Examining geographical inequalities for malaria outcomes and spending on malaria in 40 malaria-endemic countries, 2010-2020.

BACKGROUND: While substantial gains have been made in the fight against malaria over the past 20 years, malaria morbidity and mortality are marked by inequality. The equitable elimination of malaria within countries will be determined in part by greater spending on malaria interventions, and how those investments are allocated. This study aims to identify potential drivers of malaria outcome inequality and to demonstrate how spending through different mechanisms might lead to greater health equity. METHODS: Using the Gini index, subnational estimates of malaria incidence and mortality rates from 2010 to 2020 were used to quantify the degree of inequality in malaria burden within countries with incidence rates above 5000 cases per 100,000 people in 2020. Estimates of Gini indices represent within-country distributions of disease burden, with high values corresponding to inequitable distributions of malaria burden within a country. Time series analyses were used to quantify associations of malaria inequality with malaria spending, controlling for country socioeconomic and population characteristics. RESULTS: Between 2010 and 2020, varying levels of inequality in malaria burden within malaria-endemic countries was found. In 2020, values of the Gini index ranged from 0.06 to 0.73 for incidence, 0.07 to 0.73 for mortality, and 0.00 to 0.36 for case fatality. Greater total malaria spending, spending on health systems strengthening for malaria, healthcare access and quality, and national malaria incidence were associated with reductions in malaria outcomes inequality within countries. In addition, government expenditure on malaria, aggregated government and donor spending on treatment, and maternal educational attainment were also associated with changes in malaria outcome inequality among countries with the greatest malaria burden. CONCLUSIONS: The findings from this study suggest that prioritizing health systems strengthening in malaria spending and malaria spending in general especially from governments will help to reduce inequality of the malaria burden within countries. Given heterogeneity in outcomes in countries currently fighting to control malaria, and the challenges in increasing both domestic and international funding allocated to control and eliminate malaria, the efficient targeting of limited resources is critical to attain global malaria eradication goals.

GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution.

Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec.

Responses of non-native and native plant species to fluctuations of water availability in a greenhouse experiment.

Water availability strongly influences the survival, growth, and reproduction of most terrestrial plant species. Experimental evidence has well documented the effect of changes in total amount of water availability on non-native vs. native plants. However, little is known about how fluctuations in water availability affect these two groups, although more extreme fluctuations in water availability increasingly occur with prolonged drought and extreme precipitation events. Here, we grew seven non-native and seven native plant species individually in the greenhouse. Then, we exposed them to four watering treatments, each treatment with the same total amount of water, but with different divisions: W1 (added water 16 times with 125 mL per time), W2 (8 times, 250 mL per time), W3 (4 times, 500 mL per time), and W4 (2 times, 1000 mL per time). We found that both non-native and native plants produced the most biomass under medium frequency/magnitude watering treatments (W2 and W3). Interestingly, non-native plants produced 34% more biomass with the infrequent, substantial watering treatment (W4) than with frequent, minor watering treatment (W1), whereas native plants showed opposite patterns, producing 26% more biomass with W1 than with W4. Differences in the ratio of root to shoot under few/large and many/small watering treatments of non-native vs. native species probably contributed to their different responses in biomass production. Our results advance the current understanding of the effect of water availability on non-native plants, which are affected not only by changes in amount of water availability but also by fluctuations in water availability. Furthermore, our results indicate that an increased few/large precipitation pattern expected under climate change conditions might further promote non-native plant invasions. Future field experiments with multiple phylogenetically controlled pairs of non-native and native species will be required to enhance our understanding of how water availability fluctuations impact on non-native invasions.

Atypical and variable attention patterns reveal reduced contextual priors in children with autism spectrum disorder.

Accumulating evidence suggests that individuals with autism spectrum disorder (ASD) show impairments in using contextual priors to predict others' actions and make intention inference. Yet less is known about whether and how children with ASD acquire contextual priors during action observation and how contextual priors relate to their action prediction and intention inference. To form proper contextual priors, individuals need to observe the social scenes in a reliable manner and focus on socially relevant information. By employing a data-driven scan path method and areas of interest (AOI)-based analysis, the current study investigated how contextual priors would relate to action prediction and intention understanding in 4-to-9-year-old children with ASD (N = 56) and typically developing (TD) children (N = 50) during free viewing of dynamic social scenes with different intentions. Results showed that children with ASD exhibited higher intra-subject variability when scanning social scenes and reduced attention to socially relevant areas. Moreover, children with high-level action prediction and intention understanding showed lower intra-subject variability and increased attention to socially relevant areas. These findings suggest that altered fixation patterns might restrain children with ASD from acquiring proper contextual priors, which has cascading downstream effects on their action prediction and intention understanding.

"Do not inject our babies": a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines.

Designing effective childhood vaccination counseling guidelines, public health campaigns, and school-entry mandates requires a nuanced understanding of the information ecology in which parents make vaccination decisions. However, evidence is lacking on how best to "catch the signal" about the public's attitudes, beliefs, and misperceptions. In this study, we characterize public sentiment and discourse about vaccinating children against SARS-CoV-2 with mRNA vaccines to identify prevalent concerns about the vaccine and to understand anti-vaccine rhetorical strategies. We applied computational topic modeling to 149 897 comments submitted to regulations.gov in October 2021 and February 2022 regarding the Food and Drug Administration's Vaccines and Related Biological Products Advisory Committee's emergency use authorization of the COVID-19 vaccines for children. We used a latent Dirichlet allocation topic modeling algorithm to generate topics and then used iterative thematic and discursive analysis to identify relevant domains, themes, and rhetorical strategies. Three domains emerged: (1) specific concerns about the COVID-19 vaccines; (2) foundational beliefs shaping vaccine attitudes; and (3) rhetorical strategies deployed in anti-vaccine arguments. Computational social listening approaches can contribute to misinformation surveillance and evidence-based guidelines for vaccine counseling and public health promotion campaigns.

Application of multi-criteria group decision-making for water quality management.

As waste discharge into numerous river systems escalates, the pollution of water bodies typically rises. Given the limited capacity of rivers to withstand pollution and their constrained self-cleaning capabilities, treated pollutants from waste discharge must be released into the river. Despite numerous models and algorithms proposed for managing river water quality to meet standards, literature, to our awareness, lacks the utilization of a comprehensive multi-criteria group decision-making approach for water quality management, particularly in river systems. Therefore, this research introduces a new, comprehensive multi-criteria group decision-making for the management of water quality in the Haraz River basin, located in Iran. To do so, the water quality of the basin, a one-dimensional water quality model, QUAL2Kw, was employed to simulate and calibrate the water quality along the river. The simulation results revealed that the downstream water quality violates the water quality standards. To mitigate this issue, various scenarios for waste load allocation (WLA) were evaluated, including no wastewater treatment, primary wastewater treatment, advanced secondary wastewater treatment utilizing the activated sludge (AS) method, and advanced wastewater treatment via the membrane bioreactor (MBR) method. Utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS group decision-making model, it was determined that the optimal solution was the implementation of secondary wastewater treatment utilizing the activated sludge method for the 11 PS of pollution, while still adhering to Iranian water quality standard. In addition, the findings of the present study indicate that the implementation of primary wastewater treatment, advanced secondary wastewater treatment utilizing AS, and advanced wastewater treatment through MBR within the study area led to a significant enhancement in water quality. This enhancement ranged from 35 to 105% across various scenarios when compared to conditions where no actions were taken to the treatment of water.

Exploring climate change discourse on social media and blogs using a topic modeling analysis.

Climate change is one of the most pressing global issues of our time, and understanding public perception and awareness of the topic is crucial for developing effective policies to mitigate its effects. While traditional survey methods have been used to gauge public opinion, advances in natural language processing (NLP) and data visualization techniques offer new opportunities to analyze user-generated content from social media and blog posts. In this study, a new dataset of climate change-related texts was collected from social media sources and various blogs. The dataset was analyzed using BERTopic and LDA to identify and visualize the most important topics related to climate change. The study also used sentence similarity to determine the similarities in the comments written and which topic categories they belonged to. The performance of different techniques for keyword extraction and text representation, including OpenAI, Maximal Marginal Relevance (MMR), and KeyBERT, was compared for topic modeling with BERTopic. It was seen that the best coherence score and topic diversity metric were obtained with OpenAI-based BERTopic. The results provide insights into the public's attitudes and perceptions towards climate change, which can inform policy development and contribute to efforts to reduce activities that cause climate change.

A Latent Dirichlet Allocation approach to understanding students' perceptions of Automated Writing Evaluation.

Automated writing evaluation (AWE) has shown promise in enhancing students' writing outcomes. However, further research is needed to understand how AWE is perceived by middle school students in the United States, as they have received less attention in this field. This study investigated U.S. middle school students' perceptions of the MI Write AWE system. Students reported their perceptions of MI Write's usefulness using Likert-scale items and an open-ended survey question. We used Latent Dirichlet Allocation (LDA) to identify latent topics in students' comments, followed by qualitative analysis to interpret the themes related to those topics. We then examined whether these themes differed among students who agreed or disagreed that MI Write was a useful learning tool. The LDA analysis revealed four latent topics: (1) students desire more in-depth feedback, (2) students desire an enhanced user experience, (3) students value MI Write as a learning tool but desire greater personalization, and (4) students desire increased fairness in automated scoring. The distribution of these topics varied based on students' ratings of MI Write's usefulness, with Topic 1 more prevalent among students who generally did not find MI Write useful and Topic 3 more prominent among those who found MI Write useful. Our findings contribute to the enhancement and implementation of AWE systems, guide future AWE technology development, and highlight the efficacy of LDA in uncovering latent topics and patterns within textual data to explore students' perspectives of AWE.

Patterns and drivers of atmospheric nitrogen deposition retention in global forests.

Forests are the largest carbon sink in terrestrial ecosystems, and the impact of nitrogen (N) deposition on this carbon sink depends on the fate of external N inputs. However, the patterns and driving factors of N retention in different forest compartments remain elusive. In this study, we synthesized 408 observations from global forest 15N tracer experiments to reveal the variation and underlying mechanisms of 15N retention in plants and soils. The results showed that the average total ecosystem 15N retention in global forests was 63.04 ± 1.23%, with the soil pool being the main N sink (45.76 ± 1.29%). Plants absorbed 17.28 ± 0.83% of 15N, with more allocated to leaves (5.83 ± 0.63%) and roots (5.84 ± 0.44%). In subtropical and tropical forests, 15N was mainly absorbed by plants and mineral soils, while the organic soil layer in temperate forests retained more 15N. Additionally, forests retained more N 15 H 4 + $$ {}^{15}\mathrm{N}{\mathrm{H}}_4^{+} $$ than N 15 O 3 - $$ {}^{15}\mathrm{N}{\mathrm{O}}_3^{-} $$ , primarily due to the stronger capacity of the organic soil layer to retain N 15 H 4 + $$ {}^{15}\mathrm{N}{\mathrm{H}}_4^{+} $$ . The mechanisms of 15N retention varied among ecosystem compartments, with total ecosystem 15N retention affected by N deposition. Plant 15N retention was influenced by vegetative and microbial nutrient demands, while soil 15N retention was regulated by climate factors and soil nutrient supply. Overall, this study emphasizes the importance of climate and nutrient supply and demand in regulating forest N retention and provides data to further explore the impacts of N deposition on forest carbon sequestration.

Extreme functional specialization of fertile leaves in a widespread fern species and its implications on the evolution of reproductive dimorphism.

Resource allocation theory posits that organisms distribute limited resources across functions to maximize their overall fitness. In plants, the allocation of resources among maintenance, reproduction, and growth influences short-term economics and long-term evolutionary processes, especially during resource scarcity. The evolution of specialized structures to divide labor between reproduction and growth can create a feedback loop where selection can act on individual organs, further increasing specializaton and  resource allocation. Ferns exhibit diverse reproductive strategies, including dimorphism, where leaves can either be sterile (only for photosynthesis) or fertile (for spore dispersal). This dimorphism is similar to processes in seed plants (e.g., the production of fertile flowers and sterile leaves), and presents an opportunity to investigate divergent resource allocation between reproductive and vegetative functions in specialized organs. Here, we conducted anatomical and hydraulic analyses on Onoclea sensibilis L., a widespread dimorphic fern species, to reveal significant structural and hydraulic divergences between fertile and sterile leaves. Fertile fronds invest less in hydraulic architecture, with nearly 1.5 times fewer water-conducting cells and a nearly 0.5 times less drought-resistant xylem compared to sterile fronds. This comes at the increased relative investment in structural support, which may help facilitate spore dispersal. These findings suggest that specialization in ferns-in the form of reproductive dimorphism-can enable independent selection pressures on each leaf type, potentially optimizing spore dispersal in fertile fronds and photosynthetic efficiency in sterile fronds. Overall, our study sheds light on the evolutionary implications of functional specialization and highlights the importance of reproductive strategies in shaping plant fitness and evolution.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68-1700.73] to 3863.43€ [95% CI 1468.89-6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998 ; https://clinicaltrials.gov/ct2/show/NCT04747366 ; https://clinicaltrials.gov/ct2/show/NCT04679584 .

Clinical care for severe and persistent eating disorders in pediatric populations: Perspectives of health professionals.

OBJECTIVE: Models of treatment for adults with severe and enduring eating disorders focus on harm reduction and improving quality of life. However, there is a notable gap in the pediatric literature in this area. The current study set out to assess the perspectives of health professionals regarding clinical care for young people (e.g., ages 10-25 years) with severe and enduring eating disorders, and to explore perceptions about appropriate treatment options for these presentations. METHODS: Health professionals were invited to complete a two-stage online survey about their experiences with clinical care for pediatric eating disorders through Canadian and Australian professional eating disorder networks. Survey 1 included questions about their experiences in supporting individuals with severe and enduring presentations. Participants who completed Survey 2 reviewed clinical vignettes and shared their perspectives about treatment recommendations and models of care, including for a severe and enduring presentation. RESULTS: A total of 85 clinicians responded to questions on Survey 1 about severe and enduring eating disorder presentations. A portion of these respondents (n = 25) also participated in Survey 2. The majority of respondents to Survey 1 reported providing clinical care for pediatric severe and enduring eating disorder presentations. Amongst respondents to Survey 2, there was low consensus amongst respondents for the clinical care that would be most appropriate for young people with a severe and enduring eating disorder presentation. Numerous challenges in models of care for severe and enduring presentations in pediatric settings were raised in responses on Survey 2, with clinicians sharing their awareness of models focusing on quality of life, while also raising concerns about the appropriateness of these models for young people. CONCLUSIONS: The preliminary results of this study demonstrate that the majority of clinicians report that they have provided care to young people with severe and enduring presentations. There is a clear need for establishing guidance for clinicians working in pediatric eating disorder settings around models of care focused on quality of life. Engagement with interested parties, including those with lived experience, can clarify the development of terminology and clinical pathways for severe and enduring presentations of pediatric eating disorders.

Treatment models focusing on harm reduction and quality of life (as opposed to eating disorder recovery) are available for adults with severe and enduring eating disorders. However, these models are not widely available for young people. In fact, there is very limited research on severe and enduring eating disorder presentations in pediatric populations. We assessed the views of health professionals regarding clinical care for young people with severe and enduring eating disorder presentations, and asked professionals about what treatment options might be most appropriate for these presentations. Most participants reported providing clinical care for pediatric severe and enduring eating disorder presentations. However, clinicians had diverse views about the treatment that would be most appropriate for a severe and enduring eating disorder presentation in a young person. Further research and engagement with clinicians and those with lived experience is needed to clarify the terminology and clinical pathways for severe and enduring presentations of pediatric eating disorders.

Dynamic efficiency of tradable license system with time-flexible quantities.

Tradable license system (TLS) is a fundamental policy instrument for environmental management or resource development. We construct a muti-periods dynamic model with respect to a general TLS with three time-flexible quantity mechanisms: fixed quantity, solely banking, and banking and borrowing, in which the firm maximizes its discounted net benefits over the horizon by selecting an optimal license usage by license trading across agents or transferring across periods. The dynamic efficiency performance and price dynamics in TLS are respectively examined. The decentralized equilibrium in TLS with fixed quantity cannot achieve benefit-maximum unless initial license allocation is efficient. The decentralized behaviors in TLS with solely banking lead to benefit-maximum and price dynamics follows the Hotelling rule, if and only if the cumulative initial license allocation in each period is not less than the optimum, while TLS with banking and borrowing can achieve the optimal outcome and price dynamics follows Hotelling rule regardless of the initial allocation. The findings highlight the synergistic effects between the initial allocation of licenses and time-flexible quantity mechanisms in TLS design.

A Comprehensive, Multi-Faceted Strategy to Increase Pediatric Donor Heart Utilization.

BACKGROUND: Many hearts offered for pediatric heart transplantation (HT) are not placed. In 2016, we initiated a quality improvement endeavor to increase heart offer acceptance. This study assessed the effect of these interventions at our center. METHODS: Evaluation of pre-/post-implementation cohorts (1/1/2008-12/31/2016 vs. 1/1/2017- 7/1/2023) comparing donor heart utilization. Six interventions were iterated over time to increase offer acceptance ("extended criteria"): ABO-incompatible transplant, ex vivo perfusion for distanced donors, 3-dimensional total cardiac volume (TCV) assessment, acceptance of Hepatitis-C or SARS-COV-2 infected donors, and institutional culture change favoring consideration of donors previously considered unacceptable (Public Health Service Risk, long CPR duration, etc.). Outcomes studied included annual HT volume, median waitlist duration, sequence number at acceptance, and post-transplant clinical outcomes. RESULTS: From 1/2008-7/2023 annual transplant volume increased from 16/year to 25/year pre-/post-implementation. Three hundred-thirteen/389 (80%) listed patients were transplanted. Waitlist duration shortened post-implementation (P=0.01), as did the percentage of accepted heart offers utilizing at least one extended criterion (P<0.001). Institutional culture change and TCV assessment had the largest impact on donor heart utilization (P=0.04 &P<0.001). There was no difference in post-HT intubation or cardiovascular intensive care unit (CVICU) days (P= 0.05-0.9), though post-transplant hospitalization duration (P<0.001) increased. Post-transplant survival was unaffected by use of extended criteria hearts (P=0.3). CONCLUSIONS: We report increased donor heart offer acceptance resulting from a longitudinal, multi-faceted effort to increase organ offer utilization, with institutional culture change and TCV assessments having the greatest impact. Use of extended criteria hearts was not associated with inferior survival.

A transition from arbuscular to ectomycorrhizal forests halts soil carbon sequestration during subtropical forest rewilding.

Ecological succession and restoration rapidly promote multiple dimensions of ecosystem functions and mitigate global climate change. However, the factors governing the limited capacity to sequester soil organic carbon (SOC) in old forests are poorly understood. Ecological theory predicts that plants and microorganisms jointly evolve into a more mutualistic relationship to accelerate detritus decomposition and nutrient regeneration in old than young forests, likely explaining the changes in C sinks across forest succession or rewilding. To test this hypothesis, we conducted a field experiment of root-mycorrhizal exclusion in successional subtropical forests to investigate plant-decomposer interactions and their effects on SOC sequestration. Our results showed that SOC accrual rate at the 0-10 cm soil layer was 1.26 mg g-1 yr-1 in early-successional arbuscular mycorrhizal (AM) forests, which was higher than that in the late-successional ectomycorrhizal (EcM) forests with non-significant change. A transition from early-successional AM to late-successional EcM forests increase fungal diversity, especially EcM fungi. In the late-successional forests, the presence of ectomycorrhizal hyphae promotes SOC decomposition and nutrient cycle by increasing soil nitrogen and phosphorus degrading enzyme activity as well as saprotrophic microbial richness. Across early- to late-successional forests, mycorrhizal priming effects on SOC decomposition explain a slow-down in the capacity of older forests to sequester soil C. Our findings suggest that a transition from AM to EcM forests supporting greater C decomposition can halt the capacity of forests to provide nature-based global climate change solutions.

Factors Affecting the Situational Awareness of Armored Vehicle Occupants.

In the field of armored vehicles, up to 70% of accidents are associated with low levels of situational awareness among the occupants, highlighting the importance of situational awareness in improving task performance. In this study, we explored the mechanisms influencing situational awareness by simulating an armored vehicle driving platform with 14 levels of experimentation in terms of five factors: experience, expectations, attention, the cueing channel, and automation. The experimental data included SART and SAGAT questionnaire scores, eye movement indicators, and electrocardiographic and electrodermal signals. Data processing and analysis revealed the following conclusions: (1) Experienced operators have higher levels of situational awareness. (2) Operators with certain expectations have lower levels of situational awareness. (3) Situational awareness levels are negatively correlated with information importance affiliations and the frequency of anomalous information in non-primary tasks. (4) Dual-channel cues lead to higher levels of situational awareness than single-channel cues. (5) Operators' situational awareness is lower at high automation levels.

Benefits and costs: Understanding the influence of heavy metal pollution on environmental adaptability in Strauchbufo raddei tadpoles through an energy budget perspective.

Understanding the impact of environmental pollution on organismal energy budgets is crucial for predicting adaptive responses and potential maladaptation to stressors. However, the regulatory mechanism governing the trade-off between energy intake and consumption remains largely unknown, particularly considering the diverse adaptations influenced by exposure history in realistic field conditions. In the present study, we conducted a simulated field reciprocal transplant experiment to compare the energy budget strategies of Strauchbufo raddei tadpoles exposed to heavy metal. The simulated heavy metal concentrations (0.29 mg/L Cu, 1.17 mg/L Zn, 0.47 mg/L Pb, 0.16 mg/L Cd) mirrored the actual environmental exposure concentrations observed in the field habitat. This allowed for a comparison between tadpoles with parental chronic exposure to heavy metal pollutants in their habitat and those without such exposure. Results revealed that under heavy metal exposure, tadpoles originating from unpolluted areas exhibited heightened vulnerability, characterized by reduced food intake, diminished nutrient absorption, increased metabolism cost, reduced energy reserves, and increased mortality rates. In contrast, tadpoles originating from areas with long-term heavy metal pollution demonstrated adaptive strategies, manifested through adjustments in liver and small intestine phenotypes, optimizing energy allocation, and reducing energy consumption to preserve energy, thus sustaining survival. However, tadpoles from polluted areas exhibited certain maladaptive such as growth inhibition, metabolic suppression, and immune compromise due to heavy metal exposure. In conclusion, while conserving energy consumption has proven to be an effective way to deal with long-term heavy metal stress, it poses a threat to individual survival and population development in the long run.

Energy strategy alteration, rather than toxicity itself, interferes with the population fluctuation of Brachionus plicatilis exposed to water-accommodated fractions (WAFs) of crude oil.

Oil spills are reported to have conflicting impacts of either injury or resilience on zooplankton communities, and physiological plasticity is speculated to be the possible causative factor. But how? An explanation was sought by exposing the marine rotifer Brachionus plicatilis to a series of water-accommodated fractions (WAFs) of crude oil under controlled laboratory conditions, and population dynamics, which is the core issue for zooplankton facing external stress, were analyzed. The total hydrocarbon concentration of WAFs was quickly degraded from a concentration of 5.0 mg L-1 to half within 24 h and then remained stable. No acute lethality was observed; only motion inhibition was observed in the group treated with 10 %, 50 % and 100 % WAFs, which occurred simultaneously with inhibition of feeding and filtration. However, sublethal exposure to the WAFs concentration series presented stimulation impacts on reproduction and even the population of B. plicatilis. The negative correlation between motion and reproduction seemed to indicate that a shift in the distribution of individual energy toward reproduction rather than motion resulted in increased reproduction after exposure to WAFs. More evidence from transmission electron microscopy (TEM) revealed ultrastructural impairment in both the ovaries and cilia in each treated group, and imbalance in mitochondrial numbers was one of the distinct features of alteration. WAFs stress may alter the energy utilization and storage paradigm, as indicated by the significant elevation in glycogen and the significant decrease in lipid content after WAFs exposure. Further evidence from metabolomics analysis showed that WAFs stress increased the level of lipid metabolism and inhibited some of the pathways in glucose metabolism. Sublethal acute toxicity was observed only in the first 24 h with WAFs exposure, and an energy strategy consisting of changes in the utilization and storage paradigm and reallocation is responsible for the population resilience of B. plicatilis during oil spills.

Laboratory Information Management Systems in Oral Pathology: A Comprehensive Review.

Efficiency in oral pathological laboratory processes is paramount for timely and accurate diagnosis. This review explores various strategies and methodologies that help streamline oral pathological laboratory workflows to enhance productivity and reduce turnaround times. Key focus areas include specimen collection, handling, processing, and analysis. Optimization techniques such as automation, digitalization, and standardization are discussed in detail, emphasizing their role in minimizing errors and maximizing throughput. Additionally, the integration of advanced technologies such as artificial intelligence and machine learning is examined for their potential to improve laboratory operations. Moreover, the importance of quality control measures and compliance with regulatory standards is underscored as essential components of any successful laboratory streamlining initiative. By implementing a comprehensive approach that addresses the entire diagnostic pathway, oral pathological laboratories can achieve significant efficiency, ultimately leading to better patient care and outcomes.

Ecosystem engineers can regulate resource allocation strategies in associated plant species.

Balancing the biomass requirements of different functions for the purpose of population reproduction and persistence can be challenging for alpine plants due to extreme environmental stresses from both above- and below-ground sources. The presence of ecosystem engineers in alpine ecosystems effectively alleviates microenvironmental stresses, hence promoting the survival and growth of other less stress-tolerant species. However, the influence of ecosystem engineers on plant resource allocation strategies remains highly unexplored. In this study, we compared resource allocation strategies, including biomass accumulation, reproductive effort (RE), root fraction (RF), as well as relationships between different functions, among four alpine plant species belonging to Gentianaceae across bare ground, tussock grass-, cushion-, and shrub-engineered microhabitats. Shrub-engineered microhabitats exerted the strongest effects on regulating plant resource allocation patterns, followed by tussock grass- and cushion-engineered microhabitats. Additionally, apart from microhabitats, population background and plant life history also significantly influenced resource allocation strategies. Generally, plants established within engineered microhabitats exhibited higher biomass accumulation, as well as increased flower, leaf and stem production. Furthermore, individuals within engineered microhabitats commonly displayed lower RF, indicating a greater allocation of resources to above-ground functions while reducing allocation to root development. RE of annual plants was significantly higher than that of perennial plants. However, individuals of annual plants within engineered microhabitats showed lower RE compared to their counterparts in bare ground habitats; whereas perennial species demonstrated similar RE between microhabitat types. Moreover, RE was generally independent of plant size in bare-ground habitats but exhibited size-dependency in certain populations for some species within specific engineered microhabitat types. However, size-dependency did exist for absolute reproductive and root biomass allocation in most of the cases examined here. No trade-offs were observed between flower mass and flower number, nor between leaf mass and leaf number. The capacity of ecosystem engineers to regulate resource allocation strategies in associated plants was confirmed. However, the resource allocation patterns resulted synergistically from the ecosystem engineering effects, population environmental backgrounds, and plant life history strategies. In general, such regulations can improve individual survival and reproductive potential, potentially promoting population persistence in challenging alpine environments.