Overcoming the coupled climate and biodiversity crises and their societal impacts.

Earth's biodiversity and human societies face pollution, overconsumption of natural resources, urbanization, demographic shifts, social and economic inequalities, and habitat loss, many of which are exacerbated by climate change. Here, we review links among climate, biodiversity, and society and develop a roadmap toward sustainability. These include limiting warming to 1.5°C and effectively conserving and restoring functional ecosystems on 30 to 50% of land, freshwater, and ocean "scapes." We envision a mosaic of interconnected protected and shared spaces, including intensively used spaces, to strengthen self-sustaining biodiversity, the capacity of people and nature to adapt to and mitigate climate change, and nature's contributions to people. Fostering interlinked human, ecosystem, and planetary health for a livable future urgently requires bold implementation of transformative policy interventions through interconnected institutions, governance, and social systems from local to global levels.

Quantitative susceptibility mapping improves cerebral microbleed detection relative to susceptibility-weighted images.

BACKGROUND AND PURPOSE: Cerebral microbleed (CMB) detection impacts disease diagnosis and management. Susceptibility-weighted imaging (SWI) MRI depictions of CMBs are used with phase images (SWIP) to distinguish blood from calcification, via qualitative intensity evaluation (bright/dark). However, the intensities depicted for a single lesion can vary within and across consecutive SWIP image planes, impairing the classification of findings as a CMB. We hypothesize that quantitative susceptibility mapping (QSM) MRI, which maps tissue susceptibility, demonstrates less in- and through-plane intensity variation, improving the clinician's ability to categorize a finding as a CMB. METHODS: Forty-eight patients with acute intracranial hemorrhage who received multi-echo gradient echo MRI used to generate both SWI/SWIP and morphology-enabled dipole inversion QSM images were enrolled. Five hundred and sixty lesions were visually classified as having homogeneous or heterogeneous in-plane and through-plane intensity by a neuroradiologist and two diagnostic radiology residents using published rating criteria. When available, brain CT scans were analyzed for calcification or acute hemorrhage. Relative risk (RR) ratios and confidence intervals (CIs) were calculated using a generalized linear model with log link and binary error. RESULTS: QSM showed unambiguous lesion signal intensity three times more frequently than SWIP (RR = 0.3235, 95% CI 0.2386-0.4386, p<.0001). The probability of QSM depicting homogeneous lesion intensity was three times greater than SWIP for small (RR = 0.3172, 95% CI 0.2382-0.4225, p<.0001), large (RR = 0.3431, 95% CI 0.2045-0.5758, p<.0001), lobar (RR = 0.3215, 95% CI 0.2151-0.4805, p<.0001), cerebellar (RR = 0.3215, 95% CI 0.2151-0.4805, p<.0001), brainstem (RR = 0.3100, 95% CI 0.1192-0.8061, p = .0163), and basal ganglia (RR = 0.3380, 95% CI 0.1980-0.5769, p<.0001) lesions. CONCLUSIONS: QSM more consistently demonstrates interpretable lesion intensity compared to SWIP as used for distinguishing CMBs from calcification.

Developing a new approach for design support of subsurface constructed wetland using machine learning algorithms.

Knowing the effluent quality of treatment systems in advance to enable the design of treatment systems that comply with environmental standards is a realistic strategy. This study aims to develop machine learning - based predictive models for designing the subsurface constructed wetlands (SCW). Data from the SCW literature during the period of 2009-2020 included 618 sets and 10 features. Five algorithms namely, Random forest, Classification and Regression trees, Support vector machines, K-nearest neighbors, and Cubist were compared to determine an optimal algorithm. All nine input features including the influent concentrations, C:N ratio, hydraulic loading rate, height, aeration, flow type, feeding, and filter type were confirmed as relevant features for the predictive algorithms. The comparative result revealed that Cubist is the best algorithm with the lowest RMSE (7.77 and 21.77 mg.L-1 for NH4-N and COD, respectively) corresponding to 84% of the variance in the effluents explained. The coefficient of determination of the Cubist algorithm obtained for NH4-N and COD prediction from the test data were 0.92 and 0.93, respectively. Five case studies of the application of SCW design were also exercised and verified by the prediction model. Finally, a fully developed Cubist algorithm-based design tool for SCW was proposed.

Effect Of Calcium Silicate, Sodium Phosphate, and Fluoride on Dentinal Tubule Occlusion and Permeability in Comparison to Desensitizing Toothpaste: An In Vitro Study.

This study compared the ability of a calcium silicate-, sodium phosphate-, and fluoride-based (CSSPF) toothpaste (TP) in promoting dentinal tubule occlusion and reducing dentin permeability with that of other commercially available antisensitivity TPs. Seventy-eight dentin discs (1.0±0.1 mm thick) were prepared from the midcoronal area and were treated with 37% phosphoric acid for 2 minutes; then they were randomly divided into six groups according to treatments: No treatment [positive control (PC)], entirely covered with nail varnish [negative control (NC)], hydroxyapatite (HAP)-containing TP [Desensin Repair (DES)], NovaMin-based [Sensodyne Repair & Protect (SEN)], CSSPF-based TP [Regenerate Advanced (REG)], sodium monofluorophosphate, potassium citrate, zinc citrate TP [Signal Sensitive Expert (SIG)]. Dentin permeability was tested by the dye percolation method (DP%). Scanning electron microscope (SEM) micromorphological and energy dispersive X-ray elemental analysis (EDX) of the dentin surfaces were done following each treatment. Results were analyzed using one-way analysis of variance (ANOVA) followed by Tukey post hoc test at a 95% confidence level (α=0.05). All the tested groups showed higher DP% than NC and lower percolation than the PC (p<0.05). REG and SIG were statistically comparable, and showed significantly lower DP% (p<0.05) than SEN and DES. None of the TPs tested was able to obliterate the lumen of the dentinal tubules (DT) completely. REG exhibited the highest weight percentage of calcium deposition, followed by SEN. Compared to the tested desensitizing TPs, CSSPF-based TPs demonstrated equal or less dentin permeability and better DT occlusion.

White hard clam (Meretrix lyrata) shells as novel filter media to augment the phosphorus removal from wastewater.

It is well recognized that filter media play a crucial role in constructed wetlands (CWs) for decontamination of phosphorus (P)-rich wastewater. This study investigates the suitability of raw white hard clam shells (WHC) and white hard clam shells thermally modified at 800 °C (WHC-M800) as potential media to enhance P treatment performance in CWs. The results indicated that both WHC and WHC-M800 displayed appropriate physicochemical properties, such as high porosity, excellent hydraulic conductivity, and rich Ca content. WHC-M800 exhibited a superior P adsorption capacity (38.7 mg/g) to WHC (12.8 mg/g). However, the practical utilization of WHC-M800 as filter media in CWs may be compromised, due to certain limitations, for example: extremely high pH values in the post-adsorption solutions; high weight losses during calcination and adsorption processes; low mechanical strength; and intensive energy consumption. In contrast, the WHC demonstrated significant advantages of reasonably high P adsorption capacity, locally abundant availability, low cost, and marginal side effects. The fractionation of inorganic P of WHC and WHC-M800 revealed that Ca-bounded P was the most dominant binding form, followed by loosely bound P, Fe-P, occluded P, and Al-P. The present study demonstrates that recycling of WHC shells as a potential substrate in CWs provides a feasible method for upgrading P removal in CWs. Additionally, it helps to reduce waste WHC shells in a simple, cheap, and eco-friendly way, thus can double environmental benefits.

White hard clam (Meretrix lyrata) shells media to improve phosphorus removal in lab-scale horizontal sub-surface flow constructed wetlands: Performance, removal pathways, and lifespan.

This work examined the phosphorus (P) removal from the synthetic pretreated swine wastewater using lab-scale horizontal sub-surface flow constructed wetlands (HSSF-CWs). White hard clam (Meretrix lyrata) shells (WHC) and Paspalum atratum were utilized as substrate and plant, respectively. The focus was placed on treatment performance, removal mechanisms and lifespan of the HSSF-CWs. Results indicated that WHC-based HSSF-CW with P. atratum exhibited a high P removal (89.9%). The mean P efluent concentration and P removal rate were 1.34 ± 0.95 mg/L and 0.32 ± 0.03 g/m2/d, respectively. The mass balance study showed that media sorption was the dominant P removal pathway (77.5%), followed by microbial assimilation (14.5%), plant uptake (5.4%), and other processes (2.6%). It was estimated the WHC-based bed could work effectively for approximately 2.84 years. This WHC-based HSSF-CWs technology will therefore pave the way for recycling Ca-rich waste materials as media in HSSF-CWs to enhance P-rich wastewater purification.

A critical review on life cycle assessment and plant-wide models towards emission control strategies for greenhouse gas from wastewater treatment plants.

For decades, there has been a strong interest in mitigating greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs). Numerous models were developed to measure the emissions and propose the quantification. Existing studies looked at the relationship between GHG emissions and operational cost (OCI), which is one of the most important indicators for decision-makers. Other parameters that can influence the control strategies include the effluent quality (EQI) and total environmental impacts. Plant-wide models are reliable methods to examine the OCI, EQI and GHG emissions while Life cycle assessment (LCA) works to assess the potential environmental impacts. A combined LCA and plant-wide model proved to be a valuable tool evaluating and comparing strategies for the best performance of WWTPs. For this study involving a WWTP, the benchmark model is used while LCA is the decision tool to find the most suitable treatment strategy. LCA adds extra criteria that complement the existing criteria provided by such models. Complementing the cost/performance criteria is proposed for plant-wide models, including environmental evaluation, based on LCA, which provides an overall better assessment of WWTPs. It can capture both the dynamic effects and potential environmental impacts. This study provides an overview of the integration between plant-wide models and LCA.

Education and devices to prevent blood and body fluid exposures.

BACKGROUND: Healthcare workers are at risk of blood and body fluid exposures (BBFE) while delivering care to patients. Despite recent technological advances such as safety-engineered devices (SEDs), these injuries continue to occur in healthcare facilities worldwide. AIMS: To assess the impact of an education and SEDs workplace programme on rates of reported exposures. METHODS: A retrospective cohort study, utilizing interrupted time series analysis to examine reported exposures between 2005 and 2015 at a 600-bed hospital in Perth, Western Australia. The hospital wards were divided into four cohorts. RESULTS: A total of 2223 records were available for analysis. The intervention was most effective for the first cohort, with significant improvements both short-term (reduction of 12 (95% CI 7-17) incidents per 1000 full-time equivalent (FTE) hospital staff) and long-term (reduction of 2 (CI 0.6-4) incidents per 1000 FTE per year). Less significant or consistent impacts were observed for the other three cohorts. Overall, the intervention decreased BBFE exposure rates at the hospital level from 19 (CI 18-20) incidents per 1000 FTE pre-intervention to 11 (CI 10-12) incidents per 1000 FTE post-intervention, a 41% reduction. No exposures resulted in a blood-borne virus infection. CONCLUSIONS: The intervention was most effective in reducing exposures at a time when incidence rates were increasing. The overall effect was short-term and did not further reduce an already stabilized trend, which was likely due to improved safety awareness and practice, induced by the first cohort intervention.

Development of a water cycle management approach to Sponge City construction in Xi'an, China.

In recent years, climate change, population growth, and inefficient use of water have exacerbated the water resources scarcity problems around the world. Hence, this paper establishes a new approach of Sponge City construction (SCC) based on water cycle management (WCM) for the sustainable exploitation of groundwater, recycled wastewater and rainwater in the Xi'an Siyuan University. The University is located in an isolated area that is far away from the city center so that no centralized water supply system could be utilized. To mitigate water scarcity problems in the University, 39% of the annual rainfall is harvested and stored from impervious surfaces and grasslands by using the Curve Number (CN) method. This stored water is reused for non-potable purposes: 40% for toilet flushing and 60% as miscellaneous water. According to findings, the available rainwater of500-700 m3/d accounts for 16-23% of the non-potable water from April to December. Moreover, the utilization rate of water resources increases from 204% to 227%. With the minimum volume of large-scale rainwater harvesting cistern of 52,760 m3, the environment could be adequately watered while improving the expansion and development conditions on the campus. Furthermore, water scarcity problems could be mitigated through optimization of the water resources utilization system. This study demonstrates that this new approach of SCC based on WCM could alleviate water resources scarcity problems in Xi'an Siyuan University effectively. It is hoped that this study will provide a model and example of the new approach for future applications.

Quantifying permeabilization and activity recovery of Bacillus spores in adverse conditions for growth.

Heat treatment is the main hurdle used to eliminate spores in foods but the pH conditions which spores encounter after the treatment have a tremendous impact on the spore ability to germinate, outgrow and grow. The aim of this work was to discriminate the inactive permeable spores and the active spores in unfavorable acidic conditions, after a heat treatment. In this study, Bacillus weihenstephanensis KBAB4 was used as model micro-organism for psychrotrophic Bacillus. The spores were heat treated to inactivate 90% of the population, 12 min at 85 °C, or 2 min at 95 °C. After each treatment the spores were incubated at pH 5.50 or pH 7.40. The evolution of dormant spores, permeable spores, germinated and vegetative cells was monitored by flow cytometry using a double staining. LDS 751, stains in red all the permeable cells, and CFDA stains in green cells presenting an esterase activity. Dormant spores did not show neither red fluorescence nor green fluorescence. Permeabilized spores which did not recover metabolic activity were red fluorescent but not green fluorescent. Germinated spores (permeabilized and having an esterase activity) appeared red fluorescent and green fluorescent due to their permeability and their metabolic activity. This method allowed the differentiation of the impact of heat treatment and post-treatment incubation pH on the two first steps of germination: spore permeabilization and activity recovery. Having a better understanding of spore germination at unfavorable post-treatment pH allows a better control of spore forming bacteria in foods.

Prognostic significance of genetic biomarkers in isocitrate dehydrogenase-wild-type lower-grade glioma: the need to further stratify this tumor entity - a meta-analysis.

The clinical outcomes of isocitrate dehydrogenase-wild-type (IDH-wt) lower-grade glioma (LGG) have been the subject of debate for some time. In this meta-analysis, we aimed to assess the prognostic values of several known genetic markers (e.g. TERT promoter mutation, H3F3A mutation, CDKN2A loss) in this tumor group. Four electronic databases, including PubMed, Scopus, Web of Science and Virtual Health Library, were searched for relevant articles. Pooled hazard ratio (HR) and corresponding 95% confidence interval (CI) for overall survival were calculated using a random-effect model weighted by an inverse variance method. A total of 11 studies were finally selected from 2274 articles for meta-analyses. Several genetic alterations were demonstrated to have a negative impact on prognosis of IDH-wt LGGs, specifically TERT promoter mutation (HR, 1.96; 95% CI, 1.42-2.70), H3F3A mutation (HR, 3.21; 95% CI, 1.86-5.55) and EGFR amplification (HR, 1.67; 95% CI, 1.02-2.74). However, CDKN loss, ATRX mutation and coexisting gain of chromosome 7/loss of chromosome 10 showed no clinical significance in this glioma entity. Our study results demonstrated that IDH-wt LGGs are heterogeneous in clinical outcome and not all tumors have a poor prognosis. The presence of TERT promoter mutation, H3F3A mutation and EGFR amplification showed negative prognostic impacts in this tumor entity. These genetic events can be used to better stratify patient outcomes.

Microalgae biomass from swine wastewater and its conversion to bioenergy.

Ever-increasing swine wastewater (SW) has become a serious environmental concern. High levels of nutrients and toxic contaminants in SW significantly impact on the ecosystem and public health. On the other hand, swine wastewater is considered as valuable water and nutrient source for microalgae cultivation. The potential for converting the nutrients from SW into valuable biomass and then generating bioenergy from it has drawn increasing attention. For this reason, this review comprehensively discussed the biomass production, SW treatment efficiencies, and bioenergy generation potentials through cultivating microalgae in SW. Microalgae species grow well in SW with large amounts of biomass being produced, despite the impact of various parameters (e.g., nutrients and toxicants levels, cultivation conditions, and bacteria in SW). Pollutants in SW can effectively be removed by harvesting microalgae from SW, and the harvested microalgae biomass elicits high potential for conversion to valuable bioenergy.

Rapid Nanophotonics Assay for Head and Neck Cancer Diagnosis.

Efficient and timely diagnosis of head and neck squamous cell carcinoma (HNSCC) is a critical challenge, particularly in low and middle income countries. These regions, which are expected to witness a drastic increase in HNSCC rates, are ill-prepared to handle the diagnostic burden due to limited resources, especially the low ratio of pathologists per population, resulting in delayed diagnosis and treatment. Here, we demonstrate the potential of an alternative diagnostic method as a low-cost, resource-efficient alternative to histopathological analysis. Our novel technology employs unique surface-enhanced Raman scattering (SERS) "nanorattles" targeting cytokeratin nucleic acid biomarkers specific for HNSCC. In this first study using SERS diagnostics for head and neck cancers, we tested the diagnostic accuracy of our assay using patient tissue samples. In a blinded trial, our technique demonstrated a sensitivity of 100% and specificity of 89%, supporting its use as a useful alternative to histopathological diagnosis. The implications of our method are vast and significant in the setting of global health. Our method can provide a rapid diagnosis, allowing for earlier treatment before the onset of distant metastases. In comparison to histopathology, which can take several months in remote limited-resources regions, our method provides a diagnosis within a few hours.

Author Correction: Rapid Nanophotonics Assay for Head and Neck Cancer Diagnosis.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors.

A comprehensive mathematical model was constructed to evaluate the complex substrate and microbial interaction in algal-bacterial photo sequencing batch reactors (PSBR). The kinetics of metabolite, growth and endogenous respiration of ammonia oxidizing bacteria, nitrite oxidizing bacteria and heterotrophic bacteria were coupled to those of microalgae and then embedded into widely-used activated sludge model series. The impact of light intensity was considered for microalgae growth, while the effect of inorganic carbon was considered for each microorganism. The integrated model framework was assessed using experimental data from algal-bacterial consortia performing sidestream nitritation/denitritation. The validity of the model was further evaluated based on dataset from PSBR performing mainstream nitrification. The developed model could satisfactorily capture the dynamics of microbial populations and substrates under different operational conditions (i.e. feeding, carbon dosing and illuminating mode, light intensity, influent ammonium concentration), which might serve as a powerful tool for optimizing the novel algal-bacterial nitrogen removal processes.

A hybrid constructed wetland for organic-material and nutrient removal from sewage: Process performance and multi-kinetic models.

A pilot-scale hybrid constructed wetland with vertical flow and horizontal flow in series was constructed and used to investigate organic material and nutrient removal rate constants for wastewater treatment and establish a practical predictive model for use. For this purpose, the performance of multiple parameters was statistically evaluated during the process and predictive models were suggested. The measurement of the kinetic rate constant was based on the use of the first-order derivation and Monod kinetic derivation (Monod) paired with a plug flow reactor (PFR) and a continuously stirred tank reactor (CSTR). Both the Lindeman, Merenda, and Gold (LMG) analysis and Bayesian model averaging (BMA) method were employed for identifying the relative importance of variables and their optimal multiple regression (MR). The results showed that the first-order-PFR (M2) model did not fit the data (P > 0.05, and R2 < 0.5), whereas the first-order-CSTR (M1) model for the chemical oxygen demand (CODCr) and Monod-CSTR (M3) model for the CODCr and ammonium nitrogen (NH4-N) showed a high correlation with the experimental data (R2 > 0.5). The pollutant removal rates in the case of M1 were 0.19 m/d (CODCr) and those for M3 were 25.2 g/m2∙d for CODCr and 2.63 g/m2∙d for NH4-N. By applying a multi-variable linear regression method, the optimal empirical models were established for predicting the final effluent concentration of five days' biochemical oxygen demand (BOD5) and NH4-N. In general, the hydraulic loading rate was considered an important variable having a high value of relative importance, which appeared in all the optimal predictive models.

Challenges in the application of microbial fuel cells to wastewater treatment and energy production: A mini review.

Wastewater is now considered to be a vital reusable source of water reuse and saving energy. However, current wastewater has multiple limitations such as high energy costs, large quantities of residuals being generated and lacking in potential resources. Recently, great attention has been paid to microbial fuel cells (MFCs) due to their mild operating conditions where a variety of biodegradable substrates can serve as fuel. MFCs can be used in wastewater treatment facilities to break down organic matter, and they have also been analysed for application as a biosensor such as a sensor for biological oxygen which demands monitoring. MFCs represent an innovation technology solution that is simple and rapid. Despite the advantages of this technology, there are still practical barriers to consider including low electricity production, current instability, high internal resistance and costly materials used. Thus, many problems must be overcome and doing this requires a more detailed analysis of energy production, consumption, and application. Currently, real-world applications of MFCs are limited due to their low power density level of only several thousand mW/m2. Efforts are being made to improve the performance and reduce the construction and operating costs of MFCs. This paper explores several aspects of MFCs such as anode, cathode and membrane, and in an effort to overcome the practical challenges of this system.

Problematic effects of antibiotics on anaerobic treatment of swine wastewater.

Swine wastewaters with high levels of organic pollutants and antibiotics have become serious environmental concerns. Anaerobic technology is a feasible option for swine wastewater treatment due to its advantage in low costs and bioenergy production. However, antibiotics in swine wastewater have problematic effects on micro-organisms, and the stability and performance of anaerobic processes. Thus, this paper critically reviews impacts of antibiotics on pH, COD removal efficiencies, biogas and methane productions as well as the accumulation of volatile fatty acids (VFAs) in the anaerobic processes. Meanwhile, impacts on the structure of bacteria and methanogens in anaerobic processes are also discussed comprehensively. Furthermore, to better understand the effect of antibiotics on anaerobic processes, detailed information about antimicrobial mechanisms of antibiotics and microbial functions in anaerobic processes is also summarized. Future research on deeper knowledge of the effect of antibiotics on anaerobic processes are suggested to reduce their adverse environmental impacts.