UV-aging reduces the effects of biodegradable microplastics on soil sulfamethoxazole degradation and sul genes development.

In recent years, the biodegradable plastics has extensively used in industry, agriculture, and daily life. Herein, the effects of two biodegradable microplastics (BMPs), poly(butyleneadipate-co-terephthalate) (PBAT) and polyhydroxyalkanoate (PHA), on soil sulfamethoxazole (SMX) degradation and sul genes development were comparatively studied based on the type, dosage, and state. The addition of virgin BMPs significantly increased soil DOC following a sequential order PBAT > PHA and high dose > low dose. Meanwhile virgin PBAT significantly reduced soil pH. In general, the addition of BMPs not only promoted soil SMX degradation but also increased the abundance of sul genes, with an exception that pH reduction in virgin PBAT inhibited the proliferation of sul genes. The driving effects of BMPs on soil microbial diversity following the same order as that on DOC. Specific bacteria stimulated by BMPs, such as Arthrobacter and two genera affiliated with phylum TM7, accounted for the accelerated degradation of SMX. Intriguingly, UV-aging hindered the release of DOC from BMPs and the reduction in pH, mitigated the stimulation of microbial communities, and ultimately reduced the promotion effect of BMPs on SMX degradation and sul genes proliferation. Our results suggest that more attention should be paid to the proliferation risk of ARGs in the environment affected by BMPs and UV-aging can be employed sometimes to reduce this risk.

Enhancing Two-Photon Excited Fluorescence of Metal-Organic Framework Single Crystals through Modulation of Inorganic Nodes.

Regulation of the two-photon excited fluorescence (TPEF) emission intensity and wavelength of metal-organic framework (MOF) crystals with similar constitutions presents a significant challenge. In this study, two MOFs, Zn-BTPPA and Cd3-BTPPA, were constructed using tetrakis(1,1'-biphenyl-4-carboxylic acid)-1,4-benzenediamine (H4BTPPA) as the organic ligand and mononuclear Zn and trinuclear Cd3 inorganic nodes, respectively. The incorporation of H4BTPPA within the MOF structures enables effective TPEF emission in both Zn-BTPPA and Cd3-BTPPA. The TPEF results show that Zn-BTPPA and Cd3-BTPPA exhibited strong emissions at 523 and 463 nm, respectively, when excited with a 780 nm laser. Moreover, Zn-BTPPA and Cd3-BTPPA exhibited much higher two-photon absorption cross sections, approximately 4.9 and 5.2 times higher than that of the reported dinuclear MOF, Cd2-BTPPA, with a similar composition, respectively. With different inorganic nodes, the stacking of chromophores, π···π interactions, and ligand geometry were found to correlate with the enhanced TPEF in Cd3-BTPPA and the blue-shifted TPEF in Zn-BTPPA. This work serves as an inspiration for designing efficient TPEF MOF materials based on the structure-property relationship.

Efficient elimination of antibiotics and antibiotic resistance genes in hyperthermophilic sludge composting.

Composting is widely applied in recycling ever-increasing sewage sludge. However, the insufficient elimination of antibiotics and antibiotic resistance genes (ARGs) in conventional compost fertilizer poses considerable threat to agriculture safety and human health. Here we investigated the efficacy and potential mechanisms in the removal of antibiotics and ARGs from sludge in hyperthermophilic composting (HTC) plant. Our results demonstrated that the HTC product was of high maturity. HTC led to complete elimination of antibiotics and potential pathogens, as well as removal of 98.8 % of ARGs and 88.1 % of mobile genetic elements (MGEs). The enrichment of antibiotic-degrading candidates and related metabolic functions during HTC suggested that biodegradation played a crucial role in antibiotic removal. Redundancy analysis (RDA) and structural equation modelling (SEM) revealed that the reduction of ARGs was attributed to the decline of ARG-associated bacteria, mainly due to the high-temperature selection. These findings highlight the feasibility of HTC in sludge recycling and provide a deeper understanding of its mechanism in simultaneous removal of antibiotics and ARGs.

Health impact of rotavirus vaccination in China.

Rotavirus (RV) vaccines have demonstrated substantial effectiveness in reducing the healthcare burden caused by gastroenteritis (RVGE) worldwide. This study aims to understand the differential impact of RV vaccination in reducing RVGE burden in children under 7 years old in China. A Markov Model was used to investigate the health impact of introducing two different RV vaccines into the Chinese population. The analysis was conducted for RV5, a live pentavalent human-bovine reassortant vaccine, and Lanzhou Lamb RV (LLR), a live-attenuated monovalent RV vaccine, separately, by comparing the strategy of each vaccine to no vaccination within a Chinese birth cohort, including 100,000 children modeled until 7 years of age. The vaccination scenario assumed a vaccination coverage of 2.5%, 2.5%, 90% and 5% for doses one, two, three and no vaccine, respectively, for both vaccines. Strategies with RV5, LLR, and no vaccination were associated with 9,895, 49,069, and 64,746 symptomatic RV infections, respectively. RV5 and LLR were associated with an 85% and 24% reduction in the total symptomatic RV infections, respectively, suggesting that the health benefits of RV5 are at least three-fold greater than those associated with the LLR. Further, strategies with RV5 and LLR resulted in an estimated 206 and 59-year increase in quality-adjusted life years (QALYs), respectively. Sensitivity and scenario analyses supported the robustness of the base-case findings. Use of RV vaccine is expected to improve RV-associated health outcomes and its adoption will help alleviate the burden of RVGE in China. RV5 use will result in significantly better health outcomes.

Integrating Multiple Redox-Active Units into Conductive Covalent Organic Frameworks for High-Performance Sodium-Ion Batteries.

The rational design of porous covalent organic frameworks (COFs) with high conductivity and reversible redox activity is the key to improving their performance in sodium-ion batteries (SIBs). Herein, we report a series of COFs (FPDC-TPA-COF, FPDC-TPB-COF, and FPDC-TPT-COF) based on an organosulfur linker, (trioxocyclohexane-triylidene)tris(dithiole-diylylidene))hexabenzaldehyde (FPDC). These COFs feature two-dimensional crystalline structures, high porosity, good conductivity, and densely packed redox-active sites, making them suitable for energy storage devices. Among them, FPDC-TPT-COF demonstrates a remarkably high specific capacity of 420 mAh g-1 (0.2 A g-1), excellent cycling stability (~87% capacity retention after 3000 cycles, 1.0 A g-1) and high rate performance (339 mAh g-1 at 2.0 A g-1) as an anode for SIBs, surpassing most reported COF-based electrodes. The superior performance is attributed to the dithiole moieties enhancing the conductivity and the presence of redox-active carbonyl, imine, and triazine sites facilitating Na storage. Furthermore, the sodiation mechanism was elucidated through in-situ experiments and density functional theory (DFT) calculations. This work highlights the advantages of integrating multiple functional groups into redox-active COFs for the rational design of efficient and stable SIBs.

Revealing the Dark Side of Non-Local Attention in Single Image Super-Resolution.

Single Image Super-Resolution (SISR) aims to reconstruct a high-resolution image from its corresponding low-resolution input. A common technique to enhance the reconstruction quality is Non-Local Attention (NLA), which leverages self-similar texture patterns in images. However, we have made a novel finding that challenges the prevailing wisdom. Our research reveals that NLA can be detrimental to SISR and even produce severely distorted textures. For example, when dealing with severely degrade textures, NLA may generate unrealistic results due to the inconsistency of non-local texture patterns. This problem is overlooked by existing works, which only measure the average reconstruction quality of the whole image, without considering the potential risks of using NLA. To address this issue, we propose a new perspective for evaluating the reconstruction quality of NLA, by focusing on the sub-pixel level that matches the pixel-wise fusion manner of NLA. From this perspective, we provide the approximate reconstruction performance upper bound of NLA, which guides us to design a concise yet effective Texture-Fidelity Strategy (TFS) to mitigate the degradation caused by NLA. Moreover, the proposed TFS can be conveniently integrated into existing NLA-based SISR models as a general building block. Based on the TFS, we develop a Deep Texture-Fidelity Network (DTFN), which achieves state-of-the-art performance for SISR. Our code and a pre-trained DTFN are available on GitHub for verification.

Protists and fungi: Reinforcing urban soil ecological functions against flash droughts.

Rising instances of flash droughts are contributing to notable variability in soil moisture across terrestrial ecosystems. These phenomena challenge urban ecosystem services, yet the reaction of soil ecological functions (SEFs) to such events is poorly understood. This study investigates the responses of SEFs (about nutrient metabolism capacity and potential) and the microbiome under two specific scenarios: a flooding-drought sequence and a direct drought condition. Using quantitative microbial element cycling analysis, high-throughput sequencing, and enzyme activity measurements, we found that unlike in forests, the microbial composition in urban soils remained unchanged during flash drought conditions. However, SEFs were affected in both settings. Correlation analysis and Mantel test showed that forest soils exhibited more complex interactions among soil moisture, properties, and microbial communities. Positive linear correlation revealed that bacteria were the sole drivers of SEFs. Interestingly, while multi-threshold results suggested bacterial α diversity impeded the maximization of SEFs in urban soils, fungi and protists had a beneficial impact. Cross-domain network of urban soils had higher number of nodes and edges, but lower average degree and robustness than forest soils. Mantel test revealed that fungi and protist had significant correlations with bacterial composition in forest soils, but not in urban soils. In the urban network, the degree and eigenvector centrality of bacterial, fungal and protistan ASVs were significantly lower compared to those in the forest. These results suggest that the lower robustness of the microbial network in urban soils is attributed to limited interactions among fungi, consumer protists, and bacteria, contributing to the failure of microbial-driven ecological functions. Overall, our findings emphasize the critical role of fungi and protists in shielding urban soils from drought-induced disturbances and in enhancing the resistance of urban ecological functions amidst environmental changes.

Gene expression and brain imaging association study reveals gene signatures in major depressive disorder.

Major depressive disorder is often characterized by changes in the structure and function of the brain, which are influenced by modifications in gene expression profiles. How the depression-related genes work together within the scope of time and space to cause pathological changes remains unclear. By integrating the brain-wide gene expression data and imaging data in major depressive disorder, we identified gene signatures of major depressive disorder and explored their temporal-spatial expression specificity, network properties, function annotations and sex differences systematically. Based on correlation analysis with permutation testing, we found 345 depression-related genes significantly correlated with functional and structural alteration of brain images in major depressive disorder and separated them by directional effects. The genes with negative effect for grey matter density and positive effect for functional indices are enriched in downregulated genes in the post-mortem brain samples of patients with depression and risk genes identified by genome-wide association studies than genes with positive effect for grey matter density and negative effect for functional indices and control genes, confirming their potential association with major depressive disorder. By introducing a parameter of dispersion measure on the gene expression data of developing human brains, we revealed higher spatial specificity and lower temporal specificity of depression-related genes than control genes. Meanwhile, we found depression-related genes tend to be more highly expressed in females than males, which may contribute to the difference in incidence rate between male and female patients. In general, we found the genes with negative effect have lower network degree, more specialized function, higher spatial specificity, lower temporal specificity and more sex differences than genes with positive effect, indicating they may play different roles in the occurrence and development of major depressive disorder. These findings can enhance the understanding of molecular mechanisms underlying major depressive disorder and help develop tailored diagnostic and treatment strategies for patients of depression of different sex.

Unveiling the overlooked small-sized microbiome in river ecosystems.

Enriching microorganisms using a 0.22-µm pore size is a general pretreatment procedure in river microbiome research. However, it remains unclear the extent to which this method loses microbiome information. Here, we conducted a comparative metagenomics-based study on microbiomes with sizes over 0.22 µm (large-sized) and between 0.22 µm and 0.1 µm (small-sized) in a subtropical river. Although the absolute concentration of small-sized microbiome was about two orders of magnitude lower than that of large-sized microbiome, sequencing only large-sized microbiome resulted in a significant loss of microbiome diversity. Specifically, the microbial community was different between two sizes, and 347 genera were only detected in small-sized microbiome. Small-sized microbiome had much more diverse viral community than large-sized fraction. The viruses had abundant ecological functions and were hosted by 825 species of 169 families, including pathogen-related families. Small-sized microbiome had distinct antimicrobial resistance risks from large-sized microbiome, showing an enrichment of eight antibiotic resistance gene (ARG) types as well as the detection of 140 unique ARG subtypes and five enriched risk rank I ARGs. Draft genomes of five major resistant pathogens having diverse ecological and pollutant-degrading functions were only assembled in small-sized microbiome. These findings provide novel insights into river ecosystems, and highlight the overlooked small-sized microbiome in the environment.

Designing photothermal catalytic systems in multi-component MOFs for enhanced conversion of carbon dioxide.

We integrated a pair of donor-acceptor photothermal units, a Lewis acidic site, and a nucleophilic catalytic site into a multi-component metal-organic framework, resulting in an efficient photothermal catalytic system for the conversion of CO2 to cyclic carbonates.

Association of Questionnaire-Based Physical Activity Analysis and Body Composition Dynamics in Type 2 Diabetes: A Cross-Sectional Study.

Background: Physical activity (PA) exerts an important influence on glycemic control in type 2 diabetes (T2D) patients. Alterations in body composition in patients with T2D may be involved in the overall pathophysiologic process, but PAs and alterations in body composition have been poorly studied. Methods: A total of 615 patients with T2D were selected by convenient sampling. The patients were investigated with the International Physical Activity Questionnaire (IPAQ-S). Moreover, biochemical indices were collected, and the progression of the body composition of the subjects was determined via dual-energy X-ray absorptiometry (DXA). The variables included lumbar bone mineral density (LSBMD), femoral neck bone mineral density (FNBMD), hip bone mineral density (HBMD), whole-body bone mineral density (TBMD), limb skeletal muscle mass index (ASMI), whole-body fat percentage (B-FAT) and trunk fat percentage (T-FAT). Moreover, the levels of physical activity (high level of physical activity [H-PA], medium level of physical activity [M-PA] and low level of physical activity [L-PA]) were divided into three groups to analyze the changes in patient body composition with changes in physical activity level. Results: One-way analysis of variance showed that ß-CTX, TP1NP, HbA1c, B-FAT and T-FAT increased significantly (p<0.05), while 25(OH)D, LSBMD, FNBMD, HBMD, TBMD and ASMI decreased significantly (p<0.001) with the decrease of physical activity. However, there was no significant difference in serum lipids between lnHOMA-ir and lnHOMA-ß (p>0.05). Multiple linear regression model was established to gradually adjust for clinical confounding factors. It was found that physical activity level was independently positively correlated with LSBMD, FNBMD, HBMD, TBMD, and ASMI, and was independently negatively correlated with B-FAT and T-FAT in patients with type 2 diabetes. Conclusion: A lack of physical activity is an independent risk factor for decreased bone mineral density, decreased skeletal muscle content and increased fat content in patients with T2D.

[In-Vitro Analysis of Polyethylene Liner Wear Performance at 3 and 5 Million Cycles].

Objective: The purpose of this study is to compare the wear properties of UHMWPE acetabular liners after undergoing 3 million (3 Mc) and 5 million (5 Mc) cycles of in-vitro wear testing. The results will serve as a reference for the design of in-vitro testing for hip prostheses and as a control for clinical revision removals. Methods: Wear tests were conducted on three different sizes of acetabular liners (28 mm, 32 mm, and 36 mm internal diameters) using a hip simulator to determine the amount of wear after 3 and 5 million cycles. The analysis included the number, size, and shape of abrasive particles. Results: After 3 and 5 million cycles of wear, the amount of wear on the acetabular liner increased as the inner diameter increased. The abrasive particles had an average equivalent circular area diameter (ECD) of 0.27 µm and 0.29 µm, and 94.4% and 90.1% of the aspect ratio (AR) less than 4. Conclusion: The amount of wear on the acetabular liner after 3 Mc wear can indicate the wear performance of the product. The number of particles increased and the percentage of fibrous particles was higher after 5 Mc wear compared to 3 Mc wear.

Consensus of the Taiwanese dermatological association and Taiwan Lung Cancer Society on the prevention and management of tyrosine kinase inhibitor-related skin toxicities in patients with non-small cell lung cancer: An updated version incorporating Taiwanese treatment experience.

The 2023 consensus from the Taiwanese Dermatological Association (TDA) and Taiwan Lung Cancer Society (TLCS) addresses the management of tyrosine kinase inhibitor (TKI)-induced skin toxicities in non-small cell lung cancer (NSCLC). Providing a comprehensive overview, the consensus reflects recent advances in understanding causes and developmental processes of TKI-related skin toxicities. Aimed at guiding clinicians in Taiwan, the consensus integrates new treatment perspectives while incorporating experiences from local dermatology experts. Recommendations underwent a voting process, achieving consensus when 75% or more of experts agreed, leading to their inclusion. Approved by over 90% of participants, the recommended treatment algorithms for major skin toxicities offer valuable insights for clinicians managing TKI-associated effects in NSCLC patients.

Energy-Efficient Reservoir Computing Based on Solution-Processed Electrolyte/Ferroelectric Memcapacitive Synapses for Biosignal Classification.

The classification of critical physiological signals using neuromorphic devices is essential for early disease detection. Physical reservoir computing (RC), a lightweight temporal processing neural network, offers a promising solution for low-power, resource-constrained hardware. Although solution-processed memcapacitive reservoirs have the potential to improve power efficiency as a result of their ultralow static power consumption, further advancements in synaptic tunability and reservoir states are imperative to enhance the capabilities of RC systems. This work presents solution-processed electrolyte/ferroelectric memcapacitive synapses. Leveraging the synergistic coupling of electrical double-layer (EDL) effects and ferroelectric polarization, these synapses exhibit tunable long- and short-term plasticity, ultralow power consumption (∼27 fJ per spike), and rich reservoir state dynamics, making them well-suited for energy-efficient RC systems. The classifications of critical electrocardiogram (ECG) signals, including arrhythmia and obstructive sleep apnea (OSA), are performed using the synapse-based RC system, demonstrating excellent accuracies of 97.8 and 80.0% for arrhythmia and OSA classifications, respectively. These findings pave the way for developing lightweight, energy-efficient machine-learning platforms for biosignal classification in wearable devices.

Associations between perceived care quality, self-care behaviors, and glycemic control in Chinese adults with type 2 diabetes under the national essential public health services program.

BACKGROUND: The rising prevalence of Type 2 diabetes (T2D) in China poses a critical health challenge, necessitating effective management strategies. The National Essential Public Health Services Program (NEPHSP), initiated in 2009, focuses on equitable access to health services, including T2D management. This study investigates the associations between perceived care quality, self-care behaviors, and glycemic control in Chinese adults with T2D under NEPHSP, particularly examining the mediating role of self-care behaviors. METHODS: Conducted from April to November 2020 in Huai'an City, Jiangsu Province, this study involved 1,577 T2D patients enrolled in NEPHSP. We assessed perceived care quality using the Patient Assessment of Chronic Illness Care (PACIC) scale and developed a comprehensive self-care behavior score, covering nine essential health practices. Glycemic control was evaluated using HbA1c levels. Linear regression models were used to explore these associations, adjusting for demographic and clinical factors, while causal mediation analyses examined the role of intermediate variables. RESULTS: Higher PACIC scores significantly correlated with improved self-care behaviors (ß = 0.294, 95% CI: 0.233 to 0.354) and were negatively associated with HbA1c levels (ß=-0.109, 95% CI: -0.192 to -0.026). The self-care behavior score inversely related to HbA1c levels (ß=-0.197, 95% CI: -0.263 to -0.132). Notably, self-care behaviors mediated 50.41% (P < 0.05) of the effect of perceived care quality on HbA1c levels. CONCLUSIONS: This study demonstrates a substantial association between perceived care quality and better glycemic control in Chinese adults with T2D under NEPHSP, with self-care behaviors playing a crucial mediating role. These findings suggest that patient-centered care and comprehensive self-care practices are essential for effective T2D management within NEPHSP.

Polynuclear Cobalt Cluster-Based Coordination Polymers for Efficient Nitrate-to-Ammonia Electroreduction.

The electrocatalytic nitrate reduction reaction (NITRR) holds great promise for purifying wastewater and producing valuable ammonia (NH3). However, the lack of efficient electrocatalysts has impeded the achievement of highly selective NH3 synthesis from the NITRR. In this study, we report the design and synthesis of two polynuclear Co-cluster-based coordination polymers, {[Co2(TCPPDA)(H2O)5]·(H2O)9(DMF)} and {Co1.5(TCPPDA)[(CH3)2NH2]·(H2O)6(DMF)2} (namely, NJUZ-2 and NJUZ-3), which possess distinct coordination motifs with well-defined porosity, high-density catalytic sites, accessible mass transfer channels, and nanoconfined chemical environments. Benefitting from their intriguing multicore metal-organic coordination framework structures, NJUZ-2 and NJUZ-3 exhibit remarkable catalytic activities for the NITRR. At a potential of -0.8 V (vs. RHE) in an H-type cell, they achieve an optimal Faradaic efficiency of approximately 98.5% and high long-term durability for selective NH3 production. Furthermore, the electrocatalytic performance is well maintained even under strongly acidic conditions. When operated under an industrially relevant current density of 469.9 mA cm-2 in a flow cell, a high NH3 yield rate of up to 3370.6 mmol h-1 g-1cat. was observed at -0.5 V (vs. RHE), which is 20.1-fold higher than that obtained in H-type cells under the same conditions. Extensive experimental analyses, in combination with theoretical computations, reveal that the great enhancement of the NITRR activity is attributed to the preferential adsorption of NO3- and the reduction in energy input required for the hydrogenation of *NO3 and *NO2 intermediates.

A seasonal study on the microbiomes of Diploid vs. Triploid eastern oysters and their denitrification potential.

Oyster reefs are hotspots of denitrification mediated removal of dissolved nitrogen (N), however, information on their denitrifier microbiota is scarce. Furthermore, in oyster aquaculture, triploids are often preferred over diploids, yet again, microbiome differences between oyster ploidies are unknown. To address these knowledge gaps, farmed diploid and triploid oysters were collected over an annual growth cycle and analyzed using shotgun metagenomics and quantitative microbial elemental cycling (QMEC) techniques. Regardless of ploidy, Psychrobacter genus was abundant, with positive correlations found for genes of central metabolism, DNA metabolism, and carbohydrate metabolism. MAGs (metagenome-assembled genomes) yielded multiple Psychrobacter genomes harboring norB, narH, narI, and nirK denitrification genes, indicating their functional relevance within the eastern oysters. QMEC analysis indicated the predominance of carbon (C) and nitrogen (N) cycling genes, with no discernable patterns between ploidies. Among the N-cycling genes, the nosZII clade was overrepresented, suggesting its role in the eastern oyster's N removal processes.

High-risk ARGs (HRA) Chip: A high-throughput qPCR-based array for assessment of high-risk ARGs from the environment.

The global surge in antibiotic resistance genes (ARGs) presents a serious public health challenge. While methods like metagenomic analysis and qPCR arrays have been instrumental in investigating ARG distributions and dynamics, the vast diversity of ARGs often complicates effective monitoring and risk assessment. Here, we developed a High-Risk ARGs (HRA) chip based on high-capacity quantitative PCR array targeting previously identified high-risk ARGs. These ARGs are known to be prevalent in human-related environments, exhibit gene mobility, and are present in ESKAPE pathogens. The HRA chip include 101 primer sets and the 16S rRNA gene as a reference. These primer sets consist of 34 obtained from previous studies, and 67 newly designed primer sets which were validated in silico and experimentally. Absolute quantification of targeted ARGs is accomplished by generating standard curves for all ARGs with serially ten-fold diluted mixed plasmids containing targeted ARG sequences. The amplification efficiencies of all ARGs exceed 99% via plasmid template dilution tests, suggesting high reliability in quantification. The performance of HRA chip is further evaluated by practical applications in environmental samples from wastewater treatment plants (WWTPs) and soils with various land use types and fertilization regimes. The results indicate the dynamics of high-risk ARGs during wastewater treatment process, and reveal the profiles of soil high-risk ARGs which is distinct from those derived via metagenomic approaches. These findings highlight the potentials of HRA Chip in the evaluation of anthropogenic impacts on the environmental resistome with a more focused spectrum of high-risk ARGs. Overall, the HRA Chip emerges as a powerful and efficient high-throughput tool for rapid detection and quantification of high-risk ARGs, facilitating comprehensive profiling of high-risk resistomes in environmental samples which is essential for human health risk assessment of ARGs.

Construction of a redox-active metal-organic framework with an octanuclear lithium one-dimensional building block.

A stable lithium metal-organic framework, constructed using a redox-active N,N,N',N'-tetrakis(4-carboxyphenyl)-1,4-phenylenediamine linker and Li8 cluster-based one-dimensional rod secondary building unit, exhibits good stability and reversible redox activity. The Li8-MOF, which can be oxidized by AgNO3, has the potential to function as an electrochromic device, thereby advancing the development of smart MOF materials.

Effective type label-based synergistic representation learning for biomedical event trigger detection.

BACKGROUND: Detecting event triggers in biomedical texts, which contain domain knowledge and context-dependent terms, is more challenging than in general-domain texts. Most state-of-the-art models rely mainly on external resources such as linguistic tools and knowledge bases to improve system performance. However, they lack effective mechanisms to obtain semantic clues from label specification and sentence context. Given its success in image classification, label representation learning is a promising approach to enhancing biomedical event trigger detection models by leveraging the rich semantics of pre-defined event type labels. RESULTS: In this paper, we propose the Biomedical Label-based Synergistic representation Learning (BioLSL) model, which effectively utilizes event type labels by learning their correlation with trigger words and enriches the representation contextually. The BioLSL model consists of three modules. Firstly, the Domain-specific Joint Encoding module employs a transformer-based, domain-specific pre-trained architecture to jointly encode input sentences and pre-defined event type labels. Secondly, the Label-based Synergistic Representation Learning module learns the semantic relationships between input texts and event type labels, and generates a Label-Trigger Aware Representation (LTAR) and a Label-Context Aware Representation (LCAR) for enhanced semantic representations. Finally, the Trigger Classification module makes structured predictions, where each label is predicted with respect to its neighbours. We conduct experiments on three benchmark BioNLP datasets, namely MLEE, GE09, and GE11, to evaluate our proposed BioLSL model. Results show that BioLSL has achieved state-of-the-art performance, outperforming the baseline models. CONCLUSIONS: The proposed BioLSL model demonstrates good performance for biomedical event trigger detection without using any external resources. This suggests that label representation learning and context-aware enhancement are promising directions for improving the task. The key enhancement is that BioLSL effectively learns to construct semantic linkages between the event mentions and type labels, which provide the latent information of label-trigger and label-context relationships in biomedical texts. Moreover, additional experiments on BioLSL show that it performs exceptionally well with limited training data under the data-scarce scenarios.