Unveiling the characteristics of free-living and particle-associated antibiotic resistance genes associated with bacterial communities along different processes in a full-scale drinking water treatment plant.

Antibiotic resistance genes (ARGs) as emerging contaminants, often co-occur with mobile genetic elements (MGEs) and are prevalent in drinking water treatment plants (DWTPs). In this study, the characteristics of free-living (FL) and particle-associated (PA) ARGs associated with bacterial communities were investigated along two processes within a full-scale DWTP. A total of 13 ARGs and two MGEs were detected. FL-ARGs with diverse subtypes and PA-ARGs with high abundances displayed significantly different structures. PA-MGEs showed a strong positive correlation with PA-ARGs. Chlorine dioxide disinfection achieved 1.47-log reduction of FL-MGEs in process A and 0.24-log reduction of PA-MGEs in process B. Notably, PA-fraction virtually disappeared after treatment, while blaTEM, sul2, mexE, mexF and IntI1 of FL-fraction remained in the finished water. Moreover, Acinetobacter lwoffii (0.04 % ∼ 45.58 %) and Acinetobacter schindleri (0.00 % ∼ 18.54 %) dominated the 16 pathogens, which were more abundant in FL than PA bacterial communities. PA bacteria exhibited a more complex structure with more keystone species than FL bacteria. MGEs contributed 20.23 % and 19.31 % to the changes of FL-ARGs and PA-ARGs respectively, and water quality was a key driver (21.73 %) for PA-ARGs variation. This study provides novel insights into microbial risk control associated with size-fractionated ARGs in drinking water.

Digitalization of phosphorous removal process in biological wastewater treatment systems: Challenges, and way forward.

Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.

Effective Charge Collection of Electron Transport Layers for High-Performance Quantum Dot Infrared Solar Cells.

Infrared (IR) solar cells, capable of converting low-energy IR photons to electron-hole pairs, are promising optoelectronic devices by broadening the utilization range of the solar spectrum to the short-wavelength IR region. The emerging PbS colloidal quantum dot (QD) IR solar cells attract much attention due to their tunable band gaps in the IR region, potential multiple exciton generation, and facile solution processing. In PbS QD solar cells, ZnO is commonly utilized as an electron transport layer (ETL) to establish a depleted heterostructure with a QD photoactive layer. However, band gap shrinkage of large PbS QDs makes it necessary to tailor the behaviors of the ZnO ETL for efficient carrier extraction in the devices. Herein, the characteristics of ZnO ETL are efficiently and flexibly tailored to match the QD layer by handily adjusting the postannealing process of ZnO ETL. With a suitable temperature, the well-matched energy level alignment and suppressed trap states are simultaneously achieved in the ZnO ETL, effectively reducing the nonradiative recombination and accelerating the electron injection from the QD layer to ETL. As a consequence, a high-performance PbS QD photovoltaic device with power conversion efficiencies (PCEs) of 10.09% and 1.37% is obtained under AM 1.5 and 1100 nm filtered solar illumination, demonstrating a simple and effective approach for achieving high-performance IR photoelectric devices.

An exploration of organizational climate in community-based opiate prescribing services; a mixed methods study.

INTRODUCTION: Assessing the internal dynamics of organizations has been shown to provide information that can help planners and policymakers improve service delivery. A good organizational climate, which in this study incorporates mission clarity, team cohesion, staff autonomy, communication, levels of stress, and openness to change has been shown to be of particular importance. Still, there is a dearth of evidence in this area, and while relationships between organizational factors have been identified, little is known about the mechanisms that might underpin these relationships, and there is little understanding of how to address deficits once they are identified. The objective of this study was to identify relationships between program factors that influence organizational climate and to explore which mechanisms might underpin these relationships. METHODS: This paper reports on a cross-sectional, concurrent, mixed-methods study design, across twelve discrete community-based prescribing service providers (organizations) in Ireland. Data was obtained using a staff survey [n = 132] which utilized measurements of organizational readiness to change and one-to-one interviews [n = 12]. Quantitative data was analyzed using multivariate linear regression modeling which assessed relationships between variables, while interviews were analyzed using an abductive approach, both types of data were synthesized at the interpretation stage. RESULTS: A range of interdependent factors were considered to affect the climate of organizations. Surveys identified that specific types of resources, such as physical infrastructure, training, and staffing resources were important for supporting a good organizational climate, while programs with greater needs had a poorer climate. Opportunities for professional growth, the skill sets of staff, and having access to e-communication were also significant. Interviewees reported that rigid organizational hierarchies and bureaucracy, philosophical views of addiction, stress, and staff turnover were influenced by the provision of fewer resources. Interdependent factors such as leadership, supervision, staff relationships, and collective training, also thought to be influenced by resources, were considered to positively influence programs. Resources were not the only challenge identified, and practices within programs and how existing resources are used were also thought to contribute both positively and negatively to the internal dynamics of services. CONCLUSION: Key findings in this study identified that the organization of effective services is influenced by a range of specific factors, some of which can be addressed without additional resources. Overall, staff views of organizations can provide us with valuable information to support service improvement. Using a mixed methods approach can not only identify where relationships between organizational variables exist but can also help us to understand the mechanisms that underpin these relationships and, importantly, how to address deficits once they are identified. In order to improve how substance misuse services work, the need for a long-term systemic approach to program development, which incorporates some of the findings from this study, is required.

Examining domains of psychological flexibility and inflexibility as treatment mechanisms in acceptance and commitment therapy: A comprehensive systematic and meta-analytic review.

The current systematic and meta-analytic review sought to integrate a growing number of studies examining dimensions of psychological flexibility as treatment mechanisms for Acceptance and Commitment Therapy (ACT). Analyses of 77 records (67 unique studies; Ntotal = 9123 participants) from comprehensive searches of multiple databases suggested that ACT interventions led to reduced inflexibility (i.e., lowered global inflexibility, lack of present moment awareness, cognitive fusion, experiential avoidance, self-as-content, & inaction) and increased flexibility (i.e., committed action/contact with values, global flexibility/acceptance, & defusion). Those changes remained significant when ACT was compared with waitlist or active treatments and were significantly linked to corresponding drops in psychological distress, supporting their roles as ACT treatment mechanisms. Moderation analyses revealed that the use of student samples, exclusion of clinically symptomatic individuals, and comparisons of ACT with other active treatments weakened these effects whereas offering ACT as an individual therapy and excluding individuals in extreme crisis (i.e., with suicidal ideation) strengthened them. The meta-analytic findings and systematic review suggested specific recommendations for future clinical work and research on ACT mechanisms: (1) Evaluate both psychological flexibility and inflexibility as distinct treatment mechanisms, (2) Evaluate specific dimensions of psychological flexibility/inflexibility as mechanisms with multidimensional scales (CompACT, MPFI), (3) Broaden treatment outcomes to include forms of wellbeing (peace of mind, vitality, connectedness), (4) Assess mechanisms and outcomes repeatedly throughout treatment to model the process of therapeutic change, (5) Investigate non-specific factors (therapeutic alliance, treatment adherence) as mechanisms, and (6) Explore treatment mechanisms in effectiveness studies.

Phages in sludge from the A/O wastewater treatment process play an important role in the transmission of ARGs.

Phages can influence the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs) through transduction, but their profiles and effects on the transmission of ARGs are unclear, especially in complex swine sludge. In this study, we investigated the characterization of phage and ARG profiles in sludge generated from anoxic/oxic (A/O) wastewater treatment processes on swine farms using metagenomes and viromes. The results demonstrated that 205-221 subtypes of ARGs could be identified in swine sludge, among which sul1, tet(M), and floR were the dominant ARGs, indicating that sludge is an important reservoir of ARGs, especially in sludge (S) tanks. The greater abundance of mobile genetic elements (MGEs) in the S tank could significantly contribute to the greater abundance of ARGs there compared to the anoxic (A) and oxic (O) tanks (P < 0.05). However, when we compared the abundances of ARGs and MGEs in the A and O tanks, we observed opposite significant differences (P < 0.05), suggesting that MGEs are not the only factor influencing the abundance of ARGs. The high proportion of lysogenic phages in sludge from the S tank can also have a major impact on the ARG profile. Siphoviridae, Myoviridae, and Podoviridae were the dominant phage families in sludge, and a network diagram of bacteria-ARG-phages revealed that dominant phages and bacteria acted simultaneously as potential hosts for ARGs, which may have led to phage-mediated HGT of ARGs. Therefore, the risk of phage-mediated HGT of ARGs cannot be overlooked.

Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities.

In water treatment processes (WTPs), artificial intelligence (AI) based techniques, particularly machine learning (ML) models have been increasingly applied in decision-making activities, process control and optimization, and cost management. At least 91 peer-reviewed articles published since 1997 reported the application of AI techniques to coagulation/flocculation (41), membrane filtration (21), disinfection byproducts (DBPs) formation (13), adsorption (16) and other operational management in WTPs. In this paper, these publications were reviewed with the goal of assessing the development and applications of AI techniques in WTPs and determining their limitations and areas for improvement. The applications of the AI techniques have improved the predictive capabilities of coagulant dosages, membrane flux, rejection and fouling, disinfection byproducts (DBPs) formation and pollutants' removal for the WTPs. The deep learning (DL) technology showed excellent extraction capabilities for features and data mining ability, which can develop an image recognition-based DL framework to establish the relationship among the shapes of flocs and dosages of coagulant. Further, the hybrid techniques (e.g., combination of regression and AI; physical/kinetics and AI) have shown better predictive performances. The future research directions to achieve better control for WTPs through improving these techniques were also emphasized.

Aging and mitigation of microplastics during sewage sludge treatments: An overview.

Wastewater treatment plants (WWTPs) receive large quantities of microplastics (MPs) from raw wastewater, but many MPs are trapped in the sludge. Land application of sludge is a significant source of MP pollution. Existing reviews have summarized the analysis methods of MPs in sludge and the effect of MPs on sludge treatments. However, MP aging and mitigation during sludge treatment processes are not fully reviewed. Treatment processes used to remove water, pathogenic microorganisms, and other pollutants in sewage sludge also cause surface changes and degradation in the sludge MPs, affecting the potential risk of MPs. This study integrates MP abundance and distribution in sludge and their aging and mitigation characteristics during sludge treatment processes. The abundance, composition, and distribution of sludge MPs vary significantly with WWTPs. Furthermore, MPs exhibit variable degrees of aging, including rough surfaces, enhanced adsorption potentials for pollutants, and increased leaching behavior. Various sludge treatment processes further intensify these aging characteristics. Some sludge treatments, such as hydrothermal treatment, have efficiently removed MPs from sewage sludge. It is crucial to understand the potential risk of MP aging in sludge and the degradation properties of the MP-derived products from MP degradation in-depth and develop novel MP mitigation strategies in sludge, such as combining hydrothermal treatment and biological processes.

Occurrence, fate, and ecological risk of antibiotics in wastewater treatment plants in China: A review.

This review offers a comprehensive overview of the occurrence, fate, and ecological risk associated with six major categories of antibiotics found in influent, effluent, and sludge from urban wastewater treatment plants (WWTPs) in China. Further exploration includes examining the correlation between antibiotic residual rates in the effluents and process parameters of urban WWTPs across the country. Lastly, a nationwide and urban cluster-specific evaluation of the ecological risk posed by antibiotics in WWTPs is conducted. The findings reveal that the average concentrations of antibiotics in influent, effluent, and sludge from urban WWTPs in China are 786.2 ng/L, 311.2 ng/L, and 186.8 µg/kg, respectively. Among the detected antibiotics, 42% exhibit moderate to high ecological risk in the effluent, with ciprofloxacin, sulfamethoxazole, erythromycin, azithromycin, and tetracycline posing moderate to high ecological risks in sludge. The current biological treatment processes in WWTPs demonstrate inefficacy in removing antibiotics. Hence, there is a pressing need to develop and integrate innovative technologies, such as advanced oxidation processes. This review aims to offer a more comprehensive understanding and identify priority antibiotics for control to effectively manage antibiotic pollution within WWTPs at both national and regional levels.

Chemical-toxicological insights and process comparison for estrogenic activity mitigation in municipal wastewater treatment plants.

Efforts in water ecosystem conservation require an understanding of causative factors and removal efficacies associated with mixture toxicity during wastewater treatment. This study conducts a comprehensive investigation into the interplay between wastewater estrogenic activity and 30 estrogen-like endocrine disrupting chemicals (EEDCs) across 12 municipal wastewater treatment plants (WWTPs) spanning four seasons in China. Results reveal substantial estrogenic activity in all WWTPs and potential endocrine-disrupting risks in over 37.5 % of final effluent samples, with heightened effects during colder seasons. While phthalates are the predominant EEDCs (concentrations ranging from 86.39 %) for both estrogenic activity and major EEDCs (phthalates and estrogens), with the secondary and tertiary treatment segments contributing 88.59 ± 8.12 % and 11.41 ± 8.12 %, respectively. Among various secondary treatment processes, the anaerobic/anoxic/oxic-membrane bioreactor (A/A/O-MBR) excels in removing both estrogenic activity and EEDCs. In tertiary treatment, removal efficiencies increase with the inclusion of components involving physical, chemical, and biological removal principles. Furthermore, correlation and multiple liner regression analysis establish a significant (p < 0.05) positive association between solid retention time (SRT) and removal efficiencies of estrogenic activity and EEDCs within WWTPs. This study provides valuable insights from the perspective of prioritizing key pollutants, the necessity of integrating more efficient secondary and tertiary treatment processes, along with adjustments to operational parameters like SRT, to mitigate estrogenic activity in municipal WWTPs. This contribution aids in managing endocrine-disrupting risks in wastewater as part of ecological conservation efforts.

Occurrence and fate of microplastics from a water source to two different drinking water treatment plants in a megacity in eastern China.

The widespread presence of microplastics (MPs) contamination in drinking water has raised concerns regarding water safety and public health. In this study, a micro-Raman spectrometer was used to trace the occurrence of MP transport from a water source to a drinking water treatment plant (DWTP)1 with an advanced treatment process and DWTP2 with a conventional treatment process and the contributions of different processes to the risk reduction of MPs were explored. Six types of MPs were detected: polyethylene terephthalate, polyethylene, polypropylene, polystyrene, polyamide, and polyvinyl chloride. 2-5 µm (35.8-41.2%) and polyethylene terephthalate (27.1-29.9%) were the most frequently detected MP sizes and types of water source samples, respectively. The abundance of MPs in treated water decreased by 72.7-83.0% compared to raw water. Ozonation and granular activated carbon (52.7%), and sand filtration (47.5%) were the most effective processes for removing MPs from DWTP1 and DWTP2, respectively. Both DWTPs showed significant removal effects on polyethylene terephthalate, with 80.0-88.1% removal rates. The concentrations of polystyrene increase by 30.0-53.4% after chlorination. The dominant components in the treated water of DWTP1 and DWTP2 were polypropylene (24.7%) and polyethylene 27.7%, respectively, and MPs of 2-5 µm had the highest proportion (55.3-64.3%). Pollution load index and potential ecological risk index of raw water treated by DWTPs were reduced by 48.0-58.7% and 94.5-94.7%, respectively. The estimated daily intake of MPs in treated water for infants was 45.5-75.0 items/kg/d, respectively, approximately twice that of adults. This study contributes to the knowledge gap regarding MP pollution in drinking water systems.

Short-, long-read metagenome and virome reveal the profile of phage-mediated ARGs in anoxic-oxic processes for swine wastewater treatment.

Phages are among the most widely spread viruses, but their profiles and the antibiotic resistance genes (ARGs) they carry in swine wastewater remain underexplored. The present study investigated the distribution characteristics of phages and their ARG risk in anoxic/oxic (A/O) wastewater treatment processes of swine farms using short- and long-read metagenome and virome. The results demonstrated that the virome could extract more phage sequences than the total metagenome; thus, it was more suited for studying phages in wastewater settings. Intriguingly, phages had significantly lower abundance of ARG than ARGs harbored by total microorganisms (P < 0.01). Eleven ARGs co-occurred with phages and bacteria (R > 0.6 and P < 0.05), with Siphoviridae being the phage co-occurring with the most ARGs (5). Horizontal gene transfer (HGT) events were observed between Proteobacteria and the major phyla except for Bacteroidota. Furthermore, there were prophage sequences and ARGs on the same contig in bacterial MAGs. These data strongly demonstrate that phages promote horizontal transfer of ARG between bacterial hosts in A/O processes for swine wastewater treatment. Therefore, the risk of phage-mediated horizontal transfer of ARGs cannot be overlooked despite the low abundance of phage ARGs (pARG).

Fate of contaminants of emerging concern in two wastewater treatment plants after retrofitting tertiary treatment for reduction of nitrogen discharge.

More and more previously designed wastewater treatment plants (WWTPs) are upgraded to tertiary treatment to meet the higher effluent discharge standards of conventional pollutants. Contaminants of emerging concern (CECs) can cause adverse effects on organisms and usually flow into WWTPs along with urban sewage. How the retrofitted WWTPs targeting conventional pollutants will influence the treatment efficiency of CECs is seldom discussed. This study investigates the removal of CECs in two full-scale newly retrofitted WWTPs (CD and JM WWTPs), containing high-efficiency sedimentation tank and denitrification deep bed filter for enhancing total nitrogen removal. The overall CEC removal efficiencies in the CD and JM WWTPs were 73.79 % and 93.63 %, respectively. Mass balance results indicated that CD WWTP and JM WWTP release a total of 36.89 and 88.58 g/d of CECs into the environment through effluent and excess sludge, respectively. Analysis of the concentration of CECs along the treatment process revealed most CECs were removed in the biological treatment units. The incorporation of newly constructed tertiary treatment proved beneficial for CEC removal and removed 2.93 % and 2.36 % CECs, corresponding to CEC removal of 2.92 and 27.49 g/d in the CD and JM WWTPs, respectively. The data of this study were further used to evaluate the suitability of the SimpleTreat model for simulating the fate of CECs in WWTPs. The predicted fraction of CECs discharged through the biological treatment effluent were generally within ten-fold difference from the measured results, highlighting its potential for estimating CEC removal in WWTPs.

Impact of harmful algal bloom severity on bacterial communities in a full-scale biological filtration system for drinking water treatment.

The occurrence of harmful algal blooms (HABs) in freshwater environments has been expanded worldwide with growing frequency and severity. HABs can pose a threat to public water supplies, raising concerns about safety of treated water. Many studies have provided valuable information about the impacts of HABs and management strategies on the early-stage treatment processes (e.g., pre-oxidation and coagulation/flocculation) in conventional drinking water treatment plants (DWTPs). However, the potential effect of HAB-impacted water in the granular media filtration has not been well studied. Biologically-active filters (BAFs), which are used in drinking water treatment and rely largely on bacterial community interactions, have not been examined during HABs in full-scale DWTPs. In this study, we assessed the bacterial community structure of BAFs, functional profiles, assembly processes, and bio-interactions in the community during both severe and mild HABs. Our findings indicate that bacterial diversity in BAFs significantly decreases during severe HABs due to the predominance of bloom-associated bacteria (e.g., Spingopyxis, Porphyrobacter, and Sphingomonas). The excitation-emission matrix combined with parallel factor analysis (EEM-PARAFAC) confirmed that filter influent affected by the severe HAB contained a higher portion of protein-like substances than filter influent samples during a mild bloom. In addition, BAF community functions showed increases in metabolisms associated with intracellular algal organic matter (AOM), such as lipids and amino acids, during severe HABs. Further ecological process and network analyses revealed that severe HAB, accompanied by the abundance of bloom-associated taxa and increased nutrient availability, led to not only strong stochastic processes in the assembly process, but also a bacterial community with lower complexity in BAFs. Overall, this study provides deeper insights into BAF bacterial community structure, function, and assembly in response to HABs.

New insights into toxicity reduction and pollutants removal during typical treatment of papermaking wastewater.

Papermaking wastewater contained various of toxic and hazardous pollutants that pose significant threats to both the ecosystem and human health. Despite these risks, limited research has addressed the detoxification efficiency and mechanism involved in the typical process treatment of papermaking wastewater. In this study, the acute toxicity of papermaking wastewater after different treatment processes was assessed using luminousbacteria, zebrafish and Daphnia magna (D. magna). Meanwhile, the pollution parament of the corresponding wastewater were measured, and the transformation of organic pollutant in the wastewater was identified by three-dimensional fluorescence and other techniques. Finally, the possible mechanism of toxicity variation in different treatment processes were explored in combination with correlation analyses. The results showed that raw papermaking wastewater displayed high acute toxicity to luminousbacteria, and exhibited slight acute toxicity and acute toxicity effect to zebrafish and D. magna, respectively. After physical and biochemical processes, not only the toxicity of the wastewater to zebrafish and D. magna was completely eliminated, but also the inhibitory effect on luminousbacteria was significantly reduced (TU value decreased from 11.07 to 1.66). Among them, the order of detoxification efficiency on luminousbacteria was air flotation > hydrolysis acidification > IC > aerobic process. Correlation analyses revealed a direct link between the reduced of Total Organic Carbon (TOC) and Chemical Oxygen Demand (COD) and the detoxification efficiency of the different processes on the wastewater. In particular, the removal of benzene-containing aromatic pollutant correlated positively with decreased toxicity. However, the Fenton process, despite lowering TOC and COD, increased of the acute toxicity of the luminousbacteria (TU value increased from 1.66 to 2.33). This may result from the transformation generation of organic pollutant and oxidant residues during the Fenton process. Hence, oxidation technologies such as the Fenton process, as a deep treatment process, should be more concerned about the ecological risks that may be caused while focusing on their effectiveness in removing pollutant.

Top-Down Exfoliation Process Constructing 2D/3D Heterojunction toward Ultrapure Blue Perovskite Light-Emitting Diodes.

3D perovskites with low energy disorder and high ambipolar charge mobility represent a promising solution for efficient and bright light-emitting diodes. However, the challenges of regulating the nanocrystal size to trigger the quantum confinement effect and control the surface trap states to reduce charge loss hinder the applications of 3D perovskites in blue perovskite light-emitting diodes (PeLEDs). In this study, we present a top-down exfoliation method to obtain blue 3D perovskite films with clipped nanocrystals and tunable bandgaps by employing methyl cyanide (MeCN) for post-treatment. In this method, the MeCN solvent exfoliates the surface components of the 3D perovskite grains through a partial dissolution process. Moreover, the dissolved precursor can be further utilized to construct an ingenious 2D/3D heterostructure by incorporating an organic spacer into the MeCN solvent, contributing to efficient defect passivation and improved energy transfer. Consequently, efficient PeLEDs featuring ultrapure blue emission at 478 nm achieve a record external quantum efficiency of 12.3% among their 3D counterparts. This work emphasizes the significance of inducing the quantum confinement effect in 3D perovskites for efficient blue PeLEDs and provides a viable scheme for the in situ regulation of perovskite crystals.

Research on Patients’ Trust Risk Points and Promotion Path from the Perspective of Online Health Community / 中国医学伦理学

Online health community is a new medical treatment mode combining the Internet and medical treatment. Patients can get medical services through the network. However, it cannot be ignored that patients’ trust will be affected by the uncertainty of online medical information, the unsafe factors of patients’ private information, the insufficient standardization of the diagnosis and treatment process, and other issue in the process of using this new medical treatment mode. By taking measures such as improving the information quality in online health community, enhancing patients’ cognitive ability of health information, perfecting privacy protection measures in online health community, advancing patients’ participation in online health community and ensuring the standardization of diagnosis and treatment process, patients’ trust can be improved.

Application of failure mode and effect analysis in ICU admission of potentially COVID-19 infected patients.

BACKGROUND: To analyze the admission and treatment process of potentially COVID-19-infected patients in the intensive care unit under normalization, prevention, and control of the pandemic. METHODS: A multidisciplinary team was assembled to develop a flowchart of potentially COVID-19-infected patients admitted to the intensive care unit and identify potential failure steps and modes throughout the process using the failure mode and effect analysis method. Through risk priority number (RPN) analysis of each failure mode, those with the highest impact on nosocomial infection were identified, and the priority of implementation was determined. Related corrective measures have been developed to continuously improve clinical practice and management. RESULTS: Eighty potential failure modes were identified, and 8 potential failure modes were identified with RPNs greater than 100. These high RPNs of the failure modes were associated with careless inquiries of epidemiological histories by nurses, inadequate implementation of management standards by nursing assistants, and exposure of attending physicians to potentially risky environments. Finally, 18 general corrective measures are proposed. CONCLUSIONS: Application of the failure mode and effect analysis method for quality improvement is a powerful tool for predicting potential failures in the process and can suggest corrective measures that could help avoid nosocomial infection during a pandemic.

Biotoxicity dynamic change and key toxic organics identification of coal chemical wastewater along a novel full-scale treatment process.

It is particularly important to comprehensively assess the biotoxicity variation of industrial wastewater along the treatment process for ensuring the water environment security. However, intensive studies on the biotoxicity reduction of industrial wastewater are still limited. In this study, the toxic organics removal and biotoxicity reduction of coal chemical wastewater (CCW) along a novel full-scale treatment process based on the pretreatment process-anaerobic process-biological enhanced (BE) process-anoxic/oxic (A/O) process-advanced treatment process was evaluated. This process performed great removal efficiency of COD, total phenol, NH4+-N and total nitrogen. And the biotoxicity variation along the treatment units was analyzed from the perspective of acute biotoxicity, genotixicity and oxidative damage. The results indicated that the effluent of pretreatment process presented relatively high acute biotoxicity to Tetrahymena thermophila. But the acute biotoxicity was significantly reduced in BE-A/O process. And the genotoxicity and oxidative damage to Tetrahymena thermophila were significantly decreased after advanced treatment. The polar organics in CCW were identified as the main biotoxicity contributors. Phenols were positively correlated with acute biotoxicity, while the nitrogenous heterocyclic compounds and polycyclic aromatic hydrocarbons were positively correlated with genotoxicity. Although the biotoxicity was effectively reduced in the novel full-scale treatment process, the effluent still performed potential biotoxicity, which need to be further explored in order to reduce environmental risk.

Self-Monitoring Theranostic Nanomaterials: Emerging Visual Agents for Real-Time Monitoring of Tumor Treatment Processes.

Self-monitoring in tumor therapy is a concept that allows for real-time monitoring of the location and state of applied nanomaterials. This monitoring relies on dynamic signals, such as wave or magnetic signals, which vary in response to changes in the location and state of nanomaterials. Dynamic changes in nanomaterials can be monitored using dynamic signals, making it possible to determine and control the treatment process. Theranostic nanomaterials, which possess unique physical and chemical properties, have recently been explored as a viable option for self-monitoring. With the help of self-monitoring, theranostic nanomaterials can guide themselves to achieve region-selective treatment with higher controllability and safety. In this review, self-monitoring theranostic nanomaterials will be introduced in three parts according to their roles during therapy: tumor accumulation, tumor therapy, and metabolism. The limitations and future challenges of current self-monitoring theranostic nanomaterials will also be discussed.