameters catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), lipid peroxidation (LPO), glutathione contents (GSH), glutathione peroxidase (GSH-Px), glutathione reductase (GR) in different tissues (liver, brain, gills, muscles and intestine) of fish showed decreasing trend from 22 °C towards 30 °C acclimation temperatures. However, beyond 30 °C, i.e., from 34 °C to 38 °C fish showed oxidative stress response, indicated by increasing trend in antioxidant parameter levels. Moreover, thermal tolerance data revealed that fingerlings of C. idella reared at highest acclimation temperature (38 °C) showed highest CTMax and CTMin values, while those reared at lowest acclimation temperature (22 °C) showed lowest CTMax and CTMin values. Our present study provides new insights regarding the thermal tolerance of fish and can be practically implemented in aquaculture sector.

Multiple Myeloma Disease Model to Predict PFS Outcomes across Lines of Therapy, an Analysis Based on Commpass Observational Study

Introduction Multiple Myeloma (MM) remains incurable despite advances in treatment. Model-based approaches based on tumor dynamics have successfully been used to optimize drug-development in oncology. Model-derived tumor dynamics also called tumor growth inhibition (TGI) metrics capture the treatment effect as tumor biomarkers and are predictive of the overall survival (OS) benefit, based on TGI-OS models, this mathematical framework has been shown to be drug-independent in most cases. M-protein is measured longitudinally during clinical trials, it reflects tumor burden and is one of the criteria used to assess clinical response according to the International Myeloma Working Group Uniform Response Criteria. A drug-independent link between M-protein dynamic metrics and OS was previously established and confirmed for refractory MM patients. The primary endpoint in MM clinical trials is usually progression free survival (PFS). New immunotherapies are currently in development and there is a need for early and robust drug development decision making. Therefore there is strong interest to expand this modeling framework to leverage M-protein dynamics to predict PFS outcomes. Methods CoMMpass (https://www.themmrf.org/finding-a-cure/personalized-treatment-approaches/) is a prospective, longitudinal, observational study in newly diagnosed symptomatic patients with multiple myeloma. It represents a unique source of clinical data to investigate the link between M-protein dynamic and survival outcomes across lines of therapy and treatments. Individual M-protein and PFS Data from 804 patients within the CoMMpass study were used. Given patients are enrolled at their initial treatment regimen and observed over 8 years, they can receive several lines of therapy. Due to the characteristics of the modeling framework, allowing to analyze only one line of therapy for each patient, the latest line of therapy for each subject was selected for which they had at least 2 M-protein assessments available. M-protein dynamic metrics (M-protein ratio to baseline at different time points, time to growth, growth rate, shrinkage rate) derived using an empirical bi-exponential model, 42 prognostic factors and potential treatment effects were first tested in a univariate analysis using a Cox proportional hazards regression model. Statistically significant covariates in the univariate analysis (p<0.05) were included in a full multivariate parametric distribution survival model. A backward deletion stepwise procedure was performed (p<0.01) to retain covariates in the final PFS model. Model qualification was performed using posterior predictive checks based on Kaplan Meier plots. Results Among 804 patients, 490 patients received only 1 line of therapy (LoT), 157 received 2 LoTs, 93 received 3 LoTs, 31 received 4 LoTs,18 received 5 LoTs, 10 received 6 LoTs, finally 7 patients got up to 7 to 11 LoTs. PFS distribution followed a log-normal distribution. Table 1 shows the parameter estimates of the PFS model. Among all tested M-protein dynamic metrics and prognostic factors, the logarithmic value of the growth rate (log(KG)), in red in Table 1, was found to be the best predictor of PFS. Patients with slower growth rate, who received a transplantation, with higher albumin and lower lactate dehydrogenase values had longer PFS. Those findings are consistent with previous modeling works conducted in MM. Also, the PFS model was confirmed to be drug-independent. As shown in Figure 1, prediction intervals derived from model-based simulations well captured observed PFS data for each line of treatment although the line of therapy is not included as a predictor in the PFS model. Similar results were obtained across treatments. In a next step, external validations assessing the model performance to reproduce Phase 3 clinical trial outcomes will be performed. Conclusions A model linking M-protein dynamic to PFS in MM was developed across a wide range of lines of therapy and treatments. The model can support drug development in MM: enabling early predictions of clinical trial outcomes and inform study design e.g. by simulating the probability of success of upcoming pivotal clinical trials.

Research on Maize Acreage Extraction and Growth Monitoring Based on a Machine Learning Algorithm and Multi-Source Remote Sensing Data

Getting accurate and up-to-date information on the cultivated land area and spatial arrangement of maize, an important staple crop in the Ningxia Hui Autonomous Region, is very important for planning agricultural development in the region and judging crop yields. This work proposes a machine-learning methodology to extract corn from medium-resolution photos obtained from the Sentinel-2 satellite. The Google Earth Engine (GEE) cloud platform is utilized to facilitate the process. The identification of maize cultivation regions in Huinong District in the year 2021 was performed through the utilization of support vector machine (SVM) and random forest (RF) classification techniques. After obtaining the results, they were compared to see if using the random forest classification method to find planting areas for maize was possible and useful. Subsequently, the regions where maize was cultivated were combined with image data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which has a high temporal resolution. The Normalized Difference Vegetation Index (NDVI) contemporaneous difference method, which gives regular updates, was then used to track the growth of maize during its whole growth phase. The study’s results show that using the GEE cloud platform made it easier to quickly map out data about where to plant maize in Huinong District. Furthermore, the implementation of the random forest method resulted in enhanced accuracy in extracting maize planting areas. The confusion matrix’s evaluation of the classification performance produced an average overall accuracy of 98.9% and an average Kappa coefficient of 0.966. In comparison to the statistics yearbook of the Ningxia Hui Autonomous Region, the method employed in this study consistently yielded maize-planted area estimates in Huinong District with relative errors below 4% throughout the period spanning 2017 to 2021. The average relative error was found to be 2.04%. By combining MODIS image data with the NDVI difference model in the year 2021, the high-frequency monitoring of maize growth in Huinong District was successful. The growth of maize in Huinong District in 2021 exhibited comparable or improved performance in the seedling stage, nodulation stage, and the early stage of staminate pulling and spitting, possibly attributed to the impact of climate and other relevant elements. After that, the growth slowed down in August, and the percentage of regions with slower growth rates than in previous years gradually increased. However, overall, the growth of maize in Huinong District during the year 2021 showed improvement relative to the preceding years. The present study introduces a novel approach that demonstrates the capability to accurately extract corn crops in the Huinong District while simultaneously monitoring their growth at a high frequency.

Long-term and large-scale ecological restoration projects shaped the spatial heterogeneity in new forests

The implementation of long-term ecological restoration projects and policies over the past two decades has played a crucial role in advancing the achievement of Sustainable Development Goal 15. However, the resulting dynamics of new forests remain unclear. In this study, we initially examined the distribution and sources of new forests and subsequently investigated the gross primary productivity (GPP) variations within these forested regions. We discovered that new forests are mainly converted from previously cultivated land, which is primarily due to the Grain for Green Project. The new forests are mainly distributed in mid-low altitude areas and gentle slope regions, indicating that accessible areas are prone to damage but also easy to recover. Over approximately two decades of ecological restoration projects, the GPP of new forests has significantly increased trends and the growth rates of new forests vary significantly in different climatic zones. Moreover, the GPP and growth rates of new forests displayed spatial heterogeneity. Specifically, the GPP in the new forests was highest in the eastern region, followed by the central south region, while the northwest region had the lowest GPP. Meanwhile, the southwest region shows the highest GPP growth rate among new forests, while the northwest region has the slowest growth rate. Furthermore, the average GPP of new forests is lower than stable forests, but new forests in China grow faster (3.735 vs. 2.587), highlighting their substantial carbon potential. These findings indicate that it's crucial to account for variations in stand and forest change rates when modeling forest carbon sequestration potential.

Phytoplankton communities of the west coast of Florida – multiyear and seasonal responses to nutrient enrichment

Blooms of the harmful algae species Karenia brevis are frequent off the southwest coast of Florida despite having relatively slow growth rates. The regional frequency of these harmful algal blooms led to the examination of the dominant estuarine outflows for effects on both K. brevis and the phytoplankton community in general. There is comparatively little information on the growth rates of non-Karenia taxonomic groups other than diatoms. A seasonally based series (Fall, Winter, and Spring) of bioassay experiments were conducted to determine the nutrient response of the coastal phytoplankton community. Treatments included estuarine waters (Tampa Bay, Charlotte Harbor, and the Caloosahatchee River) applied in a 1:25 dilution added to coastal water to mimic the influence of estuarine water in a coastal environment. Other treatments were 5–15 μM additions of nitrogen (N), phosphorus (P), and silica (Si) species, amino acids, and N (urea) + P added to coastal water. Incubations were conducted under ambient conditions with shading for 48 h. Analyses of dissolved and particulate nutrients were coupled with HPLC analysis of characteristic photopigments and taxonomic assignments of biomass via CHEMTAX. The coastal phytoplankton community, dominated by diatoms, cyanophytes and prasinophytes, was significantly different both by bioassay and by season, indicating little seasonal fidelity in composition. Specific growth rates of chlorophyll a indicated no significant difference between any controls, any estuarine treatment, P, or Si treatments. Conditions were uniformly N-limited with the highest growth rates in diatom biomass. Despite differing initial communities, however, there were seasonally reproducible changes in community due to the persistent growth or decline of the various taxa, including haptophytes, cyanophytes, and cryptophytes. For the one bioassay in which K. brevis was present, the slow growth of K. brevis relative to diatoms in a mixed community was evident, indicating that identifying the seasonally based behavior of other taxa in response to nutrients is critical for the simulation of phytoplankton competition and the successful prediction of the region's harmful algal blooms.

ANALYSIS OF EFFECT OF SOCIO-ECONOMIC CHARACTERISTICS ON THE PERCEPTION OF FARMERS ON GIANT LAND SNAIL (Achatina achatina) PRODUCTION IN NORTH CENTRAL STATES, NIGERIA.

The study analysed Sixty-four snail farmers were sampled through multiple-stage sampling technique. Descriptive and inferential statistics were used to achieve the specific objectives of the study. The study found that snail farming was carried out by young active farmers whose average age was 44 years, with an average of 7 years experience in snail farming, small-scale in nature because their average stock size was 787 snails. The average household size and annual farm income was 6 persons and N350,000.50 respectively. The farmers’ perception was high (83%) for snail farming and this was linked to the several benefits like increased income, enhancement of family welfare, a source of animal protein, source of employment, means of turning kitchen waste and ways of engaging family labour, derived from snail production. Snail production was asserted to be low (55%) due to constraints like slow rate of growth, theft, pest and disease (just to mention but a few), the farming of snail was noted to be economically viable. Socio-economic characteristics such as farmers gender, age, education, marital status, household size and farm income were identified to be significant variables to level of snail production. By recommendation, there is need for research to focus on breeding snails that are early maturing and fast growing to help overcome the problem of slow growth and used by the farmers for production purpose.

Differentiating the roles of proteins and polysomes in nucleoid size homeostasis in Escherichia coli

A defining feature of the bacterial cytosolic interior is a distinct membrane-less organelle, the nucleoid, that contains the chromosomal DNA. Although increasing experimental evidence indicates that macromolecular crowding is the dominant mechanism for nucleoid formation, it has remained unclear which crowders control nucleoid volume. It is commonly assumed that polyribosomes play a dominant role, yet the volume fraction of soluble proteins in the cytosol is comparable with that of polyribosomes. Here, we develop a free energy-based model for the cytosolic interior of a bacterial cell to distinguish contributions arising from polyribosomes and cytosolic proteins in nucleoid volume control. The parameters of the model are determined from the existing experimental data. We show that, while the polysomes establish the existence of the nucleoid as a distinct phase, the proteins control the nucleoid volume in physiologically relevant conditions. Our model explains experimental findings in Escherichia coli that the nucleoid compaction curves in osmotic shock measurements do not depend on cell growth rate and that dissociation of polysomes in slow growth rates does not lead to significant nucleoid expansion, while the nucleoid phase disappears in fastest growth rates. Furthermore, the model predicts a cross-over in the exclusion of crowders by their linear dimensions from the nucleoid phase: below the cross-over of 30–50 nm, the concentration of crowders in the nucleoid phase decreases linearly as a function of the crowder diameter, while decreasing exponentially above the cross-over size. Our work points to the possibility that bacterial cells maintain nucleoid size and protein concentration homeostasis via feedback in which protein concentration controls nucleoid dimensions and the nucleoid dimensions control protein synthesis rate.

In vitro induction of tetraploidy and its effects on phenotypic variations in Populus hopeiensis

BackgroundArtificial induction of polyploidy is the most common and effective way to improve the biological properties of Populus and develop new varieties of this tree. In this study, in order to confirm and expand earlier findings, we established a protocol using colchicine and based on an efficient shoot regeneration system of leaf blades to induce tetraploidy in vitro in three genotypes from diploid Populus hopeiensis. The stomatal characteristics, leaf blade size, and growth were evaluated for diploids and tetraploids of three genotypes.ResultsWe found that genotype, preculture duration, colchicine concentration, and colchicine exposure time had highly significant effects on the tetraploid induction rate. The optimal protocol for inducing tetraploidy in P. hopeiensis was to preculture leaf blades for 7 days and then treat them for 4 days with 40 mg/L colchicine. The tetraploid induction rates of genotypes BT1, BT3, and BT8 were 21.2, 11.4 and 16.7%, respectively. A total of 136 tetraploids were identified by flow cytometry analysis and somatic chromosome counting. The stomatal length, width, and density of leaf blades significantly differed between diploid and tetraploid plants. Compared with their diploid counterparts, the tetraploids produced larger leaf blades and had a slower growth rate. Our findings further document the modified morphological characteristics of P. hopeiensis following whole-genome duplication (e.g., induced tetraploidy).ConclusionsWe established a protocol for in vitro induction of tetraploidy from diploid leaf blades treated with colchicine, which can be applied to different genotypes of P. hopeiensis.

The ontogenetic dimension of plant functional ecology

Abstract Plant functional strategies change considerably as plants develop, driven by intraindividual variability in anatomical, morphological, physiological and architectural traits. Developmental trait variation arises through the complex interplay among genetically regulated phase change (i.e. ontogeny), increases in plant age and size, and phenotypic plasticity to changing environmental conditions. Although spatial drivers of intraspecific trait variation have received extensive research attention, developmentally driven intraspecific trait variation is largely overlooked, despite widespread occurrence. Ontogenetic trait variation is genetically regulated, leads to dramatic changes in plant phenotypes and evolves in response to predictable changes in environmental conditions as plants develop. Evidence has accumulated to support a general shift from fast to slow relative growth rates and from shade to sun leaves as plants develop from the highly competitive but shady juvenile niche to the stressful adult niche in the systems studied to date. Nonetheless, there are major gaps in our knowledge due to examination of only a few environmental factors selecting for the evolution of ontogenetic trajectories, variability in how ontogeny is assigned, biogeographic sampling biases on trees in temperate biomes, dependencies on a few broadly sampled leaf morphological traits and a lack of longitudinal studies that track ontogeny within individuals. Filling these gaps will enhance our understanding of plant functional ecology and provide a framework for predicting the effects of global change threats that target specific ontogenetic stages. Read the free Plain Language Summary for this article on the Journal blog.

Unveiling a Biomarker Signature of Meningioma: The Need for a Panel of Genomic, Epigenetic, Proteomic, and RNA Biomarkers to Advance Diagnosis and Prognosis.

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas' tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningiomas, with a focus on neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics-, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in pre-operative and post-operative decision making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

Live slow, die old: larval propagation of slow-growing, stress-tolerant corals for reef restoration

Efforts to restore coral reefs usually involve transplanting asexually propagated fast-growing corals. However, this approach can lead to outplanted populations with low genotypic diversity, composed of taxa susceptible to stressors such as marine heatwaves. Sexual coral propagation leads to greater genotypic diversity, and using slow-growing, stress-tolerant taxa may provide a longer-term return on restoration efforts due to higher outplant survival. However, there have been no reports to date detailing the full cycle of rearing stress-tolerant, slow-growing corals from eggs until sexual maturity. Here, we sexually propagated and transplanted two massive slow-growing coral species to examine long-term success as part of reef restoration efforts. Coral spat were settled on artificial substrates and reared in nurseries for approximately two years, before being outplanted and monitored for survivorship and growth for a further four years. More than half of initially settled substrates supported a living coral following nursery rearing, and survivorship was also high following outplantation with yields declining by just 10 to 14% over four years. At 6-years post-fertilisation over 90% of outplanted corals were reproductively mature, demonstrating the feasibility of restoring populations of sexually mature massive corals in under a decade. Although use of slower growing, stress tolerant corals for reef restoration may provide a longer-term return on investment due to high post-transplantation survival rates, considerable time is required to achieve even modest gains in coral cover due to their relatively slow rates of growth. This highlights the need to use a mix of species with a range of life-history traits in reef restoration and to improve survivorship of susceptible fast-growing taxa that can generate rapid increases in coral cover.

Influence of poly(methyl methacrylate) on the structure and phase transition behavior of poly(vinylidene fluoride)

The structure and organization of poly(vinylidene fluoride) (PVDF) spherulites in blends with poly(methyl methacrylate) of high (PMMA-H) and low (PMMA-L) molecular weights, respectively, have been studied in details. It is confirmed that the addition of PMMA-H and PMMA-L have different influence on the morphologies of PVDF spherulites in several aspects, such as the spacing of ring-band α-PVDF spherulites, the kinetics of both α-PVDF crystallization and α−γ′ solid phase transition, as well as the formation of Wagon-Wheel spherulites. First, incorporation of PMMA-L enlarges the band spacing, which is associated to the increased chain mobility of crystallizable PVDF that helps to release the surface stresses of lamellae. In contrast, the low mobility of PMMA-H chains enhances the congestion at fold surfaces, which results in a vigorous twisting and thus the formation of tightened ring-band α-PVDF structure. Second, the PMMA-H reduces the crystallization rate of PVDF more severely than the PMMA-L, resulting in an extremely slow growth rate of α-PVDF spherulites in PVDF/PMMA-H sample at 160 °C, only about one-twenty-third compared to the neat PVDF. Third, the remarkably reduced α-PVDF spherulite growth rate and enhanced α−γ′ transition rate at 160 °C lead to the formation of Wagon-Wheel PVDF spherulites with inner γ′-PVDF crystals and outer γ crystals. It originates from the synchronization of slow α-PVDF growth and accelerated α−γ′ transition rate through homoepitaxy. That is, when the α−γ′ transition with exceeded rate reaches the growth front of the original α-PVDF spherulite, the transformed γ′-PVDF crystals trigger the growth of γ-PVDF crystals directly from melt with non-band feature. These results help to unravel the formation mechanism of Wagon-Wheel PVDF spherulites to be the competition of α-γ′ crystal transformation and α-spherulite radial growth rates.

Gas–Water Two-Phase Displacement Mechanism in Coal Fractal Structures Based on a Low-Field Nuclear Magnetic Resonance Experiment

In this paper, the gas–water two-phase seepage process under a real mechanical environment is restored by a nuclear magnetic resonance experiment, and the gas–water two-phase distribution state and displacement efficiency in coal with different porosity under different gas injection pressures are accurately characterized. The fractal dimension of liquid phase distribution under different gas injection pressures was obtained through experiments, and the gas–water two-phase migration law is inverted according to it. Finally, the gas–water two-phase migration mechanism inside the fractal structure of coal was obtained. The results are as follows: 1. Gas will first pass through the dominant pathway (the composition of the dominant pathway is affected by porosity) and it will continue to penetrate other pathways only when the gas injection pressure is high. When the gas injection pressure is low, the displacement occurs mainly in the percolation pores. With the increase in gas injection pressure, the focus of displacement gradually shifts to the adsorption pore. 2. As the gas injection pressure increases, the displacement efficiency growth rate is relatively uniform for the high-porosity coal samples, while the low-porosity coal samples show a trend of first fast and then slow growth rates. When the gas injection pressure reaches 7 MPa, the displacement efficiency of high-porosity coal samples exceeds that of low-porosity coal samples. 3. With the increase in gas injection pressure, the fractal dimension of the adsorption pore section and the seepage pore section shows an increasing trend, but the fractal dimension of the adsorption pore section changes faster, indicating that with the increase in gas injection pressure, gas–water two-phase displacement mainly occurs in the adsorption pore section.