Beyond water and soil: Air emerges as a major reservoir of human pathogens.

Assessing the risk of human pathogens in the environment is crucial for controlling the spread of diseases and safeguarding human health. However, conducting a thorough assessment of low-abundance pathogens in highly complex environmental microbial communities remains challenging. This study compiled a comprehensive catalog of 247 human-pathogenic bacterial taxa from global biosafety agencies and identified more than 78 million genome-specific markers (GSMs) from their 17,470 sequenced genomes. Subsequently, we analyzed these pathogens' types, abundance, and diversity within 474 shotgun metagenomic sequences obtained from diverse environmental sources. The results revealed that among the four habitats studied (air, water, soil, and sediment), the detection rate, diversity, and abundance of detectable pathogens in the air all exceeded those in the other three habitats. Air, sediment, and water environments exhibited identical dominant taxa, indicating that these human pathogens may have unique environmental vectors for their transmission or survival. Furthermore, we observed the impact of human activities on the environmental risk posed by these pathogens, where greater amounts of human activities significantly increased the abundance of human pathogenic bacteria, especially in water and air. These findings have remarkable implications for the environmental risk assessment of human pathogens, providing valuable insights into their presence and distribution across different habitats.

Spectral Embedding Fusion for Incomplete Multiview Clustering.

Incomplete multiview clustering (IMVC) aims to reveal the underlying structure of incomplete multiview data by partitioning data samples into clusters. Several graph-based methods exhibit a strong ability to explore high-order information among multiple views using low-rank tensor learning. However, spectral embedding fusion of multiple views is ignored in low-rank tensor learning. In addition, addressing missing instances or features is still an intractable problem for most existing IMVC methods. In this paper, we present a unified spectral embedding tensor learning (USETL) framework that integrates the spectral embedding fusion of multiple similarity graphs and spectral embedding tensor learning for IMVC. To remove redundant information from the original incomplete multiview data, spectral embedding fusion is performed by introducing spectral rotations at two different data levels, i.e., the spectral embedding feature level and the clustering indicator level. The aim of introducing spectral embedding tensor learning is to capture consistent and complementary information by seeking high-order correlations among multiple views. The strategy of removing missing instances is adopted to construct multiple similarity graphs for incomplete multiple views. Consequently, this strategy provides an intuitive and feasible way to construct multiple similarity graphs. Extensive experimental results on multiview datasets demonstrate the effectiveness of the two spectral embedding fusion methods within the USETL framework.

Inoculum source determines the stress resistance of electroactive functional taxa in biofilms: A metagenomic perspective.

The inoculum has a crucial impact on bioreactor initialization and performance. However, there is currently a lack of guidance on selecting appropriate inocula for applications in environmental biotechnology. In this study, we applied microbial electrolysis cells (MECs) as models to investigate the differences in the functional potential of electroactive microorganisms (EAMs) within anodic biofilms developed from four different inocula (natural or artificial), using shotgun metagenomic techniques. We specifically focused on extracellular electron transfer (EET) function and stress resistance, which affect the performance and stability of MECs. Community profiling revealed that the family Geobacteraceae was the key EAM taxon in all biofilms, with Geobacter as the dominant genus. The c-type cytochrome gene imcH showed universal importance for Geobacteraceae EET and was utilized as a marker gene to evaluate the EET potential of EAMs. Additionally, stress response functional genes were used to assess the stress resistance potential of Geobacter species. Comparative analysis of imcH gene abundance revealed that EAMs with comparable overall EET potential could be enriched from artificial and natural inocula (P > 0.05). However, quantification of stress response gene copy numbers in the genomes demonstrated that EAMs originating from natural inocula possessed superior stress resistance potential (196 vs. 163). Overall, this study provides novel perspectives on the inoculum effect in bioreactors and offers theoretical guidance for selecting inoculum in environmental engineering applications.

1H-nuclear magnetic resonance analysis reveals dynamic changes in the metabolic profile of patients with severe burns.

Background: Severe burn injury causes a hypermetabolic response, resulting in muscle protein catabolism and multiple organ damage syndrome. However, this response has not yet been continuously characterized by metabolomics in patients. This study aims to quantify temporal changes in the metabolic processes of patients with severe burns. Methods: We employed 1H-nuclear magnetic resonance (NMR) spectroscopy to scrutinize metabolic alterations during the initial 35 days following burn injury in a cohort of 17 adult patients with severe burns, with 10 healthy individuals included as controls. Plasma specimens were collected from patients on postburn days 1, 3, 7, 14, 21, 28 and 35. After performing multivariate statistical analysis, repeated-measures analysis of variance and time-series analysis, we quantified changes in metabolite concentrations. Results: Among the 36 metabolites quantified across 119 samples from burn patients, branched-chain amino acids, glutamate, glycine, glucose, pyruvate, lactate, trimethylamine N-oxide and others exhibited obvious temporal variations in concentration. Notably, these metabolites could be categorized into three clusters based on their temporal characteristics. The initial response to injury was characterized by changes in lactate and amino acids, while later changes were driven by an increase in fatty acid catabolism and microbial metabolism, leading to the accumulation of ketone bodies and microbial metabolites. Conclusions: Metabolomics techniques utilizing NMR have the potential to monitor the intricate processes of metabolism in patients with severe burns. This study confirmed that the third day after burn injury serves as the boundary between the ebb phase and the flow phase. Furthermore, identification of three distinct temporal patterns of metabolites revealed the intrinsic temporal relationships between these metabolites, providing clinical data for optimizing therapeutic strategies.

Exploring odontogenic brain abscesses: a comprehensive review.

INTRODUCTION: Whether in neurology or dentistry, odontogenic brain abscess stands as an ailment demanding undivided attention. The onset of this disease is insidious, with a relatively low incidence rate but a markedly high fatality rate. Moreover, its symptoms lack specificity, easily leading to misdiagnosis, oversight, and treatment delays. Hence, clinicians should maintain heightened vigilance when faced with pathogenic bacteria of dental origin in patients. AREAS COVERED: This paper encapsulates the latest research findings on the clinical manifestations and essential treatment points of odontogenic brain abscess. It may offer a crucial reference for prompt diagnosis and improved therapeutic approaches. EXPERT OPINIONS: Odontogenic brain abscess, an infection of the cerebral parenchyma, usually appears in immunocompromised patients with dental ailments or postdental surgeries. The main pathogenic microorganisms include Streptococcus intermedius, Fusobacterium nucleatum, Streptococcus anginosus, and Millerella. Given the undetectable and nonspecific symptoms in patients, the diagnostic process relies on microbiological methods. Therefore, clinicians should actively investigate and identify the pathogenic microorganisms of odontogenic brain abscess for early detection and selection of appropriate treatment regimens to avoid disease management delays.

Organoboron-Promoted Electrochemical Chlorosulfonylation of Alkenes with Sulfonyl Chlorides.

Although extraordinary advances have been achieved by the transition-metal catalysis system, there is an urgent need to explore and develop alternative methodologies that are more environmentally friendly. Herein, we report an electrochemical chlorosulfonylation of alkenes using a wide range of sulfonyl chlorides with an inexpensive, degradable, and commercially available organoboron as a promoter. Furthermore, this protocol employs convergent paired electrolysis, reducing the need for sacrificial anodes and minimizing the extent of hydrogen evolution.

Bridging metabolic syndrome and cognitive dysfunction: role of astrocytes.

Metabolic syndrome (MetS) and cognitive dysfunction pose significant challenges to global health and the economy. Systemic inflammation, endocrine disruption, and autoregulatory impairment drive neurodegeneration and microcirculatory damage in MetS. Due to their unique anatomy and function, astrocytes sense and integrate multiple metabolic signals, including peripheral endocrine hormones and nutrients. Astrocytes and synapses engage in a complex dialogue of energetic and immunological interactions. Astrocytes act as a bridge between MetS and cognitive dysfunction, undergoing diverse activation in response to metabolic dysfunction. This article summarizes the alterations in astrocyte phenotypic characteristics across multiple pathological factors in MetS. It also discusses the clinical value of astrocytes as a critical pathologic diagnostic marker and potential therapeutic target for MetS-associated cognitive dysfunction.

[Modified QuEChERS method combined with ultra performance liquid chromatography-tandem mass spectrometry for detection of cyclopiazonic acid in feeds].

Mycotoxins are toxic secondary metabolites produced by fungal species that can cause acute, subacute, and chronic toxicity in humans and animals. Thus, these toxins pose a significant threat to health and safety. Owing to the lack of effective antimold measures in the agricultural industry, feed ingredients such as corn, peanuts, wheat, barley, millet, nuts, oily feed, forage, and their byproducts are prone to mold and mycotoxin contamination, which can affect animal production, product quality, and safety. Cyclopiazonic acid (CPA), which is mainly biosynthesized from mevalonate, tryptophan, and diacetate units, is a myotoxic secondary metabolite produced by Penicillium and Aspergillus fungi. CPA is widely present as a copollutant with aflatoxins in various crops. Compared with some common mycotoxins such as aflatoxins, fumonisins, ochratoxins, zearalenones, and their metabolites, CPA has not been well investigated. In the United States, a survey showed that 51% of corn and 90% of peanut samples contained CPA, with a maximum level of 2.9 mg/kg. In Europe, CPA was found in Penicillium-contaminated cheeses as high as 4.0 mg/kg. Some studies have shown that CPA can cause irreversible damage to organs such as the liver and spleen in mice. Therefore, the establishment of a rapid and efficient analytical method for CPA is of great significance for the risk assessment of CPA in feeds, the development of standard limits, and the protection of feed product quality and safety. The QuEChERS method, a sample pretreatment method that is fast, simple, cheap, effective, and safe, is widely used in the analysis of pesticide residues in food. In this study, a modified QuEChERS method combined with ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to determine CPA levels in feeds. The chromatographic separation and MS detection of CPA as well as the key factors affecting the extraction efficiency of CPA, including the type of extraction solvent, type of inorganic salt, and type and dosage of adsorbent, were optimized in detail. During the optimization of the chromatographic-separation step, the acid and salt concentrations of the mobile phase affected the separation and detection of CPA. During the optimization of the QuEChERS method, the addition of a certain amount of acetic acid improved the extraction efficiency of CPA because of its acidic nature; in addition, GCB and PSA significantly adsorbed CPA from the feed extract. Under optimal conditions, the CPA in the feed sample (1.0 g) was extracted with 2 mL of water and 4 mL of acetonitrile (ACN) containing 0.5% acetic acid. After salting out with 0.4 g of NaCl and 1.6 g of MgSO4, 1 mL of the ACN supernatant was purified by dispersive solid-phase extraction using 150 mg of MgSO4 and 50 mg of C18 and analyzed by UPLC-MS/MS. The sample was separated on a Waters HSS T3 column (100 mm×2.1 mm, 1.8 µm) using 2 mmol/L ammonium acetate aqueous solution with 0.5% formic acid and ACN as the mobile phases and then analyzed by positive electrospray ionization in multiple reaction monitoring mode. CPA exhibited good linearity in the range of 2-200 ng/mL, with a high correlation coefficient (r=0.9995). The limits of detection and quantification of CPA, which were calculated as 3 and 10 times the signal-to-noise ratio, respectively, were 0.6 and 2.0 µg/kg, respectively. The average recoveries in feed samples spiked with 10, 100, and 500 µg/kg CPA ranged from 70.1% to 78.5%, with an intra-day precision of less than 5.8% and an inter-day precision of less than 7.2%, indicating the good accuracy and precision of the proposed method. Finally, the modified QuEChERS-UPLC-MS/MS method was applied to the analysis of CPA in 10 feed samples obtained from Wuhan market. The analysis results indicated that the developed method has good applicability for CPA analysis in feed samples. In summary, an improved QuEChERS method was applied to the extraction and purification of CPA from feeds for the first time; this method provides a suitable analytical method for the risk monitoring, assessment, and standard-limit setting of CPA in feed samples.

Zinc and Inflammatory Bowel Disease: From Clinical Study to Animal Experiment.

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract (GI) with a high incidence rate globally, and IBD patients are often accompanied by zinc deficiency. This review aims to summarize the potential therapeutic value of zinc supplementation in IBD clinical patients and animal models. Zinc supplementation can relieve the severity of IBD especially in patients with zinc deficiency. The clinical severity of IBD were mainly evaluated through some scoring methods involving clinical performance, endoscopic observation, blood biochemistry, and pathologic biopsy. Through conducting animal experiments, it has been found that zinc plays an important role in alleviating clinical symptoms and improving pathological lesions. In both clinical observation and animal experiment of IBD, the therapeutic mechanisms of zinc interventions have been found to be related to immunomodulation, intestinal epithelial repair, and gut microbiota's balance. Furthermore, the antioxidant activity of zinc was clarified in animal experiment. Appropriate zinc supplementation is beneficial for IBD therapy, and the present evidence highlights that alleviating zinc-deficient status can effectively improve the severity of clinical symptoms in IBD patients and animal models.

Simultaneous brain and neck time-of-flight MRA using spiral multiband with localized quadratic encoding.

PURPOSE: To develop a method that achieves simultaneous brain and neck time-of-flight (ToF) magnetic resonance angiography (MRA) within feasible scan timeframes. METHODS: Localized quadratic (LQ) encoding is efficient for both signal-to-noise ratio (SNR) and in-flow enhancement. We proposed a spiral multiband LQ method to enable simultaneous intracranial and carotid ToF-MRA within a single scan. To address the venous signal contamination that becomes a challenge with multiband (MB) ToF, tilt-optimized non-saturated excitation (TONE) and partial-Fourier slice selection (PFSS) were further introduced in the LQ framework to mitigate the venous signal and improve artery contrast. A sequential spiral MB and LQ reconstruction pipeline was employed to obtain the brain-and-neck image volumes. RESULTS: The proposed MB method was able to achieve simultaneous brain and neck ToF-MRA within a 2:50-min scan. The complementarily boosted SNR-efficiency by MB and LQ acquisitions allows for the increased spatial coverage without increase in scan time or noticeable compromise in SNR. The incorporation of both TONE and PFSS effectively alleviated the venous contamination with improved small vessel sensitivity. Selection of scan parameters such as the LQ factor and flip angle reflected the trade-off among SNR, blood contrast, and venous suppression. CONCLUSIONS: A novel MB spiral LQ approach was proposed to enable fast intracranial and carotid ToF-MRA with minimized venous corruption. The method has shown promise in MRA applications where large spatial coverage is necessary.

The anti-depression effect and potential mechanism of the petroleum ether fraction of CDB: Integrated network pharmacology and metabolomics.

The combination of Chaidangbo (CDB) is an antidepressant traditional Chinese medicine (TCM) prescription simplified by Xiaoyaosan (a classic antidepressant TCM prescription) through dismantling research, which has the effect of dispersing stagnated liver qi and nourishing blood in TCM theory. Although the antidepressant effect of CBD has been confirmed in animal studies, the material basis and possible molecular mechanism for antidepressant activity in CBD have not been clearly elucidated. Herein, we investigated the effects and potential mechanisms of CDB antidepressant fraction (petroleum ether fraction of CDB, PEFC) on chronic unpredictable mild stress (CUMS)-induced depression-like behavior in mice using network pharmacology and metabolomics. First, a UPLC-QE/MS was employed to identify the components of PEFC. To extract active ingredients, SwissADME screening was used to the real PEFC components that were found. Potential PEFC antidepressant targets were predicted based on a network pharmacology approach, and a pathway enrichment analysis was performed for the predicted targets. Afterward, a CUMS mouse depression model was established and LC-MS-based untargeted hippocampal metabolomics was performed to identify differential metabolites, and related metabolic pathways. Finally, the protein expressions in mouse hippocampi were determined by Western blot to validate the network pharmacology and metabolomics deduction. A total of 16 active compounds were screened in SwissADME that acted on 73 core targets of depression, including STAT3, MAPKs, and NR3C1; KEGG enrichment analysis showed that PEFC modulated signaling pathways such as PI3K-Akt signaling pathway, endocrine resistance, and MAPK to exert antidepressant effects. PEFC significantly reversed abnormalities of hippocampus metabolites in CUMS mice, mainly affecting the synthesis and metabolism of glycine, serine, and threonine, impacting catecholamine transfer and cholinergic synapses and regulating the activity of the mTOR signaling pathway. Furthermore, Western blot analysis confirmed that PEFC significantly influenced the main protein levels of the PI3K/Akt/mTOR signaling pathways in the hippocampus of mice subjected to CUMS. This study integrated metabolomics, network pharmacology and biological verification to explore the potential mechanism of PEFC in treating depression, which is related to the regulation of amino acid metabolism dysfunction and the activation of PI3K/Akt/mTOR signaling pathways in the hippocampus. The comprehensive strategy also provided a reasonable way for unveiling the pharmacodynamic mechanisms of multi-components, multi-targets, and multi-pathways in TCM with antidepressant effect.

Association of stress hyperglycemia ratio and mortality in patients with sepsis: results from 13,199 patients.

BACKGROUND: The stress hyperglycemia ratio (SHR), adjusted for average glycemic status, is suggested for assessing actual blood glucose levels. Its link with adverse outcomes is known in certain populations, yet its impact on sepsis patients' prognosis is unclear. This study explores the association between SHR and mortality in sepsis. METHODS: We included 13,199 sepsis patients in this study and categorized SHR into distinct groups. Additionally, we utilized restricted cubic spline analysis to evaluate the correlation between SHR as a continuous variable and mortality. The primary outcome was 1-year all-cause mortality. Logistic regression and Cox proportional hazards models were employed to assess the associations between the SHR and both in-hospital mortality and 1-year mortality, respectively. RESULTS: Among the study participants, 4,690 (35.5%) patients died during the 1-year follow-up. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and 1-year mortality. Using an SHR of 0.99 as the reference point, the hazard ratio for predicted 1-year mortality increased by 1.17 (95% CI 1.08 to 1.27) per standard deviation above 0.99, whereas each standard deviation increase predicted the hazard ratio of 0.52 (95% CI 0.39 to 0.69) below 0.99. Furthermore, we found that SHR could enhance the predictive performance of conventional severity scores. CONCLUSION: There exists a U shaped association between SHR and mortality in sepsis patients, where both low and high SHR values are associated with an increased risk of poor outcomes.

In vivo absorption, in vitro simulated digestion and fecal fermentation properties of polysaccharides from Pinelliae Rhizoma Praeparatum Cum Alumine and their effects on human gut microbiota.

Polysaccharides from Pinelliae Rhizoma Praeparatum Cum Alumine (PPA) have various biological activities, but their properties after oral administration are not clear. In this study, the absorption, digestion and fermentation properties of PPA were studied using in vivo fluorescence tracking, in vitro simulated digestion and fecal fermentation experiments. The absorption experiment showed that fluorescence was only observed in the gastrointestinal system, indicating that PPA could not be absorbed. Simulated digestion results showed that there were no significant changes in the molecular weight, Fourier transform infrared spectroscopy (FT-IR) spectrum, monosaccharides and reducing sugar of PPA during the digestion process, showing that the overall structure of PPA was not damaged. However, the carbohydrate gel electrophoresis bands of PPA enzymatic hydrolysates after simulated digestion were significantly changed, indicating that simulated digestion might impact the configuration of PPA. In vitro fermentation showed that PPA could be degraded by microorganisms to produce short chain fatty acids, leading to a decrease in pH value. PPA can promote the proliferation of Bacteroideaceae, Megasphaera, Bacteroideaceae, and Bifidobacteriaceae, and inhibit the growth of Desulfobacteriota and Enterobacteriaceae. The results indicated that PPA could treat diseases by regulating gut microbiota, providing a scientific basis for the application and development of PPA.

Animal models of inflammatory bowel disease: category and evaluation indexes.

Inflammatory bowel disease (IBD) research often relies on animal models to study the etiology, pathophysiology, and management of IBD. Among these models, rats and mice are frequently employed due to their practicality and genetic manipulability. However, for studies aiming to closely mimic human pathology, non-human primates such as monkeys and dogs offer valuable physiological parallels. Guinea pigs, while less commonly used, present unique advantages for investigating the intricate interplay between neurological and immunological factors in IBD. Additionally, New Zealand rabbits excel in endoscopic biopsy techniques, providing insights into mucosal inflammation and healing processes. Pigs, with their physiological similarities to humans, serve as ideal models for exploring the complex relationships between nutrition, metabolism, and immunity in IBD. Beyond mammals, non-mammalian organisms including zebrafish, Drosophila melanogaster, and nematodes offer specialized insights into specific aspects of IBD pathology, highlighting the diverse array of model systems available for advancing our understanding of this multifaceted disease. In this review, we conduct a thorough analysis of various animal models employed in IBD research, detailing their applications and essential experimental parameters. These include clinical observation, Disease Activity Index score, pathological assessment, intestinal barrier integrity, fibrosis, inflammatory markers, intestinal microbiome, and other critical parameters that are crucial for evaluating modeling success and drug efficacy in experimental mammalian studies. Overall, this review will serve as a valuable resource for researchers in the field of IBD, offering insights into the diverse array of animal models available and their respective applications in studying IBD.

Propagation dynamics of self-accelerating second-order Hermite complex-variable-function Gaussian wave packets in a harmonic potential.

This paper investigates the evolutionary dynamics of self-accelerating second-order Hermite complex-variable-function Gaussian (SSHCG) wave packets in a harmonic potential. The periodic variation of the wave packets is discussed via theoretical analysis and numerical simulation. The control variables method is applied to manipulate the distribution factor, cross-phase factor, potential depth, and chirp parameter, enabling the realization of unique propagation dynamics. In three-dimensional models, the SSHCG wave packets exhibit rotational states, featuring butterfly shape, three peaks shape, two polarity shape, elliptical shape, and ring-shaped double-vortex structures. Furthermore, the energy flow and the angular momentum of the wave packets are investigated. Additionally, the performance of the radiation force on a Rayleigh dielectric particle is studied. This investigation results in the emergence of distinct SSHCG wave packet propagation dynamics, and potential applications in optical communications and optical trapping are presented.

Nile Tilapia (Oreochromis niloticus) Patched1 Mutations Disrupt Cardiovascular Development and Vascular Integrity through Smoothened Signaling.

Hedgehog (Hh) signaling is crucial in cardiovascular development and maintenance. However, the biological role of Patched1 (Ptch1), an inhibitory receptor of the Hh signaling pathway, remains elusive. In this study, a Ptch1 ortholog was characterized in Nile tilapia (Oreochromis niloticus), and its function was investigated through CRISPR/Cas9 gene knockout. When one-cell embryos were injected with CRISPR/Cas9 targeting ptch1, the mutation efficiency exceeded 70%. During 0-3 days post fertilization (dpf), no significant differences were observed between the ptch1 mutant group and the control group; at 4 dpf (0 day after hatching), about 10% of the larvae showed an angiogenesis defect and absence of blood flow; from 5 dpf, most larvae exhibited an elongated heart, large pericardial cavity, and blood leakage and coagulation, ultimately dying during the 6-8 dpf period due to the lack of blood circulation. Consistently, multiple differentially expressed genes related to angiogenesis, blood coagulation, and heart development were enriched in the ptch1 mutants. Furthermore, Smoothened (Smo) antagonist (cyclopamine) treatment of the ptch1 mutants greatly rescued the cardiovascular disorders. Collectively, our study suggests that Ptch1 is required for cardiovascular development and vascular integrity via Smo signaling, and excessive Hh signaling is detrimental to cardiovascular development.

Cross-Modal Retrieval With Noisy Correspondence via Consistency Refining and Mining.

The success of existing cross-modal retrieval (CMR) methods heavily rely on the assumption that the annotated cross-modal correspondence is faultless. In practice, however, the correspondence of some pairs would be inevitably contaminated during data collection or annotation, thus leading to the so-called Noisy Correspondence (NC) problem. To alleviate the influence of NC, we propose a novel method termed Consistency REfining And Mining (CREAM) by revealing and exploiting the difference between correspondence and consistency. Specifically, the correspondence and the consistency only be coincident for true positive and true negative pairs, while being distinct for false positive and false negative pairs. Based on the observation, CREAM employs a collaborative learning paradigm to detect and rectify the correspondence of positives, and a negative mining approach to explore and utilize the consistency. Thanks to the consistency refining and mining strategy of CREAM, the overfitting on the false positives could be prevented and the consistency rooted in the false negatives could be exploited, thus leading to a robust CMR method. Extensive experiments verify the effectiveness of our method on three image-text benchmarks including Flickr30K, MS-COCO, and Conceptual Captions. Furthermore, we adopt our method into the graph matching task and the results demonstrate the robustness of our method against fine-grained NC problem. The code is available on https://github.com/XLearning-SCU/2024-TIP-CREAM.

Underwater image enhancement using multi-task fusion.

Underwater images are often scattered due to suspended particles in the water, resulting in light scattering and blocking and reduced visibility and contrast. Color shifts and distortions are also caused by the absorption of different wavelengths of light in the water. This series of problems will make the underwater image quality greatly impaired, resulting in some advanced visual work can not be carried out underwater. In order to solve these problems, this paper proposes an underwater image enhancement method based on multi-task fusion, called MTF. Specifically, we first use linear constraints on the input image to achieve color correction based on the gray world assumption. The corrected image is then used to achieve visibility enhancement using an improved type-II fuzzy set-based algorithm, while the image is contrast enhanced using standard normal distribution probability density function and softplus function. However, in order to obtain more qualitative results, we propose multi-task fusion, in which we solve for similarity, then we obtain fusion weights that guarantee the best features of the image as much as possible from the obtained similarity, and finally we fuse the image with the weights to obtain the output image, and we find that multi-task fusion has excellent image enhancement and restoration capabilities, and also produces visually pleasing results. Extensive qualitative and quantitative evaluations show that MTF method achieves optimal results compared to ten state-of-the-art underwater enhancement algorithms on 2 datasets. Moreover, the method can achieve better results in application tests such as target detection and edge detection.

2D Ni-Co bimetallic oxide nanosheets activate persulfate for targeted conversion of bisphenol A in wastewater into polymers.

The selective removal of targeted pollutants from complex wastewater is challenging. Herein, a novel persulfate (PS)-based advanced oxidation system equipped with a series of two-dimensional (2D) bimetallic oxide nanosheets (NSs) catalysts is developed to selectively degrade bisphenol A (BPA) within mixed pollutants via initiating nonradical-induced polymerization. Results indicate that the Ni0.60Co0.40Ox NSs demonstrate the highest catalytic efficiency among all Ni-Co NSs catalysts. Specifically, BPA degradation rate is 47.34, 27.26, and 9.72 times higher than that of 4-chlorophenol, phenol, and 2,4-dichlorophenol in the mixed solution, respectively. The lower oxidative potential of BPA in relation to the other pollutants renders it the primary target for oxidation within the PDS activation system. PDS molecules combine on the surface of Ni0.60Co0.40Ox NSs to form the surface-activated complex, triggering the generation of BPA monomer radicals through H-abstraction or electron transfer. These radicals subsequently polymerize on the surface of the catalyst through coupling reactions. Importantly, this polymerization process can occur under typical aquatic environmental conditions and demonstrates resistance to background matrices like Cl- and humic acid due to its inherent nonradical attributes. This study offers valuable insights into the targeted conversion of organic pollutants in wastewater into value-added polymers, contributing to carbon recycle and circular economy.