Asymmetric Organocatalytic 1,3-Dipolar Cycloaddition of Azomethine Ylides with ß-Substituted Cyclic Enones.

The enantioselective and diastereoselective control of 1,3-dipolar cycloaddition reactions to ß-substituted cyclic enones has been developed. The 1,3-dipolar cycloaddition of phthalazinium dicyanomethanides with cyclic dienones affords chiral tetrahydropyrrolo[2,1-a]phthalazine derivatives 3 through vinylogous iminium ion activation by combining a cinchona-based primary amine C3 and a chiral camphorsulfonic acid additive. Conversely, with a weaker 3,5-bis(trifluoromethyl)benzoic acid additive, the 1,3-dipolar cycloaddition of phthalazinium dicyanomethanides with ß-substituted cyclic enones leads to chiral hexahydroisoindolo[1,2-a]phthalazin-10(8H)-one derivatives 4 with excellent stereocontrol via endo-dienamine activation.

CFINet: Cross-Modality MRI Feature Interaction Network for Pseudoprogression Prediction of Glioblastoma.

Pseudoprogression (PSP) is a related reaction of glioblastoma treatment, and misdiagnosis can lead to unnecessary intervention. Magnetic resonance imaging (MRI) provides cross-modality images for PSP prediction studies. However, how to effectively use the complementary information between the cross-modality MRI to improve PSP prediction is still a challenging task. To address this challenge, we propose a cross-modality feature interaction network for PSP prediction. Firstly, we propose a triple-branch multi-scale module to extract low-order feature representations and a skip-connection multi-scale module to extract high-order feature representations. Then, a cross-modality interaction module based on attention mechanism is designed to make the complementary information between cross-modality MRI fully interact. Finally, the high-order cross-modality interaction information is fed into a multi-layer perceptron to achieve the PSP prediction task. We evaluate the proposed network on a private dataset with 52 subjects from Hunan Cancer Hospital and validate it on a private dataset with 30 subjects from Xiangya Hospital. The accuracy of our proposed network on the datasets is 0.954 and 0.929, respectively, which is better than most typical convolutional neural network and interaction methods.

Adaptation and validation of moral distress thermometer in Chinese nurses.

BACKGROUND: Moral distress seriously affects professional nurses, and a number of instruments have been developed to measure the level of moral distress. The moral distress thermometer (MDT) is one of the commonly used instruments that can rapidly measure real-time moral distress; however, it remains unclear whether it is still useful in the Chinese cultural context. AIM: This study aimed to adapt and validate the MDT among Chinese registered nurses. RESEARCH DESIGN: An online, cross-sectional, survey study of adapting and validating Chinese version of MDT. PARTICIPANTS AND RESEARCH CONTEXT: A total of 182 registered nurses effectively finished this survey. The correlation between MDT score and the score of the moral distress scale-revised version (MDS-R) was used for evaluating convergent validity, and MDT scores of registered nurses who working in different departments and who made different actions to the final question of the MDS-R were compared by using one-way ANOVA to evaluate construct validity. ETHICAL CONSIDERATIONS: The Ethics Committee of Chongqing Traditional Chinese Medicine Hospital approved this study. RESULTS: The Chinese version of MDT was described as relevant to measure moral distress, with a reported item-level content validity index (I-CVI) and scale-level CVI (S-CVI) of 1. The mean MDT score and mean MDS-R score were 2.54 and 38.66, respectively, and the correlation between these two scores was significantly moderate (r = 0.41). Nurses working different departments reported different levels of moral distress, and those working in intensive care unit reported the highest level of moral distress than those working in other departments (p = 0.04). The MDT scores between nurses who presented different actions to their position were also significantly different, and those who had ever left and those who had considered leaving but did not leave reported significantly higher moral distress. CONCLUSION: The MDT is a reliable, valid, and easy-to-use instrument to rapidly measure the real-time moral distress of registered nurses in China.

Greening the Belt and Road Initiative: Evidence from emergy evaluation of China's provincial trade with ASEAN countries.

The Belt and Road Initiative (BRI) is a central policy within China's regional development and foreign trade strategy. Traditional trade has typically depended on economic valuation of resources, while the embedded environmental value is rarely considered. This situation exists in most BRI trade evaluations. To address BRI environmental sustainability issues, we consider the role of pivotal Chinese provinces and their key trade partners (ASEAN countries) as an illustration for the environmental value of resource exchanges. Emergy accounting is used as the valuation tool for a sample period of seventeen years. Key results include: (1) Emergy valuations show sustainability of sample provinces decreased over time; (2) ASEAN countries such as Indonesia, Malaysia, Singapore, Thailand, and Vietnam play significant resource roles for provincial economic systems; (3) Diverse trends in trade between pivotal provinces and ASEAN countries resulted in an unbalanced trade structure from trade. Policy implications are proposed to promote a more globally sustainable and fair trade using BRI as an established trade policy.

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model.

This paper aims to verify the impact of capital structure on business model innovation and firm performance and the mediating effect of business model innovation. We use the data of the Chinese growth enterprises market (GME) listed high-tech firms from 2016 to 2022 as a dynamic panel data model with the system-generalized method of moments (sys-GMM), adopting return on asset and earning per share as firm performance. Our results show that capital structure has a lag effect on firm performance. The total debt ratio in the last period has a significant non-linear impact on the performance and business model innovation level of nowadays, presenting a U-shaped relationship. The first-order lag short-term debt ratio positively improves firm performance. Business model innovation significantly promotes better firm performance, and business model innovation does exist in the mediating effect between enterprise capital structure and its performance. These results remain robust to different sample sizes or proxy variables. This paper proposes some suggestions for firm operations and government policies based on the findings.

Correction: Machine learning in internet financial risk management: A systematic literature review.

[This corrects the article DOI: 10.1371/journal.pone.0300195.].

Study on the photosynthetic growth characters in Cimicifuga dahurica (Turcz.) Maxim under different supplemental light environments.

Cimicifuga dahurica (C. dahurica) is an important medicinal plant in the northern region of China. The best supplemental light environment helps plant growth, development, and metabolism. In this study, we used two-year-old seedlings as experimental materials. The white light as the control (CK). The different ratios of red (R) and blue (B) combined light were supplemented (T1, 2R: 1B, 255.37 µmol m-2·s-1; T2, 3R: 1B, 279.69 µmol m-2·s-1; T3, 7R: 1B, 211.16 µmol m-2·s-1). The growth characteristics, photosynthetic pigment content, photosynthesis and chlorophyll fluorescence parameters, and primary metabolite content were studied in seedlings. The results showed that: 1) The fresh weight from shoot, root, and total fresh weight were significantly (P < 0.05) increased under T2 and T3 treatment. 2) The contents of chlorophyll a (Chl a), chlorophyll b (Chl b), and total chlorophyll (Chl) were significantly (P < 0.05) increased under T2 treatment, and carotenoid (car) content was reduced. 3) The photochemical quenching (qP), the actual photosynthetic efficiency of PSII (Y(II)), and the photosynthetic electron transfer rate (ETR) from leaves were significantly (P < 0.05) increased under T1 treatment. The Net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO2 concentration (Ci), and transpiration rate (Tr) were significantly (P < 0.05) increased under T2 and T3 treatments. 4) A total of 52 primary metabolites were detected in C. dahurica leaves. Compared with CK, 14, 15, and 18 differential metabolites were screened under T1, T2, and T3 treatments. In addition, D-xylose, D-glucose, glycerol, glycolic acid, and succinic acid were significantly (P < 0.05) accumulated under the T2 treatment, which could regulate the TCA cycle metabolism pathway. The correlation analysis suggested that plant growth was promoted by regulating the change of D-mannose content in galactinol metabolism and amino sugar and nucleotide sugar metabolism. In summary, the growth of C. dahurica was improved under T2 treatment.

Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia.

The rapid growth in computational power, sensor technology, and wearable devices has provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence (AI) has been instrumental in bringing about significant changes in the prevention, risk assessment, diagnosis, and treatment of arrhythmia. This review examines the current state of AI in the diagnosis and treatment of atrial fibrillation, supraventricular arrhythmia, ventricular arrhythmia, hereditary channelopathies, and cardiac pacing. Furthermore, ChatGPT, which has gained attention recently, is addressed in this paper along with its potential applications in the field of arrhythmia. Additionally, the accuracy of arrhythmia diagnosis can be improved by identifying electrode misplacement or erroneous swapping of electrode position using AI. Remote monitoring has expanded greatly due to the emergence of contactless monitoring technology as wearable devices continue to develop and flourish. Parallel advances in AI computing power, ChatGPT, availability of large data sets, and more have greatly expanded applications in arrhythmia diagnosis, risk assessment, and treatment. More precise algorithms based on big data, personalized risk assessment, telemedicine and mobile health, smart hardware and wearables, and the exploration of rare or complex types of arrhythmia are the future direction.

Association between lipoprotein(a) and premature atherosclerotic cardiovascular disease: a systematic review and meta-analysis.

Aims: High lipoprotein(a) [Lp(a)] level has been demonstrated as an important risk factor for atherosclerotic cardiovascular diseases (ASCVD) amongst the older populations, whereas its effects in the younger population remain unclear. This study evaluated the associations between Lp(a) and the risk of premature ASCVD. Method and results: PubMed and Embase were searched for related studies until 12 November 2023. Fifty-one studies including 100 540 participants were included. Mean age of patients ranged from 35.3 to 62.3 years. The proportion of male participants ranged from 0% to 100%. The mean follow-up was provided in five studies ranging from 1 year to 40 years. The definition of elevated Lp(a) varied among studies, such as >30 mg/dL, >50 mg/dL, the top tertiles, the top quartiles, the top quintiles, and so on. Higher Lp(a) was significantly associated with the composite ASCVD [odds ratio (OR): 2.15, 95% confidence interval (95% CI): 1.53-3.02, P < 0.001], especially for coronary artery disease (OR: 2.44, 95% CI: 2.06-2.90, P < 0.001) and peripheral arterial disease (OR: 2.56, 95% CI: 1.56-4.21, P < 0.001). This association remained significant in familial hypercholesterolaemia (FH) (OR: 3.11, 95% CI: 1.63-5.96, P < 0.001) and type 2 diabetes mellitus (T2DM) patients (OR: 2.23; 95% CI: 1.54-3.23, P < 0.001).Significant results were observed in South Asians (OR: 3.71, 95% CI: 2.31-5.96, P < 0.001), Caucasians (OR: 3.17, 95% CI: 2.22-4.52, P < 0.001), and patients with baseline low-density lipoprotein cholesterol (LDL-c) level ≥ 2.6 mmol/L. Conclusion: Elevated Lp(a) predicts the risk of the composite or individual ASCVD in young, regardless of study design, gender, population characteristics (community or hospitalized), different premature definitions, and various Lp(a) measurement approaches. This association was important in South Asians, Caucasians, FH patients, T2DM patients, and patients with baseline LDL-c level ≥ 2.6 mmol/L.

Metabolomic analysis of rumen-protected branched-chain amino acids in primiparous dairy cows.

Introduction: Peripartal cows are susceptible to a negative energy balance due to inadequate nutrient intake and high energy requirements for lactation. Improving the energy metabolism of perinatal dairy cows is crucial in increasing production in dairy cows. Methods: In this study, we investigated the impact of rumen-protected branched-chain amino acid (RPBCAA) on the production performance, energy and lipid metabolism, oxidative stress, and immune function of primiparous dairy cows using metabolomics through a single-factor experiment. Twenty healthy primiparous Holstein cows were selected based on body condition scores and expected calving date, and were randomly divided into RPBCAA (n = 10) and control (n = 10) groups. The control group received a basal diet from calving until 21 d in milk, and the RPBCAA group received the basal diet and 44.6 g/d RPLeu, 25.14 g/d RPIle, and 25.43 g/d RPVal. Results: In comparison to the control group, the supplementation of RPBCAA had no significant effect on milk yield and milk composition of the dairy cows. Supplementation with RPBCAA significantly increased the concentrations of insulin, insulin growth factor 1, glucagon, and growth hormones, which are indicators of energy metabolism in postpartum cows. The very low density lipoprotein, fatty acid synthase, acetyl coenzyme A carboxylase, and hormone-sensitive lipase contents of the RPBCAA group were significantly greater than that of the control group; these metrics are related to lipid metabolism. In addition, RPBCAA supplementation significantly increased serum glutathione peroxidase and immunoglobulin G concentrations and decreased malondialdehyde concentrations. Liquid chromatography-mass spectrometry (LC-MS) analysis revealed 414 serum and 430 milk metabolic features. Supplementation with RPBCAA primarily increased concentrations of amino acid and lipid metabolism pathways and upregulated the abundance of serotonin, glutamine, and phosphatidylcholines. Discussion: In summary, adding RPBCAA to the daily ration can influence endocrine function and improve energy metabolism, regulate amino acid and lipid metabolism, mitigate oxidative stress and maintain immune function on primiparous cows in early lactation.

Paradoxical Embolism in Juveniles and Young Adults With Severe-to-Profound Sudden Sensorineural Hearing Loss.

Objective: Paradoxical embolism from right-to-left shunting is a common cause of cryptogenic stroke in the young. Circulatory ischemia of the cochlea is closely connected with severe-to-profound sudden sensorineural hearing loss. This study aimed to explore the role of paradoxical embolism in severe-to-profound sudden sensorineural hearing loss in juveniles and young adults. Methods: From August 2021 to September 2022, consecutive outpatients under 35 years of age with severe-to-profound sudden hearing loss were included in the study. Routine auditory electrophysiological testing and contrast transcranial Doppler ultrasonography (c-TCD) were conducted, and the results were retrospectively analyzed. Results: Seven patients (age: 19.4 ± 6.5 years) were enrolled, including 5 juveniles and 2 young adults. Three patients had severe deafness, and 4 patients had profound deafness. Right-to-left shunting was detected in all patients through c-TCD. Patent foramen ovale was found in 2 patients while pulmonary arteriovenous fistula was found in 1 patient through contrast transthoracic echocardiography or cardiac catheterization. No patients had precipitating factors for sudden sensorineural hearing loss, and none had abnormalities on head magnetic resonance imaging. Six patients underwent whole-exome sequencing, and no known deafness gene variant was detected. After standard treatment for 1 month, 2, 3, and 2 patients had complete, slight, and no hearing recovery, respectively. Conclusions: Paradoxical embolism is a possible cause of severe-to-profound sudden sensorineural hearing loss in juveniles and young adults. In young patients, c-TCD is an effective screening tool to detect right-to-left shunting, while contrast transthoracic echocardiography is a complementary examination to c-TCD.

Transfer learning for anatomical structure segmentation in otorhinolaryngology microsurgery.

BACKGROUND: Reducing the annotation burden is an active and meaningful area of artificial intelligence (AI) research. METHODS: Multiple datasets for the segmentation of two landmarks were constructed based on 41 257 labelled images and 6 different microsurgical scenarios. These datasets were trained using the multi-stage transfer learning (TL) methodology. RESULTS: The multi-stage TL enhanced segmentation performance over baseline (mIOU 0.6892 vs. 0.8869). Besides, Convolutional Neural Networks (CNNs) achieved a robust performance (mIOU 0.8917 vs. 0.8603) even when the training dataset size was reduced from 90% (30 078 images) to 10% (3342 images). When directly applying the weight from one certain surgical scenario to recognise the same target in images of other scenarios without training, CNNs still obtained an optimal mIOU of 0.6190 ± 0.0789. CONCLUSIONS: Model performance can be improved with TL in datasets with reduced size and increased complexity. It is feasible for data-based domain adaptation among different microsurgical fields.

Psychometric Evaluation of the Persian Version of Spiritual Self-Care Practice Scale in Iranian Patients with Cancer.

Spiritual self-care is defined as a set of patient-centered or family-centered spiritual activities aimed at promoting health and well-being. In chronic diseases such as cancer, the responsibility for care typically falls on the patient or their family, necessitating an accurate assessment of the patient's self-care practices to achieve this goal. The objective of this study was to translate, culturally adapt, and examine the psychometrics of the Persian version of the spiritual self-care practice scale (SSCPS) in cancer patients. This scale is designed to be administered directly to patients to assess their spiritual self-care practices. This cross-sectional study was conducted at the oncology ward in Afzalipoor Hospital, Javad Al-Aemeh Clinic, and Physicians Clinics affiliated with Kerman University of Medical Sciences in Kerman, southeast Iran. The study included qualitative and quantitative assessments of face validity, content validity, item analysis, exploratory and confirmatory factor analysis (construct validity), and reliability. Data collection took place between March 20, 2023, and December 30, 2023. The scale's content validity index was calculated to be 0.948, with mostly minor revision comments for most items. The item-content validity indices ranged from 0.7 to 1. Exploratory factor analysis revealed a five-factor solution with 23 items, explaining 61.251% of the total variance. The identified factors were labeled as 'personal and interpersonal spiritual practices,' 'shaping and strengthening relationship practices,' 'religious practices,' 'physical spiritual practices,' and 'reshaping relationship practices.' Most of the confirmatory factor analysis indices were satisfactory (χ2/df = 1.665, CFI = 0.934, IFI = 0.935, RMSEA = 0.058). The Cronbach's α coefficient for the total scale was 0.89, while it ranged from 0.596 to 0.882 for the subscales. The Persian version of SSCPS with 23 items demonstrates reliability and effectiveness in assessing the spiritual practice performance of Iranian cancer patients. Compared to the original version, the Persian adaptation of SSCPS is concise, making it a suitable instrument for future research and practice on spiritual self-care among Iranian cancer patients.

Machine learning in internet financial risk management: A systematic literature review.

Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.

Protein C deficiency with venous and arterial thromboembolic events.

Protein C (PC) is a key component of the vitamin K-dependent coagulation pathway. It exerts anticoagulant effects by inactivating factors V and VIII. Acquired or inherited PC deficiency results in a prothrombotic state, with presentations varying from asymptomatic to venous thromboembolism. However, there has been an increasing number of reports linking PC deficiency to arterial thromboembolic events, such as myocardial infarction and ischemic stroke. This editorial focuses on the association between PC deficiency and thromboembolism, which may provide some insights for treatment strategy and scientific research.

[Analysis of the effect of different facial nerve managements applied to tumor resection in the jugular foramen region].

Objective:To summarize the results of different facial nerve management modalities applied to tumor resection in the jugular foramen region. Methods:The clinical data of 54 patients with tumors in the jugular foramen region who underwent surgery from January 2015 to March 2023 were retrospectively analyzed: 18 males and 36 females; Age ranges from 21 to 67 years, with an average age of 44.4 years; and median follow-up time: 12 months. The House-Brackmann（HB） grading system was applied to assess the patients' facial nerve function before surgery, 1-2 weeks after surgery and at the final follow-up （HBⅠ-Ⅱ grade for good function）: 42 cases with preoperative HB grades Ⅰ-Ⅱ; partial facial nerve transposition（9 cases）, complete facial nerve transposition（28 cases）, and facial nerve excision and re-construction（17 cases） were used, respectively（stage Ⅰor Ⅱ）. Relevant factors affecting postoperative facial nerve function were analyzed. Results:Postoperative pathology confirmed 39 cases of paraganglioma, 9 cases of nerve sheath tumor, 3 cases of meningioma, and 1 case each of fibromucinous sarcoma, chondrosarcoma, and intravascular myofibroma. Facial nerve function after partial facial nerve transposition was HB grade Ⅰ-Ⅱ in 89%（8/9）; after complete facial nerve transposition was HB grade Ⅰ-Ⅱ in 86%（24/28） in 28 cases; after facial nerve severance and reconstruction was HB grade Ⅰ-Ⅱ in 2/7（Stage Ⅰ） and 0/3（Stage Ⅱ）, respectively. Tumor size and surgical approach were correlated with postoperative facial nerve function in patients with facial nerve transposition（P<0.05）. There was no statistically significant difference in facial nerve function after complete and partial facial nerve transposition（P>0.05）. Conclusion:Intraoperative stretching of the facial nerve may be an important factor affecting facial nerve function during surgical treatment of tumors in the jugular venous foramen region; for patients with facial nerve dissection, facial nerve reconstruction should be adopted according to the situation, aiming at the recovery of facial nerve function.

Improving salt-tolerant artificial consortium of Bacillus amyloliquefaciens for bioconverting food waste to lipopeptides.

High-salt content in food waste (FW) affects its resource utilization during biotransformation. In this study, adaptive laboratory evolution (ALE), gene editing, and artificial consortia were performed out to improve the salt-tolerance of Bacillus amyloliquefaciens for producing lipopeptide under FW and seawater. High-salt stress significantly decreased lipopeptide production in the B. amyloliquefaciens HM618 and ALE strains. The total lipopeptide production in the recombinant B. amyloliquefaciens HM-4KSMSO after overexpressing the ion transportor gene ktrA and proline transporter gene opuE and replacing the promoter of gene mrp was 1.34 times higher than that in the strain HM618 in medium containing 30 g/L NaCl. Lipopeptide production under salt-tolerant consortia containing two strains (HM-4KSMSO and Corynebacterium glutamicum) and three-strains (HM-4KSMSO, salt-tolerant C. glutamicum, and Yarrowia lipolytica) was 1.81- and 2.28-fold higher than that under pure culture in a medium containing FW or both FW and seawater, respectively. These findings provide a new strategy for using high-salt FW and seawater to produce value-added chemicals.

Efficacy and safety of colchicine for atrial fibrillation prevention: An updated meta-analysis of randomized controlled trials.

BACKGROUND: Atrial fibrillation (AF), the most common arrhythmia, is closely related to inflammation. Colchicine has the potent anti-inflammatory effects. Several randomized clinical trials (RCTs) have evaluated the efficacy and safety of colchicine in the prevention of AF but the results are inconsistent. OBJECTIVE: The purpose of our study was to evaluate the impact of colchicine on AF. METHOD AND RESULTS: PubMed, EMBASE, Web of Science, Cochrane Library and ClinicalTrials.gov were searched for related studies until Jan 8, 2024. A total of 17 studies including 16,238 participants were included. Compared to the placebo group, there were fewer incidences of AF in the colchicine group (RR: 0.75, 95%CI: 0.68-0.83, P < 0.001). The incidence of overall adverse events and overall gastrointestinal intolerance did not differ significantly between the two groups. However, diarrhea, nausea, and discontinuation occurred more frequently in patients treated with colchicine. CONCLUSION: Colchicine can prevent patients from the incidence of AF, regardless of the mean age of patients, type of atrial fibrillation, maintenance dose, duration of colchicine use, cumulative daily dose, and follow-up time with more diarrhea, nausea and discontinuation. These adverse events can be avoided by low doses (0.5 mg once daily) and long period time of colchicine use.

Joint toxicity of cadmium (II) and microplastic leachates on wheat seed germination and seedling growth.

Cadmium (Cd) pollution ranks first in soils (7.0%) and microplastics usually have a significant adsorption capacity for it, which could pose potential threats to agricultural production and human health. However, the joint toxicity of Cd and microplastics on crop growth remains largely unknown. In this study, the toxic effects of Cd2+ and two kinds of microplastic leachates, polyvinyl chloride (PVC) and low-density polyethylene (LDPE), on wheat seed germination and seedlings' growth were explored under single and combined conditions. The results showed that Cd2+ solution and two kinds of microplastic leachates stimulated the wheat seed germination process but inhibited the germination rate by 0-8.6%. The combined treatments promoted wheat seed germination but inhibited the seedlings' growth to different degrees. Specifically, the combination of 2.0 mg L-1 Cd2+ and 1.0 mgC L-1 PVC promoted both seed germination and seedlings' growth, but they synergistically increased the antioxidant enzyme activity of seedlings. The toxicity of the PVC leachate to wheat seedlings was stronger than LDPE leachate. The addition of Cd2+ could alleviate the toxicity of PVC leachate on seedlings, and reduce the toxicity of LDPE leachate on seedlings under the same concentration class combinations but aggravated stress under different concentration classes, consistent with the effect on seedlings' growth. Overall, Cd2+, PVC, and LDPE leachates have toxic effects on wheat growth, whether treated under single or combined treatments. This study has important implications for the joint toxicity of Cd2+ solution and microplastic leachates in agriculture.

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achieved outstanding performance in predicting PPIS. However, these studies often neglect the modeling of information at different scales in the graph and the symmetry of protein molecules within three-dimensional space. RESULTS: In response to this gap, this article proposes the MEG-PPIS approach, a PPIS prediction method based on multi-scale graph information and E(n) equivariant graph neural network (EGNN). There are two channels in MEG-PPIS: the original graph and the subgraph obtained by graph pooling. The model can iteratively update the features of the original graph and subgraph through the weight-sharing EGNN. Subsequently, the max-pooling operation aggregates the updated features of the original graph and subgraph. Ultimately, the model feeds node features into the prediction layer to obtain prediction results. Comparative assessments against other methods on benchmark datasets reveal that MEG-PPIS achieves optimal performance across all evaluation metrics and gets the fastest runtime. Furthermore, specific case studies demonstrate that our method can predict more true positive and true negative sites than the current best method, proving that our model achieves better performance in the PPIS prediction task. AVAILABILITY AND IMPLEMENTATION: The data and code are available at https://github.com/dhz234/MEG-PPIS.git.