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This paper is a methodological reflection on a community-based participatory research (CBPR) project that used the photovoice method to unravel the educational experiences of disabled college students in China's higher education institutions. Although CBPR endeavors to nurture equitable community engagement in research processes, there are practical challenges to address the full participation of people with divergent disabilities and access needs. Drawing upon the critical disability studies literature, and particularly upon the activist scholarship of disability justice that revolves around interdependency, collective access, and cross-disability solidarity, we provide an open discussion on the complexities, tensions, and challenges of envisioning and creating access for participants with different disabilities in a visuality-centered CBPR. Our findings suggest that access creation in CBPR should go beyond the checklist style of accommodation and instead be approached as relational, dynamic, and iterative processes that require ongoing reflection, (re)learning, and negotiation among researchers and participants. We implemented nonvisual photography to adapt to the visuality-centered bias in the photovoice method. Nonvisual photography empowered participants with visual disabilities to evoke multiple sensorialities in their photo-taking, displaying, and interpretation. Moreover, the participants without visual disabilities also learned and practiced collective access and interdependency through co-transforming the CBPR into an accessible space for all. The heterogeneity among participants with divergent disabilities and access needs challenged CBPR's envisioning of a unified community with recognized commonalities. The inclusion of participants across disability groups created an opportunity for all participants to draw meaning from the ableist social and political circumstances that forged them as a community and to develop a sense of belonging and bonding in and through CBPR. In that light, disability justice and access should be reimagined and incorporated into CBPR. [ABSTRACT FROM AUTHOR]

Introduction: The automatic segmentation of the liver is a crucial step in obtaining quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems. This task is challenging due to the frequent presence of noise and sampling artifacts in computerized tomography (CT) images, as well as the complex background, variable shapes, and blurry boundaries of the liver. Standard segmentation of medical images based on full-supervised convolutional networks demands accurate dense annotations. Such a learning framework is built on laborious manual annotation with strict requirements for expertise, leading to insufficient high-quality labels. Methods: To overcome such limitation and exploit massive weakly labeled data, we relaxed the rigid labeling requirement and developed a semi-supervised double-cooperative network (SD- Net). SD-Net is trained to segment the complete liver volume from preoperative abdominal CT images by using limited labeled datasets and large-scale unlabeled datasets. Specifically, to enrich the diversity of unsupervised information, we construct SD-Net consisting of two collaborative network models. Within the supervised training module, we introduce an adaptive mask refinement approach. First, each of the two network models predicts the labeled dataset, after which adaptive mask refinement of the difference predictions is implemented to obtain more accurate liver segmentation results. In the unsupervised training module, a dynamic pseudo-label generation strategy is proposed. First each of the two models predicts unlabeled data and the better prediction is considered as pseudo-labeling before training. Results and discussion: Based on the experimental findings, the proposed method achieves a dice score exceeding 94%, indicating its high level of accuracy and its suitability for everyday clinical use. [ABSTRACT FROM AUTHOR]

Abstract \nPOINTS OF INTERESTS Moving away from an individual and pathological framework and instead drawing on a social-relational model of disability, this article examines the experiences of mothers with autistic children in navigating between caregiving and working life in China. Conducting narrative analysis of 14 in-depth interviews with mothers of autistic children, we argue that their decisions to make adjustments to work are situated in social and relational dynamics of disabled and gendered cultural ideologies, inaccessibility to healthcare, education, and social services, as well as filial familial relationship. As a result, they have to adjust their careers and personal life, such as resigning from previous work and becoming full-time mothers. Although these women constantly experienced a strong sense of loss in terms of their personal and social identity, some developed new perspectives seeing disability, normality, and the meaning of ‘good mother’ in the process of negotiating their work life and motherhood role. Mothers of autistic children in China experience social and relational barriers in caregiving and working life. Mothers adjust to their careers and personal life by quitting their previous jobs and becoming full-time mothers, changing positions, or switching to part-time employment. The unavailability of healthcare and social service, as well as the discrimination of the education system against children with autism, significantly affect their mothers’ work and family life. Autistic children encounter exclusion in the filial family in China. Grandparents and fathers of autistic children often refuse to participate in childcare arrangements. As a result, mothers had to bear the care responsibility alone. Some mothers described their personal journey of ‘walking out’. They rejected the idea that autism is a form of abnormality needed to be cured. They also organized to advocate for social inclusion and policy changes. Mothers of autistic children in China experience social and relational barriers in caregiving and working life.Mothers adjust to their careers and personal life by quitting their previous jobs and becoming full-time mothers, changing positions, or switching to part-time employment.The unavailability of healthcare and social service, as well as the discrimination of the education system against children with autism, significantly affect their mothers’ work and family life.Autistic children encounter exclusion in the filial family in China. Grandparents and fathers of autistic children often refuse to participate in childcare arrangements. As a result, mothers had to bear the care responsibility alone.Some mothers described their personal journey of ‘walking out’. They rejected the idea that autism is a form of abnormality needed to be cured. They also organized to advocate for social inclusion and policy changes. [ABSTRACT FROM AUTHOR]

The reasonable selection of cutting parameters in the machining process is of great significance to improve productivity, reduce production costs, and improve the quality of parts. However, due to the complexity of cutting parameter model optimization, most factories currently use experience or refer to relevant manuals to select the value of cutting parameters in production. In order to avoid and minimize abnormalities, they usually select more experienced and conservative values, and often do not select reasonable cutting parameters, which is not conducive to improving productivity, reducing production costs, and improving the quality of parts. Therefore, the research on cutting parameter optimization has important theoretical value and application value. In this paper, in order to find the optimal cutting parameters, the cutting model is solved by the improved monarch butterfly optimization (IMBO) algorithm, and the optimized cutting parameters are obtained. By establishing the mathematical model of cutting, the constraint conditions of actual machining are introduced into the model. In order to solve the model, some ideas of particle swarm optimization (PSO) and differential evolution (DE) are added to the traditional monarch butterfly optimization (MBO) algorithm. The MBO algorithm is improved to deal with multiobjective optimization problems. The IMBO algorithm is used to optimize the cutting model. The experiment shows that the optimized cutting parameters can significantly reduce production cost and maintain high production efficiency. Compared with NSGA-II algorithm and other swarm intelligence optimization algorithms, it shows that the IMBO algorithm has certain advantages in multiobjective optimization. [ABSTRACT FROM AUTHOR]

Limited attention has been paid to market actors' interventions and their consequences in regard to shaping NGOs' behaviors in China. Drawing on a case study of a national disability organization's participation in China's largest internet fundraising campaign—the Tencent Charity Day—this paper examines how market actors constitute the institutional contexts that shape and restructure NGOs' framing and practice. I argue that market actors transform the institutional environments of NGOs by transplanting social media platforms' institutional logic concerning the attention economy to incubate NGOs' charitable marketing practices. The consequences of this transformation are the re-coalitions of actors, as well as the rise of charitable framing and the market methods of charitable programming. Meanwhile, market interventions unintendedly open spaces for grassroots NGOs to pursue their social missions and re-envision rights and advocacy under transformed state–civil society relationships, even though this process is highly uneven and hierarchical. [ABSTRACT FROM AUTHOR]

Although discrimination has gained increasing attention in research and practice intervention for family caregivers of children with disabilities, little is known about the social determinants that associate with the perceived discrimination among caregivers, especially in non-Western contexts. This study aims to examine the socio-familial and child-level determinants of perceived discrimination among family caregivers of children with disabilities in China. This study drew from a population-based cross-sectional survey in Shenzhen, China. Proportional quota sampling was conducted to get data from 2500 family caregivers of children with disabilities in rehabilitation service centers (response rate = 94.9%, n = 2373), accounting for 25% of the total population of children with disabilities receiving service in Shenzhen. Latent profile analysis was conducted to categorize three perceived discrimination groups among caregivers (i.e., severe perceived discrimination group, moderate perceived discrimination group, and low perceived discrimination group). The multinomial logistic regression models were conducted to test the association between these social determinants and perceived discrimination. Most caregivers (82.9%) reported moderate or severe levels of perceived discrimination. Caregivers of children with moderate and severe impairments and children with mental and multiple disabilities were more vulnerable to perceiving severe social discrimination. Socio-familial characteristics, particularly the intersectionality between gender and employment, influence caregivers' perceived discrimination. Caregivers of children with disabilities experience pervasive social discrimination in contemporary urban China. Our study demonstrates that the social construction of disablism and the affiliate discrimination against family caregivers of children with disabilities is complex and multidimensional and depends upon the children's disability and the caregivers' socio-demographic characteristics. • 80% disabled children's parents report moderate/severe perceived discrimination. • Mental and more severe disability are related to greater perceived discrimination. • Being female and unemployed are associated with greater perceived discrimination. [ABSTRACT FROM AUTHOR]

Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a very serious problem. This article mainly studies a diagnostic method of microscopic images of liver and gallbladder tumors. Under this research direction, this article proposes to use convolutional neural network to learn and use hyperspectral images to diagnose it. It is found that the addition of the convolutional neural network can greatly improve the actual map classification and the accuracy of the map, and effectively improve the success rate of the treatment. At the same time, the article designs related experiments to compare its feature extraction performance and classification situation. The experimental results in this article show that the improved diagnostic method based on convolutional neural network has an accuracy rate of 85%–90%, which is as high as 6%–8% compared with the traditional accuracy rate, and thus it effectively improves the clinical problem of hepatobiliary tumor treatment. [ABSTRACT FROM AUTHOR]

Strengthening aquatic resilience to prevent adverse shifts is critical for preserving global freshwater biodiversity and advancing Sustainable Development Goals. Nonetheless, understanding the long‐term trends and underlying causes of lake ecosystem resilience at a global scale remains elusive. Here, we employ an innovative framework, integrating satellite‐derived water quality indices with early warning signals and machine learning techniques, to investigate the dynamics of resilience in 1,049 lakes worldwide during 2000–2018. Our results indicate that 46.7% of lakes are experiencing a significant decline in resilience, particularly since the early 2010s, closely associated with higher human population density and anthropogenic eutrophication. In contrast, most lakes situated in alpine regions exhibit an increase in resilience, probably benefiting from climate warming and wetting. Together, this study provides a novel way to monitor lake resilience and predict undesired transitions, and reveals a widespread erosion in the ability of lakes to withstand stressors associated with global change. Plain Language Summary: Based on water quality data from satellite observation and generic indicators of ecological resilience, we found 46.7% of lakes worldwide are experiencing a significant decline in the ability to resist and recover from environmental disturbances. This issue is exacerbated in Northern Europe and Eastern North America, closely related to local human impacts, such as anthropogenic eutrophication. As the regional wealth grows, like in central North America, the negative impact of human activity on aquatic ecosystems may decrease. In contrast, in regions like the Tibetan Plateau and Andes Mountains, lakes are actually showing an increase in resilience, indicating that ecosystems may adapt to or even benefit from climate change. Our analysis' global scope allows us to better understand lake ecosystem dynamics and the socioeconomic drivers associated with them. This knowledge will help manage lakes' response to global change. Key Points: Over the last two decades (2000–2018), nearly half of global lakes experienced resilience lossLake resilience decline is closely linked to human activities in the catchmentsSatellite data effectively track early warning signals of lake resilience loss [ABSTRACT FROM AUTHOR]

To enhance the quality of tobacco leaves and optimize the smoking experience, diverse strains of functional bacteria and their associated metabolites have been used in tobacco aging. Exogenous cellulase additives are frequently employed to facilitate the degradation of cellulose and other macromolecular matrices and enhance the quality of the tobacco product. However, little is known about how microbial metabolites present in exogenous enzyme additives affect tobacco quality. In this study, crude cellulase solutions, produced by a tobacco-originating bacterium Bacillus subtilis FX-1 were employed on flue-cured tobacco. The incorporation of cellulase solutions resulted in the reduction of cellulose crystallinity in tobacco and the enhancement of the overall sensory quality of tobacco. Notably, tobacco treated with cellulase obtained from laboratory flask fermentation demonstrated superior scent and flavor attributes in comparison to tobacco treated with enzymes derived from industrial bioreactor fermentation. The targeted and untargeted metabolomic analysis revealed the presence of diverse flavor-related precursors and components in the cellulase additives, encompassing sugars, alcohols, amino acids, organic acids, and others. The majority of these metabolites exhibited significantly higher levels in the flask group compared to the bioreactor group, probably contributing to a pronounced enhancement in the sensory quality of tobacco. Our findings suggest that the utilization of metabolic products derived from B. subtilis FX-1 as additives in flue-cured tobacco holds promise as a viable approach for enhancing sensory attributes, establishing a solid theoretical foundation for the potential development of innovative tobacco aging additives. Cellulase solutions obtained from Bacillus subtilis FX-1, a bacterium originating from tobacco, were applied to flue-cured tobacco during the aging process. The cellulase structure of tobacco was analyzed using 13C cross-polarization magic angle spinning NMR spectroscopy. Sensory evaluation was utilized to assess the sensory attributes and quality characteristics. Targeted and untargeted metabolomics were utilized to investigate the chemical components present in the cellulase solutions. The inclusion of cellulase additives altered the cellulose structure in tobacco and introduced various flavor-related precursors and components. The utilization of cellulase additives derived from B. subtilis FX-1 substantially improved the overall quality of the tobacco product. [ABSTRACT FROM AUTHOR]

This article examines the challenges and opportunities of implementing the CRPD's rights-based model in China, especially the effects of the diminishing space for civil society on the nascent disability rights movement. A disability rights movement emerged as a direct result of the CRPD's adoption in 2008. Two recent restrictive civil society legislations, however, undermined this process. While the diminishing space of civil society has posed great challenges to the movement by marginalizing the rights advocacy approach, it has created an opportunity for service-oriented disability associations to thrive. While service-oriented associations are often ignored by disability studies scholarship and the disability rights movement, I argue that, through these organizations, persons with disabilities in China have done critical identity work and substantively increased their level of independence in their daily lives. As a result, a disability rights consciousness continues to be built in China, despite governmental hostility to political advocacy. [ABSTRACT FROM AUTHOR]

The effect of dehydration of plant cell walls on the physical status of cellulose microfibrils (CMFs) interspersed in pectin matrices was studied. Vibrational sum frequency generation (SFG) spectroscopy analysis of cellulose revealed reversible changes in spectral features upon dehydration and rehydration of onion epidermal walls used as a model primary cell wall (PCW). Combined with microscopic imaging and indentation modulus data, such changes could be attributed to local strains in CMFs due to the collapse of the pectin matrix upon dehydration. X-ray diffraction (XRD) showed that the (200) spacing of cellulose in dried PCWs is larger than that of cellulose Iβ obtained from tunicates. Thus, the modulus of CMFs in PCWs would be lower than those of highly-crystalline cellulose Iβ and inhomogeneous local bending or strain of CMFs could occur readily during the physical collapse of pectin matrix due to dehydration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fe–N–C with various morphologies and enriched iron sites were constructed. • Fe–N x was identified as the dominated active site for periodate activation. • Fe0/Fe 3 C nanoparticles were found inactive for activating periodate. • Fe–N–C/PI oxidized contaminants through a nonradical mechanism. • Fe–N–C/PI showed strong resistance to background constituents. The practical application of periodate-based advanced oxidation technologies (PI-AOTs) for wastewater treatment requires efficient and cost-effective activators. Pyrolyzed Fe–N/C materials are potential candidates, however, their actual active sites and activation mechanisms are yet to be fully understood. Herein, a series of Fe–N/C samples (denoted as Fe@NC- X) with differing structures and iron components were delicately synthesized. Experimental studies on the structure–activity relationship and density functional theory (DFT) computations revealed that Fe–N x species serve as the dominant active site for periodate activation, while the inactive iron-based particles (i.e., Fe0 and Fe 3 C) optimized the binding affinity of surrounding carbon layers with periodate, resulting in enhanced activity. In-depth exploration of the oxidative mechanism revealed that Fe@NC- X activated periodate through an electron transfer regime. Our results also showed that the optimal Fe@NC-0.2/periodate system was highly effective in catalyzing the oxidation of 4-CP, outperforming many reported activators. These findings provide an indispensable foundation for the rational development of advanced Fe–N/C activators and offer vital insights into the mechanism underlying pollutant destruction through PI-AOTs. [ABSTRACT FROM AUTHOR]

Regime shifts of freshwater ecosystems driven by fast-changing multiple stressors are increasingly occurring. However, lake regime shifts across intensive agricultural landscapes are less explored, especially how different aquatic communities respond to multiple environmental forcings through time is poorly understood. Using a century scale paleolimnological record from Gaoyou Lake in the Huai River Basin, one of the most intensively cultivated areas in China, we analyzed high-resolution sedimentary subfossil pigments and cladoceran assemblages to investigate the dynamic trajectories of plankton communities and detect the potential occurrence of ecological shifts across different aquatic trophic levels. Furthermore, we explored how these shifts were driven by anthropogenic and climatic stressors, and examined the rates of ecological change through time. Our results revealed a significant ecological shift in the cladoceran community around the 1970s associated with the hydrological regulation through damming within the basin. Subsequently, a regime shift for the whole-lake ecosystem occurred in the 1990s, which was characterized by the onset of eutrophication with elevated primary production and decreased water clarity. Redundancy and variance partitioning analyses identified agricultural intensification with substantial anthropogenic nutrient loading as the main driver of lake ecological dynamics. Rising temperature played an additional role. Moreover, we detected two significant acceleration phases of lake primary productivity (in the 1990s and after the 2000s), which were asynchronous with the variability of external environmental drivers. This finding probably indicated Gaoyou Lake has switched from a slow-to a fast-response system with decreasing ecological stability. Our study offers new challenges and insights for incorporating rate-focused management strategies to minimize the risk of catastrophic ecological shifts in aquatic ecosystems. • Agricultural intensifications triggered pervasive lake regime shifts. • A great increase in the RoC of lake primary production occurred before regime shift. • The lake switched from a slow-to fast-response system with decreased stability. • The integration of historical baseline and rate-focused management are recommended. [ABSTRACT FROM AUTHOR]

Abrupt ecological shifts have become a pervasive feature of aquatic ecosystems with severe socio-ecological consequences. Yet, it remains uncertain whether these shifts happened synchronously or not among various lakes, and how multiple drivers interacted through time to drive these abrupt changes on a global scale. To address this knowledge gap, here we conducted a meta-analysis of 72 lakes worldwide based on integrated paleoecological records ranging from the 1850s–2010s. We found ecological shifts were mostly asynchronous across global lakes, but with an exceptionally increasing frequency since the 1950s. Driver-response results showed that abrupt shifts before the 1950s were dominated by climate change, whereas both anthropogenic drivers and climate change were responsible for most post-1950s shifts. Network analysis further indicated that interactions of multiple stressors are more prone to produce abrupt shifts, and global climate change is the most frequent co-occurrence driver, underscoring the need for global coherent collaboration to mitigate Anthropocene risk. Our findings provide new insights and empirical evidence for characterizing the Anthropocene from a global lake perspective. [ABSTRACT FROM AUTHOR]

Simple Summary: In order to understand the prevalence of respiratory diseases in urban stray cats in Shanghai and provide scientific evidence for the development of targeted prevention and control strategies for respiratory diseases in stray cats, we performed a molecular survey in Shanghai in 2022. A total of 374 stray cats were screened against six respiratory pathogens. Out of the 374 samples, 146 tested positive. Mycoplasma felis exhibited the highest positivity rate at 18.72% (70/374), followed by Chlamydia felis at 11.76% (44/374), feline calicivirus at 3.74% (14/374), feline herpesvirus type-1 at 3.48% (13/374), and Bordetella bronchiseptica at 1.34% (5/374); influenza A virus was not detected. Mycoplasma felis and Chlamydia felis were the primary causative agents of respiratory infections in urban stray cats, with Mycoplasma felis demonstrating a notably higher positivity rate compared to other respiratory pathogens and frequently co-infecting with Chlamydia felis and feline calicivirus. The positivity rate of Mycoplasma felis was elevated during the summer, autumn, and winter seasons, with no significant variance between seasons. These results highlight a substantial overall prevalence of respiratory pathogens in urban stray cats in the Shanghai region, characterized by seasonal patterns and concurrent infections with other pathogens. These findings suggest the need for comprehensive prevention and control measures to address respiratory pathogen infections in urban stray cats in the Shanghai area. Urban stray cats are cats without owners that survive in the wild for extended periods of time. They are one of the most common stray animals in cities, and as such, monitoring the pathogens carried by urban stray cats is an important component of urban epidemiological surveillance. In order to understand the prevalence of respiratory diseases in urban stray cats in Shanghai and provide scientific evidence for the development of targeted prevention and control strategies for respiratory diseases in stray cats, we collected 374 ocular, nasal, and oropharyngeal swabs from urban stray cats in Shanghai from January 2022 to December 2022. After RNA extraction, we used real-time PCR to detect six respiratory pathogens, including influenza A virus, feline calicivirus, feline herpesvirus type 1, Mycoplasma, Chlamydia, and Bordetella bronchiseptica. The results showed that among the 374 samples, 146 tested positive, with a positivity rate of 39.04%. The highest positivity rate was observed for Mycoplasma felis at 18.72% (70/374), followed by Chlamydia felis at 11.76% (44/374), feline calicivirus at 3.74% (14/374), feline herpesvirus 1 at 3.48% (13/374), Bordetella bronchiseptica at 1.34% (5/374), and influenza A virus was not detected. The highest positivity rate for Mycoplasma felis was in Minhang District at 31.94% (23/72), while Chlamydia felis and Bordetella bronchiseptica had the highest positivity rates in Jiading District at 23.53% (8/34) and 5.88% (2/34), respectively. The highest positivity rates for feline calicivirus and feline herpesvirus 1 were both observed in Qingpu District, at 14.46% (12/83) and 9.64% (8/83), respectively. A total of 36 samples showed mixed infections with two or more pathogens, with Mycoplasma felis being involved in 32 of these mixed infections, with the highest number of mixed infections being with Chlamydia felis at 25 samples. Respiratory pathogen positivity was detected throughout the year, with peak detection rates in summer and winter. The positivity rates of cat respiratory pathogens in different seasons showed statistical differences (χ2 = 27.73, p < 0.01). There was no statistical difference in the positivity rates of respiratory pathogens between cats of different genders (χ2 = 0.92, p > 0.05). The positivity rates of respiratory pathogens in cats of different age groups showed statistical differences (χ2 = 44.41, p < 0.01). Mycoplasma felis and Chlamydia felis were the main pathogens causing respiratory infections in stray cats, with Mycoplasma felis showing a much higher positivity rate than other respiratory pathogens and often co-infecting with Chlamydia felis and feline calicivirus. The positivity rate of Mycoplasma felis was high in summer, autumn, and winter, with no statistical difference between seasons. These results indicate a serious overall prevalence of respiratory pathogens in urban stray cats in the Shanghai area, showing seasonal trends and mixed infections with other pathogens. These findings suggest the need for comprehensive prevention and control measures to address respiratory pathogen infections in urban stray cats in the Shanghai area. [ABSTRACT FROM AUTHOR]

• We propose a Behavior Regularized Prototypical Network (BR-ProtoNet) for few-shot image classification in semi-supervised scenarios. • BR-ProtoNet enables metric learning to benefit from readily-available unlabeled data. • We construct complementary constraints to regularize the model's behavior over the neighborhoods of training instances and along the interpolation paths among them. • The constructed regularization encourages the learnt embedding space to possess the property of proximity preservation. We propose a Behavior Regularized Prototypical Network (BR-ProtoNet) for few-shot image classification in semi-supervised scenarios. To learn a generalizable metric, we exploit readily-available unlabeled data and construct complementary constraints to regularize the model's behavior. Specifically, we match the label spaces between each episode and the whole training set. The predictions on the unlabeled data over different episodes can be aggregated to capture more reliable category information. We further construct new instances via adversarial perturbation and interpolation. These instances regularize the model's behavior over the neighborhoods of the original ones and along the interpolation paths among them. In addition, they ensure the learnt embedding space possesses the property of proximity preservation. The regularization of these aspects is incorporated into the optimization process of BR-ProtoNet on partially labeled data. We have conducted thorough experiments on multiple challenging benchmarks. The results suggest that the metric learning can significantly benefit from the proposed regularization, and thus leading to the state-of-the-art performance in semi-supervised few-shot image classification. [ABSTRACT FROM AUTHOR]

Objectives. Evidence suggests that about 80% of all salivary gland tumors involve the parotid glands, with approximately 20% of parotid gland tumors (PGTs) being malignant. Discriminating benign and malignant parotid gland lesions preoperatively is vital for selecting the appropriate treatment strategy. This study explored the diagnostic performance of deep learning system for discriminating benign and malignant PGTs in ultrasonography images and compared it with radiologists. Methods. A total of 251 consecutive patients with surgical resection and proven parotid gland malignant or benign tumors who underwent preoperative ultrasound examinations were enrolled in this study between January 2014 and November 2020. Next, we compared the diagnostic accuracy of deep learning methods (ViT-B\16, EfficientNetB3, DenseNet121, and ResNet50) and radiologists in parotid gland tumor. In addition, the area under the curve (AUC), specificity, sensitivity, positive predictive value, and negative predictive value were calculated. Results. Among the 251 patients, 176/251 were the training set, whereas 75/251 were the validation set. Results showed that 74/251 patients had malignant tumor. Deep learning models achieved good performance in differentiating benign from malignant tumors, with the diagnostic accuracy and AUCs of ViT-B\16, EfficientNetB3, DenseNet121, and ResNet50 model being 81% and 0.81, 80% and 0.82, 77% and 0.81, and 79% and 0.80, respectively. On the other hand, the diagnostic accuracy and AUCs of radiologists were 77%-81% and 0.68-0.75, respectively. It was evident that the diagnostic accuracy of deep learning methods was higher than that of inexperienced radiologists, but there was no significant difference between deep learning methods and experienced radiologists. Conclusions. This study shows that the deep learning system can be used for diagnosing parotid tumors. The findings also suggest that the deep learning system may improve the diagnosis performance of inexperienced radiologists. [ABSTRACT FROM AUTHOR]

Ion exchange resins are commonly utilized for water treatment in pressurized water reactors' primary loop. These resins have the ability to adsorb radioactive cations present in the primary loop coolant, leading to a purification effect. However, the resin becomes radioactive post-purification and cannot be regenerated, thus requiring regular replacement. As the process of resin replacement exposes personnel to radiation, it is crucial to enhance the resin's utilization. This paper aims to investigate a non-destructive testing method for evaluating the lifetime of resin in pressurized water reactor purification units. It also aims to offer guidance for safe resin replacement. The resin is contained in a column (commonly referred to as ion exchange columns) and consumed from top to bottom, with radioactivity decreasing in intensity from top to bottom. The study utilizes the longitudinal radioactivity distribution characteristics of ionic resins to build a gamma-ray detection system with high resistance to interlayer interference and good longitudinal resolution. In this study, a two-stage resin column was utilized to capture common fission product nuclides and corrosion-activated nuclides, such as 60Co, 137Cs, 54Mn, and 124Sb, from the effluent of a pressurized water reactor. The distribution of these nuclides was measured using this device. The results indicate that the activity levels of 60Co, 137Cs, and 54Mn reached their peak in the column before rapidly declining. The height of the resin layer corresponding to the highest activity level of each nuclide varied, indicating the resin's adsorption selectivity. After processing an additional 10 tons of wastewater, a second measurement was taken which showed that the failure range of the resin expanded downwards as the treated water volume increased. The entire distribution curve of the nuclides within the exchange column also shifted upwards and to the right. By comparing the first and second observations, we discovered that the bottom part of the resin will fail when the activity of the most penetrating nuclide in the wastewater surpasses a specific threshold. This research suggests a novel approach to predicting the lifetime of resin, which generalizes the trend of radionuclide intensity inside the ion exchange column. • Designed a detection system to measure the longitudinal distribution of radioactivity in resins for PWR primary loop. • Simulation and experiment were used to verify the top-down depletion of resin in the ion exchange column. • The changes in the distribution of radionuclides within the resin as the treated water increases are discussed. • A method for predicting the resin life of PWR primary loop is proposed by mathematical iteration. [ABSTRACT FROM AUTHOR]

The increasingly popular fused batch-streaming big data framework, Apache Flink, has many performance-critical as well as untamed configuration parameters. However, how to tune them for optimal performance has not yet been explored. Machine learning (ML) has been chosen to tune the configurations for other big data frameworks (e.g., Apache Spark), showing significant performance improvements. However, it needs a long time to collect a large amount of training data by nature. In this article, we propose a guided machine learning (GML) approach to tune the configurations of Flink with significantly shorter time for collecting training data compared to traditional ML approaches. GML innovates two techniques. First, it leverages generative adversarial networks (GANs) to generate a part of training data, reducing the time needed for training data collection. Second, GML guides a ML algorithm to select configurations that the corresponding performance is higher than the average performance of random configurations. We evaluate GML on a lab cluster with 4 servers and a real production cluster in an internet company. The results show that GML significantly outperforms the state-of-the-art, DAC (Datasize-Aware-Configuration) (Z. Yu et al. 2018) for tuning the configurations of Spark, with 2.4× of reduced data collection time but with 30 percent reduced 99th percentile latency. When GML is used in the internet company, it reduces the latency by up to 57.8× compared to the configurations made by the company. [ABSTRACT FROM AUTHOR]

Macrophytes play important roles in maintaining ecosystem health and stability of shallow lakes. Better understanding of their long-term dynamics has important theoretical and practical significance for both lake ecosystem restoration and eutrophication control. However, the knowledge about the historical status and changing patterns of macrophytes in China's shallow lakes is still controversial and lacks systematic research. Here, we reviewed and synthesized the published records of submerged macrophytes from 14 typical shallow lakes in the eastern plain covering the past 100 years. The results suggest that submerged macrophytes have experienced three clear stages of change: rare period (the 1900s-the 1950s), growth period (the 1950s-the 1980s), and recession period (the 1980s-now). This finding is different from the traditional understanding that submerged macrophytes were abundant in the early 20th century and have been degrading since then. On this basis, we proposed the possible evolution pattern (less-more-less) of submerged macrophytes in the eastern plain lake region over the past 100 years, which provides new perspectives about the long-term evolution process of macrophytes in shallow lakes. Furthermore, we found that the decline of submerged macrophytes during the regime shift shows a gradual process at the interdecadal scale; this finding contradicts the classical regime shift theory that macrophytes decline sharply during the critical transition. This study has important theoretical value for the restoration of the eastern plain lakes in China from "turbid lake" to "clear lake", especially for establishing the historical reference condition and restoration path of macrophytes. [ABSTRACT FROM AUTHOR]

Background: Mechanical refining is a low-capital and well-established technology used in pulp and paper industry to improve fiber bonding for product strength. Refining can also be applied in a biorefinery context to overcome the recalcitrance of pretreated biomass by opening up the biomass structure and modifying substrate properties (e.g., morphology, particle size, porosity, crystallinity), which increases enzyme accessibility to substrate and improves carbohydrate conversion. Although several characterization methods have been used to identify the changes in substrate properties, there is no systematic approach to evaluate the extent of fiber cell wall disruption and what physical properties can explain the improvement in enzymatic digestibility when pretreated lignocellulosic biomass is mechanically refined. This is because the fiber cell wall is complex across multiple scales, including the molecular scale, nano- and meso-scale (microfibril), and microscale (tissue level). A combination of advanced characterization tools is used in this study to better understand the effect of mechanical refining on the meso-scale microfibril assembly and the relationship between those meso-scale modifications and enzymatic hydrolysis. Results: Enzymatic conversion of autohydrolysis sugarcane bagasse was improved from 69.6 to 77.2% (11% relative increase) after applying mechanical refining and an increase in enzymatic digestibility is observed with an increase in refining intensity. Based on a combination of advanced characterizations employed in this study, it was found that the refining action caused fiber size reduction, internal delamination, and increase in pores and swellability. Conclusions: A higher level of delamination and higher increase in porosity, analyzed by TEM and DSC, were clearly demonstrated, which explain the faster digestibility rate during the first 72 h of enzymatic hydrolysis for disc-refined samples when compared to the PFI-refined samples. In addition, an increased inter-fibrillar distance between cellulose microfibrils at the nano–meso-scale was also revealed by SFG analysis, while no evidence was found for a change in crystalline structure by XRD and solid-state NMR analysis. [ABSTRACT FROM AUTHOR]

Pectins are abundant in the cell walls of dicotyledonous plants, but how they interact with other wall polymers and influence wall integrity and cell growth has remained mysterious. Here, we verified that QUASIMODO2 (QUA2) is a pectin methyltransferase and determined that QUA2 is required for normal pectin biosynthesis. To gain further insight into how pectin affects wall assembly and integrity maintenance, we investigated cellulose biosynthesis, cellulose organization, cortical microtubules, and wall integrity signaling in two mutant alleles of Arabidopsis (Arabidopsis thaliana) QUA2 , qua2 and tsd2. In both mutants, crystalline cellulose content is reduced, cellulose synthase particles move more slowly, and cellulose organization is aberrant. NMR analysis shows higher mobility of cellulose and matrix polysaccharides in the mutants. Microtubules in mutant hypocotyls have aberrant organization and depolymerize more readily upon treatment with oryzalin or external force. The expression of genes related to wall integrity, wall biosynthesis, and microtubule stability is dysregulated in both mutants. These data provide insights into how homogalacturonan is methylesterified upon its synthesis, the mechanisms by which pectin functionally interacts with cellulose, and how these interactions are translated into intracellular regulation to maintain the structural integrity of the cell wall during plant growth and development. [ABSTRACT FROM AUTHOR]

In this study, ten strains of lactic acid bacteria were isolated from the intestine of Blainville's beaked whale (Mesoplodon densirostris),and their cholesterol-lowering activities in vitro and in vivo were investigated. The among these strains, HJ-S2 strain, which identified as Lactiplantibacillus plantarum, showed a high in vitro cholesterol-lowering rate (48.82%). Strain HJ-S2 was resistant to acid and bile salts, with a gastrointestinal survival rate of more than 80%, but was sensitive to antibiotics. Strain HJ-S2 was found to be able to adhere to HT-29 cells in an adhesion test. The number of cell adhesion was 132.52. In addition, we also performed the cholesterol-lowering activities in vivo using high-fat diet feed mouse models. Our results indicated that HJ-S2 reduced total cholesterol (TC), total glycerol (TG), and low-density lipoprotein cholesterol (LDLC) levels while increasing the high-density lipoprotein cholesterol (HDLC) level. It also alleviated the lipid accumulation in high-fat diet feed mouse liver and pancreas. Hence, HJ-S2 demonstrated appropriate cholesterol-lowering ability and has the potential to be used as a probiotic in functional foods. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial resistance (AMR) is one of the greatest threats to animal and public health. Here, we conducted a dynamic surveillance of Escherichia coli on Chongming Island in Shanghai during 2009–2021 to identify the characteristics and trends of Chongming's AMR pandemic. Methods: Rectal (cloaca) swabs from four poultry and nine swine farms (Chongming Island, 2009–2021) were collected for E. coli strains acquisition. The micro-broth dilution method was used to test antimicrobial susceptibility of E. coli isolates against 10 antimicrobial classes including 15 antimicrobials. Utilizing generalized linear mixed models (GLMMs) and co-occurrence analyses, we further explored the multiple-drug-resistance (MDR) combinations and dynamic patterns of E. coli over 10 years in two food animals. Results: Total of 863 MDR isolates were found among 945 collected E. coli isolates, 337 from poultry and 608 from swine. Both isolates exhibited high resistant rates (> 70%) to tetracyclines, phenicols, sulfonamides, penicillins, and aminoglycosides (only in swine). The resistant rates of swine isolates to penicillins, aminoglycosides, tetracyclines, phenicols, and polymyxins were significantly higher than those of poultry isolates, whereas resistance to fluoroquinolones was reversed. Resistance to polymyxins decreased similarly in swine (42.4% in 2009 to 0.0% in 2021) and poultry isolates (from 16.5% to 0.0%). However, resistance to other seven antimicrobial classes (excluding carbapenems and penicillins) declined dramatically in swine isolates, particularly fluoroquinolones (from 80.5% to 14.4%), and tendencies of resistance to the seven classes showed markedly divergent patterns in poultry isolates. Using Poisson GLMMs, the AMR carriage since 2016 was significantly lower than that of 2009 (odds ratio < 1), indicating a decline in the risk of MDR emergence. Furthermore, despite the highly diverse MDR profiles, co-occurrence analysis identified two prominent MDR clusters of penicillins-phenicols-fluoroquinolones in poultry and aminoglycosides-tetracyclines-sulfonamides-phenicols in swine. Conclusions: Our study uncovered vastly distinct AMR patterns and dynamic tendencies of poultry and swine E. coli isolates from Chongming. Meanwhile, Chongming's AMR status has ameliorated, as indicated by the decline in antimicrobials prevalence (particularly in swine), lower likelihood of MDR emergence and low carbapenem-, cephalosporin-, and polymyxin resistance. Importantly, this surveillance results are the vital basis for future policy development in Chongming and Shanghai. [ABSTRACT FROM AUTHOR]

Abstract: Three-component hybrid membranes comprising Pebax, poly (ethylene glycol) (PEG)-based polymers and multi-walled carbon nanotube (MWCNT) were prepared by simple physical mixing of Pebax solution and MWCNT-containing PEG-based polymer solution. Scanning electron microscope (SEM) images showed an improved dispersion of MWCNT within polymer matrix arisen from the hydrophilic modification of PEG-based polymers. The embedded MWCNT disrupted the polymer chain packing and decreased polymer crystallinity, which was confirmed by X-ray diffraction. Influences of PEG-based polymer type on CO2, N2 and CH4 permeations were investigated: incorporating high molecular weight PEG-based polymers favored CO2/CH4 separation, while incorporating low molecular weight PEG-based polymers favored CO2/N2 separation. All the hybrid membranes displayed enhanced CO2 permeability owing to the increased amorphous phase. With the incorporation of MWCNT, CO2/CH4 selectivity was decreased for the enhanced chain mobility, while CO2/N2 selectivity was increased for the increased amorphous PEO content. In particular, for P-PEGDME(40)–CNT(5) membrane, a CO2/N2 mixed gas selectivity of 108 and CO2 permeability up to 743Barrer at 10bar and room temperature were acquired, which showed promising prospect for CO2 capture. [Copyright &y& Elsevier]

It is of great significance to establish an assessment model for organ failures in the early stage of admission in acute pancreatitis (AP). And the clinical notes are underutilized. To predict organ failures for AP patients using early clinical notes in hospital, early text features obtained from the pretrained Chinese Bidirectional Encoder Representations from Transformers model and attention-based LSTM were combined with early structured features (laboratory tests, vital signs, and demographic characteristics) to predict organ failures (respiratory, cardiovascular, and renal) in 12,748 AP inpatients in West China Hospital, Sichuan University, from 2008 to 2018. The text plus structured features fusion model was used to predict organ failures, compared to the baseline model with only structured features. The performance of the model with text features added is superior to the model that only includes structured features. [ABSTRACT FROM AUTHOR]

Background: Recent studies show that contrast-enhanced ultrasonography (CEUS) using SonoVue has the potential to improve the performance of sentinel lymph node biopsy (SLNB) in patients with early breast cancer. However, the evidence of SLNB using CEUS in patients converting from cN1 to cN0 after neoadjuvant chemotherapy (NAC) is lacking. The aim of this prospective study is to evaluate the feasibility of CEUS using SonoVue for the identification of sentinel lymph node (SLN) and the value of the combination of CEUS and blue dye (BD) for SLNB in patients converting from cN1 to cN0 following NAC.Methods: Patients with cytology-proven node positive breast cancer at the initial diagnosis (stage T1-T3N1M0) from January 2018 to January 2019, underwent NAC. Patients converting from cN1 to cN0 following NAC were enrolled and randomized into two groups for SLNB: the combination method group using CEUS and BD together, and the single BD method group. Then all patients underwent complete axillary lymph node dissection (ALND) and primary breast surgery. Compared with the final pathological results, the identification rate, sensitivity, specificity, accuracy, false negative rate, negative predictive value, positive predictive value were recorded and compared between two methods.Results: A total of 400 patients with stage T1-T3N1M0 disease underwent NAC between January 2018 to January 2019, among which 134 (33.5%) patients had clinically negative node confirmed by imaging after NAC and randomized into two groups. Each group included 67 cases. In the combination method group, contrast-enhanced lymphatic vessels in 66 cases of 67 were clearly visualized by US soon after the periareolar injection of SonoVue and the SLNs were accurately localized. The identification rate of the combination method was 98.5%%, which was significantly higher than 83.6% (56/67) using the single BD method. The mean numbers of SLNs identified by the combination method was higher than that by the single BD method. Compared with pathological diagnosis, sensitivity, specificity, accuracy, the positive predictive value, the negative predictive value, and the FNR of the combingation method were 84.4%, 100%, 89.4%, 100%, 75%, and 15.6%, respectively. In contrast, sensitivity, specificity, accuracy, the positive predictive value, the negative predictive value, and the FNR using single blue dye were 73.9%, 100%, 89.3%, 100%, 84.6%, and 26.1%, respectively. The FNR using the combination method was significantly lower than that using single BD.Conclusion: Identification of SLNs in patients converting from cN1 to cN0 following NAC by CEUS is a technically feasible. The combination of CEUS and BD is more effective than BD alone for SLNB in patients converting from cN1 to cN0 following NAC. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus (S. aureus) is a major cause of foodborne infections and its persistence in raw milk is a multifaceted phenomenon that poses a considerable public health challenge. Our study investigated the prevalence, virulence genes, antibiotic resistance, and genetic characterization of S. aureus in raw milk in six Shanghai districts from 2013 to 2022. At 18 dairy farms, a total of 704 S. aureus strains were isolated from 1799 samples tested for drug sensitivity. The highest rates of antibiotic resistance were ampicillin (96.7 %), sulfamethoxazole (65 %), and erythromycin (21.6 %). Between 2018 and 2022, there was a significant decrease in the resistance rates of ceftiofur, ofloxacin, tilmicosin, erythromycin, clindamycin, amoxicillin-clavulanic acid, and sulfamethoxazole in comparison to the period from 2013 to 2017. There were 205 S. aureus strains chosen for whole genome sequencing (WGS), with no more than 2 strains of the same resistance phenotype from each farm per year. The prevalence of mecA -positive strains was 14.15 %, while other antibiotic resistance-associated genes were observed as follows: blaI (70.21 %), lnu (B) (5.85 %), lsa (E) (5.75 %), fexA (6.83 %), erm (C) (4.39 %), tet (L) (9.27 %), and dfrG (5.85 %). Isolates harboring the immune evasion cluster (IEC) genes (scn , chp , and sak) were predominantly categorized as sequence types (STs) 7, 188, 15, 59, and 398. The predominant cluster complexes were CC97, CC1, CC398, and CC1651. In 2017–2022, there was a transition in CC1 from the highly antibiotic-resistant ST9 strain that emerged between 2013 and 2018 to the low-resistant but highly virulent ST1 strain. Retrospective phylogenetic analysis elucidated the evolutionary history of the isolates and demonstrated that the human-animal host transition of S. aureus was linked to the genesis of MRSA CC398. The implementation of extended surveillance will aid in the development of innovative strategies to avoid the transmission of S. aureus along the dairy food chain and the occurrence of public health events. [Display omitted] • A ten-year investigation of the genomic characteristics of S. aureus from raw milk. • Resistance to six antibiotics reduced substantially in dairy-derived S. aureus. • Virulent ST1 strains have gradually replaced the resistant ST9 and ST188 in CC1. • Host-switching events between animals and humans led to the emergence of MRSA CC398. [ABSTRACT FROM AUTHOR]

• Sedimentary biomarkers allow to assess long-term trajectory and variability of CyanoHABs. • Synergistic effects of eutrophication and climate change sustain bloom-forming potential. • Toxic HABs increase in Lake Taihu mainly attributed to regional warming. • Booming algal variability predicts ecosystem resilience loss with risk of catastrophic shifts. • Mitigating climate change is increasingly important to reverse HABs and their detriments. Harmful algal blooms (HABs) producing toxic metabolites are increasingly threatening environmental and human health worldwide. Unfortunately, long-term process and mechanism triggering HABs remain largely unclear due to the scarcity of temporal monitoring. Retrospective analysis of sedimentary biomarkers using up-to-date chromatography and mass spectrometry techniques provide a potential means to reconstruct the past occurrence of HABs. By combining aliphatic hydrocarbons, photosynthetic pigments, and cyanotoxins, we quantified herein century-long changes in abundance, composition, and variability of phototrophs, particularly toxigenic algal blooms, in China's third largest freshwater Lake Taihu. Our multi-proxy limnological reconstruction revealed an abrupt ecological shift in the 1980s characterized by elevated primary production, Microcystis -dominated cyanobacterial blooms, and exponential microcystin production, in response to nutrient enrichment, climate change, and trophic cascades. The empirical results from ordination analysis and generalized additive models support climate warming and eutrophication synergy through nutrient recycling and their feedback through buoyant cyanobacterial proliferation, which sustain bloom-forming potential and further promote the occurrence of increasingly-toxic cyanotoxins (e.g., microcystin-LR) in Lake Taihu. Moreover, temporal variability of the lake ecosystem quantified using variance and rate of change metrics rose continuously after state change, indicating increased ecological vulnerability and declined resilience following blooms and warming. With the persistent legacy effects of lake eutrophication, nutrient reduction efforts mitigating toxic HABs probably be overwhelmed by climate change effects, emphasizing the need for more aggressive and integrated environmental strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

• We develop an integrated method for assessing lake ecosystem health. • Lake ecosystem degradation shows clear spatial heterogeneity patterns in East China. • Identifying the nonlinear contribution of multiple stressors to lake degradation. • Lake ecosystem health is significantly influenced by its distance from the city. Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China's most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems. [ABSTRACT FROM AUTHOR]

Practical implementation of periodate-based advanced oxidation processes for environmental remediation largely relies on the development of cost-effective and high-performance activators. Surface atomic engineering toward these activators is desirable but it remains challenging to realize improved activation properties. Here, a surface atomic engineering strategy used to obtain a novel hybrid activator, namely cobalt-coordinated nitrogen-doped graphitic carbon nanosheet-enwrapped cobalt nanoparticles (denoted as Co@NC-rGO), from a sandwich-architectured metal–organic framework/graphene oxide composite is reported. This activator exhibits prominent periodate activation properties toward pollutant degradation, surpassing previously reported transition-metal-based activators. Importantly, the activator shows good stability, magnetic reusability, and the potential for application in a complex water matrix. Density functional theory modeling implies that the strong activation capability of Co@NC-rGO is related to its surface atomic structure for which the embedded cobalt nanoparticles with abundant interfacial Co–N coordinations display modified electronic configurations on the active centers and benefit periodate adsorption. Quenching experiments and electrochemical measurements showed that the system could oxidize organics through a dominant nonradical pathway. Additionally, a lower concentration of cobalt leaching was observed for the Co@NC-rGO/periodate system than for its Co@NC-rGO/persulfate counterpart. Our work provides a pathway toward engineering surface atomic structures in hybrid activators for efficient periodate activation. [Display omitted] • A surface atomic structure engineering strategy was proposed. • The achieved Co@NC-rGO could effectively activate periodate. • Modulated electronic structure of active sites benefited the activation process. • Nonradical pathway via the electron-transfer regime was elucidated. [ABSTRACT FROM AUTHOR]

The prevalence of juvenile Pacific abalone disease without apparent external lesions in the Chinese province of Fujian has led to mass mortality in 2018. A novel method for screening abalone pathogen was developed based on the importance of mucus in innate immunity. We identified the pathogenic bacterial strain of abalone by bacterial isolation, sequence analysis, and experimental challenges in vitro and in vivo. We verified that the abalone mortality rates were high when exposed to Pseudoalteromonas shioyasakiensis strain SDCH87 at 28 °C. This opportunistic pathogen had an outstanding growth ability in mucus and disrupted the first line mucosal immunity in the pedal within three days. To our knowledge, this is the first report that P. shioyasakiensis is a severe opportunistic pathogen of abalone, which indicated pedal was the lesion, in the context of a heatwave. • A novel method was developed for screening abalone pathogens, based on the important role of mucus in the innate immunity. • P. shioyasakiensis strain SDCH87 is a significant opportunistic pathogen of abalone during a record-breaking heatwave. • Histopathology and the distribution of bacterial strains indicated pedal was the lesion. [ABSTRACT FROM AUTHOR]