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Cold exposure, especially in combination with exercise, is a common procedure to fortify the body. However, its effects in old age are poorly understood. Using the homeostasis stability coefficient as an indicator, the body response to a 20-min swim in cold water was for the first time studied comprehensively in old and young Wistar rats. Effects on the hormonal, hematological, and morphofunctional systems of the liver and thymus were assessed. Unfavorable age-related changes in the stability of homeostasis were observed in old rats. The changes complicated the recovery after cold stress and required the involvement of a greater number of homeostatic mechanisms than in young rats. The liver was found to be the most vulnerable to cold stress. It was concluded that fortifying the body by cold exposure is possible to use in old age, but with due regard to age-related restrictions.

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Rising global temperatures are often identified as the key driver impacting ecosystems and the services they provide by affecting biodiversity structure and function. A disproportionate amount of our understanding of biodiversity and function is from short-term experimental studies and static values of biodiversity indices, lacking the ability to monitor long-term trends and capture community dynamics. Here, we analyse a biennial dataset spanning 32 years of macroinvertebrate benthic communities and their functional response to increasing temperatures. We monitored changes in species' thermal affinities to examine warming-related shifts by selecting their mid-point global temperature distribution range and linking them to species' traits. We employed a novel weighted metric using Biological Trait Analysis (BTA) to gain better insights into the ecological potential of each species by incorporating species abundance and body size and selecting a subset of traits that represent five ecosystem functions: bioturbation activity, sediment stability, nutrient recycling and higher and lower trophic production. Using biodiversity indices (richness, Simpson's diversity and vulnerability) and functional indices (richness, Rao's Q and redundancy), the community structure showed no significant change over time with a narrow range of variation. However, we show shifts in species composition with warming and increases in the abundance of individuals, which altered ecosystem functioning positively and/or non-linearly. Yet, when higher taxonomic groupings than species were excluded from the analysis, there was only a weak increase in the measured change in community-weighted average thermal affinities, suggesting changes in ecosystem functions over time occur independently of temperature increase-related shifts in community composition. Other environmental factors driving species composition and abundance may be more important in these subtidal macrobenthic communities. This challenges the prevailing emphasis on temperature as the primary driver of ecological response to climate change and emphasises the necessity for a comprehensive understanding of the temporal dynamics of complex systems.

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With the acceleration of urbanization, the risk of urban population exposure to environmental pollutants is increasing. Protecting public health is the top priority in the construction of smart cities. The purpose of this study is to propose a method for identifying toxicological biological indicators of human exposure in smart cities based on public health data and deep learning to achieve accurate assessment and management of exposure risks. Initially, the study used a network of sensors within the smart city infrastructure to collect environmental monitoring data, including indicators such as air quality, water quality, and soil pollution. Using public health data, a database containing information on types and concentrations of environmental pollutants has been established. Convolutional neural network was used to recognize the pattern of environmental monitoring data, identify the relationship between different indicators, and build the correlation model between health indicators and environmental indicators. Identify biological indicators associated with environmental pollution exposure through training optimization. Experimental analysis showed that the prediction accuracy of the model reached 93.45%, which could provide decision support for the government and the health sector. In the recognition of the association pattern between respiratory diseases, cardiovascular diseases and environmental exposure factors such as PM2.5 and SO2, the fitting degree between the model and the simulation value reached more than 0.90. The research design model can play a positive role in public health and provide new decision-making ideas for protecting public health.

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Chemical pollution is one of the most important threats to freshwater ecosystems. The plethora of potentially occurring chemicals and their effects in complex mixtures challenge standard monitoring methods. Effect-based methods (EBMs) are proposed as complementary tools for the assessment of chemical pollution and toxic effects. To investigate the effects of chemical pollution, the ecological relevance of EBMs and the potential of macroinvertebrates as toxicity-specific bioindicators, ecological and ecotoxicological data were linked. Baseline toxicity, mutagenicity, dioxin-like and estrogenic activity of water and sediment samples from 30 river sites in central Germany were quantified with four in vitro bioassays. The responses of macroinvertebrate communities at these sites were assessed by calculating 16 taxonomic and functional metrics and by investigating changes in the taxonomic and trait composition. Principal component analysis revealed an increase in toxicity along a joint gradient of chemicals with different modes of action. This toxicity gradient was associated with a decrease in biodiversity and ecological quality, as well as significant changes in taxonomic and functional composition. The strength of the effects suggested a strong impact of chemical pollution and underlined the suitability of EBMs in detecting ecological relevant effects. However, the metrics, taxa, and traits associated with vulnerability or tolerance to toxicity were found to also respond to other stressors in previous studies and thus may have only a low potential as toxicity-specific bioindicators. Because macroinvertebrates respond integratively to all present stressors, linking both ecological and environmental monitoring is necessary to investigate the overall effects but also isolate individual stressors. EBMs have a high potential to separate the toxicity of chemical mixtures from other stressors in a multiple stressor scenario, as well as identifying the presence of chemical groups with specific modes of action.

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Elasmobranch populations are in steep decline mainly due to overfishing bycatch, but parasites may accelerate the collapse of vulnerable and/or highly parasitized species. We therefore studied metazoan parasites of Rajidae from the northeast Atlantic: vulnerable Leucoraja fullonica, near-threatened Raja brachyura, Raja clavata, Raja microocellata and Raja undulata, and least-concerned Raja montagui and Leucoraja naevus. Overall prevalence varied from 19% for R. montagui to 100% for L. fullonica. Parasite communities differed between skate species, and prevalence and abundance were higher for L. fullonica, R. microocellata, and R. undulata. We recorded 11 parasite taxa in the study: three nematodes, six cestodes, one monogenean, and one myxosporean. Whatever the skate species, the parasite component community comprised at least two nematode taxa among Phocanema spp., Proleptus sp. and Anisakis simplex. DNA-sequencing revealed that Phocanema azarasi and Phocanema krabbei both occurred in R. microocellata and R. undulata. Phocanema spp. was first recorded in L. fullonica, L. naevus, R. microocellata, R. montagui, and R. undulata, as Proleptus sp. in L. fullonica, and A. simplex in L. fullonica and R. clavata, Rockacestus sp. and Nybelinia sp. in R. undulata, and gill-myxosporeans on L. fullonica, L. naevus, R. microocellata, and R. undulata. The occurrence of 16 new host-parasite associations suggests potential environmental changes. Information provided by trophically transmitted helminths confirmed an opportunistic skate diet based on crustaceans and fish. We discuss results in terms of host fitness loss, bioindicator role of parasites, and anisakiasis risk. We recommend incorporating parasitology in research to improve elasmobranch conservation.

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With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

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The objective of the present study was to assess the levels of circulating cytokines in patients with diffuse large B-cell lymphoma (DLBCL), and to examine the associations between the cytokine levels, clinicopathological manifestations and patient prognosis. The study enrolled 49 patients with DLBCL, 11 patients with chronic lymphocytic leukemia/small lymphocytic lymphoma and 67 healthy controls from Zhejiang Provincial People's Hospital (Hangzhou, China) between January 2017 and January 2020. The serum levels of interleukin (IL)-2, IL-4, IL-6, IL-10, IL-17, tumor necrosis factor (TNF)-α and interferon (IFN)-γ were measured using flow cytometry. The IL-6, IL-10 and IFN-γ levels were significantly raised in patients with DLBCL compared with those in the healthy controls (P<0.05). The levels of IL-10 were significantly higher in patients with raised levels of circulating lactate dehydrogenase (P<0.05), while increases in both IL-6 and IL-10 were associated with raised C-reactive protein (CRP) levels, with IL-6 levels positively associated with those of serum CRP (P<0.01; r=0.66). Additionally, International Prognostic Index (IPI) risk stratification of patients with DLBCL was strongly associated with circulating IL-6 and IL-10 levels. Raised IL-6, IL-10 and TNF-α levels were linked with worse short-term treatment efficacies (P<0.05). Moreover, the accuracy of the model predicting short-term treatment response in patients with DLBCL, obtained using the support vector machine algorithm, was 81.63%. It was also found that raised serum IL-6 and IL-10 levels, together with reduced levels of IL-17, were associated with survival of <1 year in patients with DLBCL (P<0.05), although no significant link was found between cytokine levels and long-term overall survival. In conclusion, the serum levels of IL-6, IL-10, IL-17, TNF-α and IFN-γ can potentially serve as biological indicators of DLBCL tumor immune status, and combined application with the IPI score can be a robust prognostic indicator in patients with DLBCL.

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Affective states, such as emotions, are presumably widespread across the animal kingdom because of the adaptive advantages they are supposed to confer. However, the study of the affective states of animals has thus far been largely restricted to enhancing the welfare of animals managed by humans in non-natural contexts. Given the diversity of wild animals and the variable conditions they can experience, extending studies on animal affective states to the natural conditions that most animals experience will allow us to broaden and deepen our general understanding of animal welfare. Yet, this same diversity makes examining animal welfare in the wild highly challenging. There is therefore a need for unifying theoretical frameworks and methodological approaches that can guide researchers keen to engage in this promising research area. The aim of this article is to help advance this important research area by highlighting the central relationship between physiology and animal welfare and rectify its apparent oversight, as revealed by the current scientific literature on wild animals. Moreover, this article emphasises the advantages of including physiological markers to assess animal welfare in the wild (e.g. objectivity, comparability, condition range, temporality), as well as their concomitant limitations (e.g. only access to peripheral physiological markers with complex relationships with affective states). Best-practice recommendations (e.g. replication and multifactorial approaches) are also provided to allow physiological markers to be used most effectively and appropriately when assessing the welfare of animals in their natural habitat. This review seeks to provide the foundation for a new and distinct research area with a vast theoretical and applied potential: wild animal welfare physiology.

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Pollution by anthropogenic litter is a major threat to global ecosystems. Seabirds are frequently used as environmental monitors of litter ingestion, but similar research is rare for terrestrial birds. Here, we focused on pellet analysis from 117 nests of an iconic bird of the Western Palearctic, the white stork (Ciconia ciconia), breeding in southern and southwestern Poland in a farmland landscape, far away from large dumps and landfills. We found that most prey items in the diet of white storks were invertebrates (particularly from orders Coleoptera, Orthoptera, and Hymenoptera) but vertebrate prey comprised most of the biomass. Further analysis revealed that anthropogenic litter was found in 22.7% of pellets (34.2% of breeding pairs) with plastic (8.4%) and cigarette filters (6.9%) being most prevalent. This study represents the first assessment through pellet analysis of the ingestion of anthropogenic litter by live wild storks in Poland and also by a migratory population of white storks. Our study indicates a potentially significant transfer of plastic and other anthropogenic material through terrestrial food webs.

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The continuous increment in world population coupled with the greatest natural resource consumption and waste generation has an enormous impact on the environment. To date, using biological indicators (bioindicators) to evaluate the biological quality of natural environments is very common. Nonetheless, selecting those suitable for each ecosystem or contaminant is one of the most important issues for environmental sciences. Bacteria and helminths are mainly related to fecal contamination, while antibiotic-resistant bacteria, fungi, viruses, and microalgae are organisms used to determine deteriorated ecosystems by diverse contaminants. Nowadays, each bioindicator is used as a specific agent of different contaminant types, but detecting and quantifying these bioindicator microorganisms can be performed from simple microscopy and culture methods up to a complex procedure based on omic sciences. Developing new techniques based on the metabolism and physiological responses of traditional bioindicators is shown in a fast environmental sensitivity analysis. Therefore, the present review focuses on analyzing different bioindicators to facilitate developing suitable monitoring environmental systems according to different pollutant agents. The traditional and new methods proposed to detect and quantify different bioindicators are also discussed. Their vital role is considered in implementing efficient ecosystem bioprospection, restoration, and conservation strategies directed to natural resource management.

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This research quantitatively evaluated the diversity of plants to protect vulnerable species. To measure vegetation information, the appropriate sampling plot size was determined based on the canopy cover of the dominant species of the study area (1 m2). Then, in each unit, sampling was done along 3 transects of 100 m. Along each transect, 10 plots with dimensions of one square meter were placed at a distance of 10 m from each other. In each plot, the type, life forms, frequency of plant species, and species density were recorded. Species diversity indices were calculated using Ecological Methodology software. The values obtained from these indicators were analyzed in SPSS 24 statistical software and using the F test. The results of the Analysis of variance (ANOVA) showed that the highest values of the species diversity indices are in the middle altitudes (ecotone) class. ANOVA of the richness, evenness, and heterogeneity indices in different altitude classes showed that the values of the richness indices were not significant, but among the indices related to the heterogeneity, the Hill index and all the evenness indices were significant. Comparing the numerical indices of our communities enables us to determine the impact of environmental stress in a single community to choose the best habitat among a similar group for conservation. A community that has high diversity and richness is important for conservation. Therefore, the authorities must prevent the destruction of the vegetation of the study area in connection with the implementation of principled and correct management by the potential of the region, but also to reduce the pressure of livestock grazing and carry out corrective and restoration operations, to turn these rangelands towards rich diversity.

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This research aims to enhance the classification and prediction of ischemic heart diseases using machine learning techniques, with a focus on resource efficiency and clinical applicability. Specifically, we introduce novel non-invasive indicators known as Campello de Souza features, which require only a tensiometer and a clock for data collection. These features were evaluated using a comprehensive dataset of heart disease cases from a machine learning data repository. Our findings highlight the ability of machine learning algorithms to not only streamline diagnostic procedures but also reduce diagnostic errors and the dependency on extensive clinical testing. Three key features-mean arterial pressure, pulsatile blood pressure index, and resistance-compliance indicator-were found to significantly improve the accuracy of machine learning algorithms in binary heart disease classification. Logistic regression achieved the highest average accuracy among the examined classifiers when utilizing these features. While such novel indicators contribute substantially to the classification process, they should be integrated into a broader diagnostic framework that includes comprehensive patient evaluations and medical expertise. Therefore, the present study offers valuable insights for leveraging data science techniques in the diagnosis and management of cardiovascular diseases.

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Insect pollinators provide an important ecosystem service that supports global biodiversity and environmental health. The study investigates the effects of the environmental matrix on six oxidative stress biomarkers in the honey bee Apis mellifera. Thirty-five apiaries located in urban, forested, and agricultural areas in Central Italy were sampled during the summer season. Enzyme activities in forager bees were analyzed using an artificial neural network, allowing the identification and representation of the apiary patterns in a Self-Organizing Map. The SOM nodes were correlated with the environmental parameters and tissue levels of eight heavy metals. The results indicated that the apiaries were not clustered according to their spatial distribution. Superoxide dismutase expressed a positive correlation with Cr and Mn concentrations; catalase with Zn, Mn, Fe, and daily maximum air temperature; glutathione S-transferase with Cr, Fe, and daily maximal air temperature; and glutathione reductase showed a negative correlation to Ni and Fe exposure. This study highlights the importance of exploring how environmental stressors affect these insects and the role of oxidative stress biomarkers. Artificial neural networks proved to be a powerful approach to untangle the complex relationships between the environment and oxidative stress biomarkers in honey bees. The application of SOM modeling offers a valuable means of assessing the potential effects of environmental pressures on honey bee populations.

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Marine microplastic (MP) pollution is becoming a serious problem and their potentially toxic effects on marine organisms have attracted much attention. Sea cucumber is very important for the safety and health of marine ecosystems. However, there have been relatively few studies on the effects of microplastic pollution on sea cucumbers at environmentally-related concentrations and under controlled conditions. Therefore, this study evaluated the effects of polyethylene terephthalate (PET) microplastics (particle sizes: 0.5-45 µm, 2-200 µm, and 20-300 µm; and three concentration levels for each particle size, approximately 103, 104, and 105 particles/kg) on the basic biological indicators, intestinal digestive enzymes, and intestinal flora of Apostichopus japonicus after a 28-day feeding experiment. This study showed that environmentally-related and high concentrations of microplastics had little effect on A. japonicus. This study provides valuable reference information about the effects of marine microplastic pollution on sea cucumbers.

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The environmental contamination due to bacterial proliferation vs their identification is the major deciding factor in the spread of diseases leading to pandemics. The advent of drug-resistant pathogenic contaminants in our environment has further added to the load of complications associated with their diagnosis and treatment. Obstructing the spread of such infections, prioritizes the expansion of sensor-based diagnostics, effectuating, a sturdy detection of disease-causing microbes, contaminating our surroundings in shortest possible time, with minimal expenditure. Among many sensors known, optical biosensors promote the recognition of pathogens befouling the environment through a comparatively intuitive, brisk, portable, multitudinous, and thrifty approach. This article reviews the recent progresses in optical biosensor-based systems for effective environmental monitoring. The technical and methodological perspectives of fundamental optical-sensing platforms are reviewed, combined with the pros and cons of every procedure. Eventually, the obstacles lying in the path of development of an effective optical biosensor device for bio-monitoring and its future perspectives are highlighted in the present work.

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OBJECTIVE: This study aimed to investigate the efficacy of inflammatory markers (NLR, PLR) combined with tumor markers (CA50, CA199, CEA) in the diagnosis of colorectal cancer metastasis by a single-center retrospective study. METHODS: A total of 1163 CRC patients who received treatments in our hospital from January 2017 to December 2021 were enrolled retrospectively. Patients were grouped according to the absence of metastasis. The separate efficacy of tumor markers, NLR and PLR, was evaluated in the diagnosis of metastasis of colorectal cancer using ROC curve analysis, and their optimal cut-off values for distant metastases from colorectal cancer were determined. The area under the ROC curve (AUC) of the tumor markers combined with NLR and PLR was calculated by binary logistic regression analysis to evaluate the diagnostic efficacy of metastasis of colorectal cancer. In addition, patients were divided into two groups of high and low levels according to the optimal cut-off values, and the effects of NLR, PLR, and tumor markers on distant metastasis of colorectal cancer were evaluated using multiple logistic regression analysis. RESULT: The abnormal rate of CA50, CA199, CEA, NLR, and PLR in two subgroupsIt was statistically significant (P < 0.05). After AUC testifying, the diagnostic efficacy of NLR and PLR was equivalent to that of tumor marker (P > 0.05). In assessment of liver metastasis, peritoneal metastasis, and multiple metastasis, AUC of NLR and PLR with CRC-specific tumor markers showed higher predictive efficacy than AUC without combined NLR nor PLR. The CA50, CA199, CEA, PLR, and NLR were proved independently associated with metastasis using multiple logistic regression analysis (P < 0.05). CONCLUSION: NLR and PLR are noted tumor markers of colorectal cancer, which are characterized by noninvasive, high diagnostic efficacy, easy availability, and low cost. They can be combined with traditional tumor markers to evaluate and diagnose colorectal cancer metastasis by clinicians.

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Intensification of crop cultivation can have detrimental environmental consequences that however can be prevented by monitoring of the specific biological indicators sensitive to changes in the ambient environment. In this study the impact of crop type (spring wheat and corn) and cultivation intensity on the community of ground beetles (Coleoptera: Carabidae) in the forest-steppe of Western Siberia was investigated. A total of 39 species from 15 genera were collected. Ground beetles' community was characterized by a high evenness of species distribution across the agroecosystems. The average Jaccard's similarity index for species presence/absence was 65%, and for abundance it was 54%. The significant difference in the distribution of predatory and mixophytophages ground beetles in wheat crops (U test, P < 0.05) can be justified by the constant suppression of the weed component and the use of insecticides that lead to the dominance of the predators. Fauna of wheat crops was more diverse than that in corn (Margalef index, U test, P < 0.05). No significant differences in biological diversity indexes, except for the Simpson dominance index (U test, P < 0.05, wheat), were found in ground beetle communities in crops at different levels of intensification. A certain differentiation of predatory species was caused by the selective occurrence of the litter-soil species, especially abundant in the row-crop. The specificity of the ground beetle community of corn crops may have been caused by repeated inter-row tillage, which influenced the increase in porosity and topsoil relief and contributed to the creation of favorable microclimatic conditions. In general, the applied level of agrotechnological intensification had no significant effect on the species composition and ecological structure of beetle communities in agrolandscapes. The use of bioindicators made it possible to assess the environmental sustainability of the agricultural environment and also creates the prerequisites for the development of ecologically directed correction of agrotechnological operations in agroecosystem management.

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The voluminous nature of palm oil mill effluent (POME) is directly associated with environmental hazards and could be turned into biorefinery products. The POME, rich in BOD, COD, and oil and grease, with few hazardous materials such as siloxanes, fatty acid methyl ester, and phenolic compounds that may significantly increase the risk of violating the effluent quality standards. Recently, the application of chemical and biological risk assessment that can use electrochemical sensors and microalgae-like species has gained paramount attention towards its remediation. This review describes the existing risk assessment for POME and recommends a novel assessment approach using fish species including invasive ones as suitable for identifying the toxicants. Various physico-chemical and biological treatments such as adsorption, coagulation-flocculation, photo-oxidation, solar-assisted extraction, anaerobic digestion, integrated anaerobic-aerobic, and microalgae cultivation has been investigated. This paper offers an overview of anaerobic technologies, with particular emphasis on advanced bioreactors and their prospects for industrial-level applications. To illustrate, palmitic acid and oleic acid, the precursors of fatty acid methyl ester found in POME pave the way to produce biodiesel with 91.45%. Although there are some challenges in attaining production at an economic scale, this review offers some opportunities that could help in overcoming these challenges.

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Legacies of past land use persist today in the form of incised, single-threaded stream channels with dramatically different hydrologic functions of pre-colonial stream valleys. Restoration practices that aim to return lost hydrologic functions by re-establishing floodplain and groundwater connections should result in stream habitat and biological assemblages that differ from modern, single-threaded channels. The aim of this case study was to identify attributes of macroinvertebrate assemblages that might serve as biological indicators of improved hydrologic functions following the restoration of a stream-wetland complex, similar to a Stage 0 restoration, of a headwater valley in the Western Allegheny region of the USA. We monitored hydrologic functions and macroinvertebrate assemblages from stream reaches of a restored and unrestored site over multiple years during the early years following restoration. Reduced bed mobility and increased flow duration indicated improved hydrologic functions from the restored site. Aggregate metrics that capture functional attributes of macroinvertebrate assemblage (i.e., density and biomass) were consistently greater from the restored site. EPT biomass from restored pools was 3-4 × greater than amounts from the unrestored site as a result of consistently greater mayfly abundance. Restored pools also supported a subassemblage of taxa with life history attributes that are aligned with habitat conditions created from improved hydrologic functions. Results from this case study demonstrate the importance of habitat-specific sampling designs that report the absolute abundance of potential biological indicators. Findings from this case study should help guide the development of rapid biological indicators of improved hydrologic functions.

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Welding operations are widely present in the manufacturing production process, involving a large number of occupational groups, and are the key occupations where work injuries and occupational diseases occur in China. For different welding processes and welding materials, the content and focus of occupational health monitoring are different. At present, the item of occupational health examination in welding operation is in poor consistency with the on-site exposure of occupational hazard factors, and it is mainly concentrated in the stage of disease development, which can not reflect the early health damage caused by welding dust exposure in time. The emergence of biomarkers of welding dust can make up for this defect. Therefore, it is of great significance to describe the current situation of occupational health monitoring of welding dust and summarize the research progress of related biomarkers for the early prevention of diseases caused by welding dust and the practice of occupational health monitoring.

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