Vacancy-assisted exposed Sn atoms enhancing NO2 room temperature sensing of SnSe2 nanoflowers.

NO2 is a hazardous gas extremely harmful to the ecosystem and human health, so effective detection of NO2 is critical. SnSe2 is a promising candidate for gas sensors owing to its unique layered configuration that facilitates the diffusion of gas molecules. Here, ultrathin self-assembled nanoflowers F-SnSe2 rich in defects were synthesized by a simple solvothermal method. It exhibits excellent gas sensing performances for NO2 at room temperature (25 °C), with a high gas sensing response of 8.6 for 1 ppm NO2 and a lower detection limit as low as 200 ppb, capable of sensitively detecting ppb-level NO2. DFT calculations revealed that the presence of Se vacancies assists the central Sn atoms to break through the shielding effect of the surface Se atoms and become exposed active sites. The higher reactivity leads to more charge transfer and higher adsorption energy, which strongly promoted the adsorption of NO2. This work verifies the important role of vacancies for the exposed active sites and provides new guidance for defect engineering to modulate the gas sensing performances of SnSe2.

Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China.

Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.

Multiple physical crosslinked highly adhesive and conductive hydrogels for human motion and electrophysiological signal monitoring.

Hydrogel-based flexible electronic devices serve as a next-generation bridge for human-machine interaction and find extensive applications in clinical therapy, military equipment, and wearable devices. However, the mechanical mismatch between hydrogels and human tissues, coupled with the failure of conformal interfaces, hinders the transmission of information between living organisms and flexible devices, which resulted in the instability and low fidelity of signals, especially in the acquisition of electromyographic (EMG) and electrocardiographic (ECG) signals. In this study, we designed an ion-conductive hydrogel (ICHgel) utilizing multiple physical interactions, successfully applied for human motion monitoring and the collection of epidermal physiological signals. By incorporating fumed silica (F-SiO2) nanoparticles and calcium chloride into an interpenetrating network (IPN) composed of polyvinyl alcohol (PVA) and polyacrylamide (AAm)/acrylic acid (AA) chains, the ICHgel exhibited exceptional tunable stretchability (>1450% strain) and conductivity (10.58 ± 0.85 S m-1). Additionally, the outstanding adhesion of the ICHgel proved to be a critical factor for effective communication between epidermal tissues and flexible devices. Demonstrating its capability to acquire stable electromechanical signals, the ICHgel was attached to different parts of the human body. More importantly, as a flexible electrode, the ICHgel outperformed commercial Ag/AgCl electrodes in the collection of ECG and EMG signals. In summary, the synthesized ICHgel with its outstanding conformal interface capabilities and mechanical adaptability paves the way for enhanced human-machine interaction, fostering the development of flexible electronic devices.

Bimodal Intelligent Electronic Skin Based on Proximity and Tactile Interaction for Pressure and Configuration Perception.

The flexible bimodal e-skin exhibits significant promise for integration into the next iteration of human-computer interactions, owing to the integration of tactile and proximity perception. However, those challenges, such as low tactile sensitivity, complex fabrication processes, and incompatibility with bimodal interactions, have restricted the widespread adoption of bimodal e-skin. Herein, a bimodal capacitive e-skin capable of simultaneous tactile and proximity sensing has been developed. The entire process eliminates intricate fabrication techniques, employing DLP-3D printing for the electrode layers and sacrificial templating for the dielectric layers, conferring high tactile sensitivity (1.672 kPa-1) and rapid response capability (∼30 ms) to the bimodal e-skin. Moreover, exploiting the "fringing electric field" effect inherent in parallel-plate capacitors has facilitated touchless sensing, thereby enabling static distance recognition and dynamic gesture recognition of varying materials. Interestingly, an e-skin sensing array was created to identify the positions and pressure levels of various objects of different masses. Furthermore, with the aid of machine learning techniques, an artificial neural network has been established to possess intelligent object recognition capabilities, facilitating the identification, classification, and training of various object configurations. The advantages of the bimodal e-skin render it highly promising for extensive applications in the field of next-generation human-machine interaction.

["Load-Unload" Effect of Manganese Oxides on Phosphorus in Surface Water of the Pearl River Estuary].

Phosphorus (P) conveyed by surface runoff plays an essential role in regulating nutrient balance and primary production in estuarine waters. In this study, basic physiochemical properties, total phosphorus (TP, including speciation), particulate iron (PFe), particulate manganese (PMn), and particulate aluminum (PAl) of the surface water in the Pearl River Estuary (PRE) in different seasons were determined to investigate the spatiotemporal distribution characteristics of P and to identify the crucial factor controlling P migration and transformation in the freshwater-saltwater interaction zone. TP concentrations (28.88-233.68 µg·L-1) decreased with increasing salinity gradient owing to deposition and dilution. The proportions of P speciation followed a decreasing order as dissolved inorganic phosphorus (DIP, 37.3%) > particulate inorganic phosphorus (PIP, 22.7%) > dissolved organic phosphorus (DOP, 21.0%) > particulate organic phosphorus (POP, 19.0%). PIP was positively related to PFe, PMn, and PAl (P < 0.05), confirming their concurrent migration behaviors. In addition, the increase in salinity promoted the desorption of phosphate on the suspended particulate matters, which mainly took place near the freshwater-saltwater interface. A significant positive correlation (P < 0.001) between the solid-liquid phase partitioning coefficient (Kd) of phosphate and salinity indicated that PIP was present mainly in more stable forms in the brackish water. Most importantly, a better relationship between Kd and PMn (P < 0.01) supported our scientific hypothesis of the "load-unload" effect of Mn oxides on P:particulate-carrying phosphates transported from the freshwater zone tend to be desorbed and released into the brackish water.

Physiological responses and removal mechanisms of ciprofloxacin in freshwater microalgae.

Antibiotics, such as ciprofloxacin (CIP), are frequently detected in various environmental compartments, posing significant risks to ecosystems and human health. In this study, the physiological responses and elimination mechanisms of CIP in Chlorella sorokiniana and Scenedesmus dimorphus were determined. The exposure CIP had a minimal impact on the growth of microalgae, with maximum inhibit efficiency (IR) of 5.14% and 22.74 for C. sorokiniana and S. dimorphus, respectively. Notably, the photorespiration in S. dimorphus were enhanced. Both microalgae exhibited efficient CIP removal, predominantly through bioaccumulation and biodegradation processes. Intermediates involved in photolysis and biodegradation were analyzed through Liquid Chromatography High Resolution Mass Spectrometer (HPLC-MS/MS), providing insights into degradation pathways of CIP. Upregulation of key enzymes, such as dioxygenase, oxygenase and cytochrome P450, indicated their involvement in the biodegradation of CIP. These findings enhance our understanding of the physiological responses, removal mechanisms, and pathways of CIP in microalgae, facilitating the advancement of microalgae-based wastewater treatment approaches, particularly in antibiotic-contaminated environments.

Ce-Ag Active Bimetallic Pairs in Two-Dimensional SnS2 for Enhancing NO2 Sensing.

Developing gas sensors capable of efficiently detecting harmful gases is urgent to protect the human environment. Here, an active Ce-Ag bimetallic pair was innovatively introduced into SnS2, which successfully exhibited excellent NO2 gas sensing performance. 0.8% Ce-SnS2-Ag showed a gas sensing response of 5.18 to 1 ppm of NO2 at a low temperature of 80 °C, with a lower limit of detection as low as 100 ppb. DFT calculations revealed that Ce atoms are substituted into the main lattice of SnS2, which opens up the interlayer spacing and serves as an anchor point to fix the Ag atoms in the interlayer. The Ce-Ag bimetallic pairs successfully modulate the electronic structure of SnS2, which promotes the adsorption and charge transfer between NO2 and Ce-SnS2-Ag and thus achieves such an outstanding gas sensing performance. This work opens an avenue for the rational functional modification of SnS2 with an optimized electronic structure and enhanced gas sensing.

Microalgae cultivation with recycled harvesting water achieved economic and sustainable production of biomass and lipid: Feasibility assessment and inhibitory factors analysis.

This study was conducted to achieve economic and sustainable production of biomass and lipids from Chlorella sorokiniana by recirculating cultivation with recycled harvesting water, to identify the major inhibitory factors in recirculating culture, and to analyze accordingly economic benefits. The results showed that recirculating microalgae cultivation (RMC) could obtain 0.20-0.32 g/L biomass and lipid content increased by 23.1 %-38.5 %. Correlation analysis showed that the extracellular polysaccharide (PSext), chemical oxygen demand (COD) and chromaticity of recirculating water inhibited photosynthesis and induced oxidative stress, thus inhibiting the growth of C. sorokiniana. In addition, the economic benefits analysis found that circulating the medium twice could save about 30 % of production cost, which is the most economical RMC solution. In conclusion, this study verified the feasibility and economy of RMC, and provided a better understanding of inhibitory factors identification in culture.

Estimation of water quality variables based on machine learning model and cluster analysis-based empirical model using multi-source remote sensing data in inland reservoirs, South China.

Reservoirs play important roles in the drinking water supply for urban residents, agricultural water provision, and the maintenance of ecosystem health. Satellite optical remote sensing of water quality variables in medium and micro-sized inland waters under oligotrophic and mesotrophic status is challenging in terms of the spatio-temporal resolution, weather conditions and frequent nutrient status changes in reservoirs, etc., especially when quantifying non-optically active components (non-OACs). This study was based on the surface reflectance products of unmanned aerial vehicle (UAV) multispectral images, Sentinel-2B Multispectral instrument (MSI) images and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) by utilizing fuzzy C-means (FCM) clustering algorithm was combined with band combination (BC) model to construct the FCM-BC empirical model, and used mixed density network (MDN), extreme gradient boosting (XGBoost), deep neural network (DNN) and support vector regression (SVR) machine learning (ML) models to invert 12 kinds of optically active components (OACs) and non-OACs. Compared with the unclustered BC (UC) model, the mean coefficient of determination (MR) of the FCM-BC models was improved by at least 46.9%. MDN model showed best accuracy (R2 in the range of 0.60-0.98) and stability (R2 decreased by up to 13.2%). The accuracy of UAV was relatively higher in both empirical methods and machine learning methods. Additionally, the spatio-temporal distribution maps of four water quality variables were mapped based on the MDN model and UAV images, all platforms showed good consistency. An inversion strategy of water quality variables in various monitoring frequencies and weather conditions were proposed finally. The purpose of introducing the UAV platform was to cooperate with the satellite to improve the monitoring response ability of OACs and non-OACs in small and micro-sized oligotrophic and mesotrophic water bodies.

Urea addition as an enhanced strategy for degradation of petroleum contaminants during co-composting of straw and pig manure: Evidences from microbial community and enzyme activity evaluation.

Alterations in microbial community succession patterns and enzyme activities by petroleum pollutants during co-composting of straw and swine manure with the supplementary nitrogen source are unclear. In this study, urea was added into co-composting systems, and the removal performance of petroleum, microbial enzyme activity and community changes were investigated. Results showed that the polyphenol oxidase and catalase activities which were both related to the degradation of petroleum contaminants were accordingly increased from 20.65 to 30.31 U/g and from 171.87 to 231.86 U/g due to urea addition. The removal efficiency of petroleum contaminants in composting with urea increased from 45.06% to 82.29%. The addition of urea increased the diversity and abundance of petroleum-degrading microorganisms, and enhanced microbial linkages. This study provides a novel strategy for the degradation of petroleum hydrocarbon as well as a new insight into the effect of urea on both microbial processes and composting phases.

Physiological sensing system integrated with vibration sensor and frequency gel dampers inspired by spider.

Recent advances in bioelectronics in mechanical and electrophysiological signal detection are remarkable, but there are still limitations because they are inevitably affected by environmental noise and motion artifacts. Thus, we develop a gel damper-integrated crack sensor inspired by the vibration response of the viscoelastic cuticular pad and slit organs in a spider. Benefitting from the specific crack structure design, the sensor possesses excellent sensing behaviors, including a low detection limit (0.05% strain), ultrafast response ability (3.4 ms) and superior durability (>300 000 cycles). Such typical low-amplitude fast response properties allow the ability to accurately perceive vibration frequency and waveform. In addition, the gel damper exhibits frequency-dependent dynamic mechanical behavior that results in improved stability and reliability of signal acquisition by providing shock resistance and isolating external factors. They effectively attenuate external motion artifacts and low-frequency mechanical noise, resulting in cleaner and more reliable signal acquisition. When the gel damper is combined with the crack-based vibration sensor, the integrated sensor exhibits superior anti-interference capability and frequency selectivity, demonstrating its effectiveness in extracting genuine vocal vibration signals from raw voice recordings. The integration of damping materials with sensors offers an efficient approach to improving signal acquisition and signal quality in various applications.

Biochemical responses of freshwater microalgae Chlorella sorokiniana to combined exposure of Zn(â ¡) and estrone with simultaneous pollutants removal.

With the development of livestock industry, contaminants such as divalent zinc ions (Zn (Ⅱ)) and estrone are often simultaneously detected in livestock wastewater. Nevertheless, the combined toxicity of these two pollutants on microalgae is still unclear. Moreover, microalgae have the potential for biosorption and bioaccumulation of heavy metals and organic compounds. Thus, this study investigated the joint effects of Zn (Ⅱ) and estrone on microalgae Chlorella sorokiniana, in terms of growth, photosynthetic activity and biomolecules, as well as pollutants removal by algae. Interestingly, a low Zn (Ⅱ) concentration promoted C. sorokiniana growth and photosynthetic activity, while the high concentration experienced inhibition. As the increase of estrone concentration, chlorophyll a content increased continuously to resist the environmental stress. Concurrently, the secretion of extracellular polysaccharides and proteins by algae increased with exposure to Zn (Ⅱ) and estrone, reducing toxicity of pollutants to microalgae. Reactive oxygen species and superoxide dismutase activity increased as the increase of pollutant concentration after 96 h cultivation, but high pollutant concentrations resulted in damage of cells, as proved by increased MDA content. Additionally, C. sorokiniana displayed remarkable removal efficiency for Zn (Ⅱ) and estrone, reaching up to 86.14% and 84.96% respectively. The study provides insights into the biochemical responses of microalgae to pollutants and highlights the potential of microalgae in pollutants removal.

Self-Powered Integrated System with a Flexible Strain Sensor and a Zinc-Air Battery.

At present, self-powered, lightweight, and flexible sensors are widely applied, especially in the fields of wearable devices and human health monitoring. Nevertheless, conventional self-powered flexible sensor systems rely on power supply components such as supercapacitors, nanofriction generators, and solar cells, which present certain limitations, such as high dependence on external environmental factors and the inability to provide long-term stable energy supply. Thus, a paramount exigency emerges for the development of wearable sensors endowed with enduring battery life to enable continuous monitoring of human motion for extended periods. In our academic study, we present an innovative self-powered sensing system that seamlessly combines a pliable zinc-air battery with a strain sensor. This approach offers a stable output signal over extended periods without an external energy device, which is crucial for long-term, continuous human motion monitoring. Through the incorporation of various carbon materials, we realized the multifunction of poly(vinyl alcohol) (PVA)/poly(acrylic acid) (PAA) dual network hydrogels and prepared zinc-air battery electrolytes and strain sensors. Notably, the batteries exhibit impressive power density (82.5 mW cm-2), high open-circuit voltage (1.42 V), and remarkable environmental stability. Even when subjected to puncture and breakage, the batteries remain operational without suffering from electrolyte leakage. Similarly, our strain sensor boasts a broad working range spanning from 0 to 1400%, coupled with a remarkable sensitivity (GF = 2.99) and exceptional capacity to accurately detect various mechanical deformations. When integrated into a single system, the integrated system can monitor human movement for up to 10 h, which has broad prospects in wearable sensor applications.

Nitrogen-doped hollow mesoporous carbon spheres for efficient oxygen reduction.

Extensive investigations have been devoted to nitrogen-doped carbon materials as catalysts for the oxygen reduction reaction (ORR) in various conversion technologies. In this study, we introduce nitrogen-doped carbon materials with hollow spherical structures. These materials demonstrate significant potential in ORR activity within alkaline media, showing a half-wave potential of 0.87 V versus the reversible hydrogen electrode (RHE). Nitrogen-doped hollow carbon spheres (N-CHS) exhibit unique characteristics such as a thin carbon shell layer, hollow structure, large surface area, and distinct pore features. These features collectively create an optimal environment for facilitating the diffusion of reactants, thereby enhancing the exposure of active sites and improving catalytic performance. Building upon the promising qualities of N-CHS as a catalyst support, we employ heme chloride (1 wt%) as the source of iron for Fe doping. Through the carbonization process, Fe-N active sites are effectively formed, displaying a half-wave potential of 0.9 V versus RHE. Notably, when implemented as a cathode catalyst in zinc-air batteries, this catalyst exhibits an impressive power density of 162.6 mW cm-2.

A liquid-free conducting ionoelastomer for 3D printable multifunctional self-healing electronic skin with tactile sensing capabilities.

Conductive elastomers with both softness and conductivity are widely used in the field of flexible electronics. Nonetheless, conductive elastomers typically exhibit prominent problems such as solvent volatilization and leakage, and poor mechanical and conductive properties, which limit their applications in electronic skin (e-skin). In this work, a liquid-free conductive ionogel (LFCIg) with excellent performance was fabricated by utilizing the innovative double network design approach based on a deep eutectic solvent (DES). The double-network LFCIg is cross-linked by dynamic non-covalent bonds, which exhibit excellent mechanical properties (2100% strain while sustaining a fracture strength of 1.23 MPa) and >90% self-healing efficiency, and a superb electrical conductivity of 23.3 mS m-1 and 3D printability. Moreover, the conductive elastomer based on LFCIg has been developed into a stretchable strain sensor that achieves accurate response recognition, classification, and identification of different robot gestures. More impressively, an e-skin with tactile sensing functions is produced by in situ 3D printing of sensor arrays on flexible electrodes to detect light weight objects and recognize the resulting spatial pressure variations. Collectively, the results demonstrate that the designed LFCIg has unparalleled advantages and presents wide application potential in flexible robotics, e-skin and physiological signal monitoring.

Recent developments on BMPs and their antagonists in inflammatory bowel diseases.

Inflammatory bowel diseases (IBDs), including ulcerative colitis, and Crohn's disease, are intestinal disorders characterized by chronic relapsing inflammation. A large proportion of patients with IBD will progress to develop colitis-associated colorectal cancer due to the chronic intestinal inflammation. Biologic agents that target tumour necrosis factor-α, integrin α4ß7, and interleukin (IL)12/23p40 have been more successful than conventional therapies in treating IBD. However, drug intolerance and loss of response are serious drawbacks of current biologics, necessitating the development of novel drugs that target specific pathways in IBD pathogenesis. One promising group of candidate molecules are bone morphogenetic proteins (BMPs), members of the TGF-ß family involved in regulating morphogenesis, homeostasis, stemness, and inflammatory responses in the gastrointestinal tract. Also worth examining are BMP antagonists, major regulators of these proteins. Evidence has shown that BMPs (especially BMP4/6/7) and BMP antagonists (especially Gremlin1 and follistatin-like protein 1) play essential roles in IBD pathogenesis. In this review, we provide an updated overview on the involvement of BMPs and BMP antagonists in IBD pathogenesis and in regulating the fate of intestinal stem cells. We also described the expression patterns of BMPs and BMP antagonists along the intestinal crypt-villus axis. Lastly, we synthesized available research on negative regulators of BMP signalling. This review summarizes recent developments on BMPs and BMP antagonists in IBD pathogenesis, which provides novel insights into future therapeutic strategies.

A Novel Nomogram Combining Mucus Barrier Index for Predicting Treatment Failures in Ulcerative Colitis.

Background: Treatment failures (TFs) generally exist in the course of ulcerative colitis (UC), while early reliable predictors of TFs are still lacking. We aimed to generate nomograms for the prediction of TFs. Methods: In this retrospective case-control study, the endpoint was the occurrence of TFs, which included medically associated treatment failures and surgery-associated treatment failures (colectomy). Clinical features and mucus integrity evident by goblet cells (GCs) number, expression levels of MUC2 and SLC26A3 were enrolled in the univariate analysis. Nomogram performance was evaluated by discrimination and calibration. Results: We identified 256 UC patients at our center from January 2010 to June 2022. Fourteen variables for TFs and 9 for colectomy were identified by univariate analysis. Five baseline indices were incorporated into the nomogram for the prediction of TFs: area of GCs, age at diagnosis, disease duration, hemoglobin, and Mayo score. The model was presented with decent discrimination (C index of 0.822) and well calibration. In addition, the colectomy predictive nomogram was built using MUC2 intensity, age at onset, and Mayo score with a good discrimination (C index of 0.92). Conclusion: Nomograms based on comprehensive factors including mucus barrier function were developed to predict TFs in UC patients with great discrimination, which may serve as practical tools aiming to identify high-risk subgroups warrant timely intervention.

Tough and Robust Mechanically Interlocked Gel-Elastomer Hybrid Electrode for Soft Strain Gauge.

Soft strain gauges provide a flexible and versatile alternative to traditional rigid and inextensible gauges, overcoming issues such as impedance mismatch, the limited sensing range, and fatigue/fracture. Although several materials and structural designs are used to fabricate soft strain gauges, achieving multi-functionality for applications remains a significant challenge. Herein, a mechanically interlocked gel-elastomer hybrid material is exploited for soft strain gauge. Such a material design provides exceptional fracture energy of 59.6 kJ m-2 and a fatigue threshold of 3300 J m-2 , along with impressive strength and stretchability. The hybrid material electrode possesses excellent sensing performances under both static and dynamic loading conditions. It boasts a tiny detection limit of 0.05% strain, ultrafast time resolution of 0.495 ms, and high linearity. This hybrid material electrode can accurately detect full-range human-related frequency vibrations ranging from 0.5 to 1000 Hz, enabling the measurement of physiological parameters. Additionally, the patterned soft strain gauge, created through lithography, demonstrates superior signal-noise rate and electromechanical robustness against deformation. By integrating a multiple-channel device, an intelligent motion detection system is developed, which can classify six typical human body movements with the assistance of machine learning. This innovation is expected to drive advancements in wearable device technology.

Tough hydrogel with high water content and ordered fibrous structures as an artificial human ligament.

Natural biological tissues such as ligaments, due to their anisotropic across scale structure, have high water content, while still maintaining high strength and flexibility. Hydrogels are ideal artificial materials like human ligaments. However, conventional gel materials fail to exhibit high strength or fatigue resistance at high water content in human tissues. To address this challenge, we propose a simple integrated strategy to prepare an anisotropic hierarchical hydrogel architecture for artificial ligaments by combining freeze-casting assisted compression annealing and salting-out treatments. The hybrid polyvinyl alcohol hydrogels are of water content up to 79.5 wt%. Enhanced by the added carbon nanotubes, the hydrogels exhibit high strength of 4.5 MPa and a fatigue threshold of 1467 J m-2, as well as excellent stress sensitivity. The outstanding durability of the artificial ligament provides an all-around solution for biomedical applications.

Towards advanced nutrient removal by microalgae-bacteria symbiosis system for wastewater treatment.

In this study, the microalgae-bacteria symbiosis (ABS) system by co-culturing Chlorella sorokiniana with activated sludge was constructed for pollutants removal, and the according interaction mechanism was investigated. The results showed that the ABS system could almost completely remove ammonia nitrogen, and the removal efficiency of total nitrogen and total phosphorus could accordingly reach up to 65.3 % and 42.6 %. Brevundimonas greatly promoted microalgal biomass growth (maximum chlorophyll-a concentration of 9.4 mg/L), and microalgae contributed to the increase in the abundance of Dokdonella and Thermomonas in ABS system, thus facilitating nitrogen removal. The extended Derjaguin-Landau-Verwey-Overbeek theory indicated a repulsive potential barrier of 561.7 KT, while tryptophan-like proteins and tyrosine-like proteins were key extracellular polymeric substances for the formation of flocs by microalgae and activated sludge. These findings provide an in-depth understanding of interaction mechanism between microalgae and activated sludge for the removal of contaminants from wastewater.