First detection of Tetraparvovirus ungulate 1 in diseased cattle (Chinese Simmental) from Hunan province, China.

Tetraparvovirus is an emerging parvovirus infecting a variety of mammals and humans, and associated with human diseases including severe acute respiratory infection and acute encephalitis syndrome. In the present study, a Tetraparvovirus ungulate 1 (formerly known as bovine hokovirus) strain HNU-CBY-2023 was identified and characterized from diseased Chinese Simmental from Hunan province, China. The nearly complete genome of HNU-CBY-2023 is 5346 nt in size and showed genomic identities of 85-95.5% to the known Tetraparvovirus ungulate 1 strains from GenBank, indicating a rather genetic variation. Phylogenetic and genetic divergence analyses indicated that Tetraparvovirus ungulate 1 could be divided into two genotypes (I and II), and HNU-CBY-2023 was clustered into genotype II. This study, for the first time, identified Tetraparvovirus ungulate 1 from domestic cattle from mainland China, which will be helpful to understand the prevalence and genetic diversity of Tetraparvovirus ungulate 1.

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.

PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms. METHODS: We utilized computational fluid dynamics (CFD) to simulate hemodynamics in 66 cerebral aneurysms from 65 patients, including 57 stable and nine recanalized aneurysms. We derived a total of 107 features for each aneurysm, encompassing four clinical features, 12 morphological features, and 91 hemodynamic features. To investigate the influence of feature derivation and selection methods on the ML models, we employed two derivation methods, simplified and fully derived, in combination with four selection methods: all features, statistically significant analysis, stepwise multivariate logistic regression analysis (stepwise-LR), and recursive feature elimination (RFE). Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) on both the training and testing datasets. RESULTS: The AUROC values on the testing dataset exhibited a wide-ranging spectrum, spanning from 0.373 to 0.863. Fully derived features and the RFE selection method demonstrated superior performance in intra-model comparisons. The multi-layer perceptron (MLP) model, trained with RFE-selected fully derived features, achieved the best performance on the testing dataset, with an AUROC value of 0.863 (95% CI: 0.684- 1.000). CONCLUSION: Our study demonstrated the importance of feature derivation and selection in determining the performance of ML models. This enabled the development of accurate decision-making models without the need to invade the patient.

HVEM in acute lymphocytic leukemia facilitates tumour immune escape by inhibiting CD8+ T cell function.

PURPOSE: Leukaemia remains a major contributor to global mortality, representing a significant health risk for a substantial number of cancer patients. Despite notable advancements in the field, existing treatments frequently exhibit limited efficacy or recurrence. Here, we explored the potential of abolishing HVEM (herpes virus entry mediator, TNFRSF14) expression in tumours as an effective approach to treat acute lymphoblastic leukaemia (ALL) and prevent its recurrence. METHODS: The clinical correlations between HVEM and leukaemia were revealed by public data analysis. HVEM knockout (KO) murine T cell lymphoblastic leukaemia cell line EL4 were generated using CRISPR-Cas9 technology, and syngeneic subcutaneous tumour models were established to investigate the in vivo function of HVEM. Immunohistochemistry (IHC), RNA-seq and flow cytometry were used to analyse the tumour immune microenvironment (TIME) and tumour draining lymph nodes (dLNs). Immune functions were investigated by depletion of immune subsets in vivo and T cell functional assays in vitro. The HVEM mutant EL4 cell lines were constructed to investigate the functional domain responsible for immune escape. RESULTS: According to public databases, HVEM is highly expressed in patients with ALL and acute myeloid leukemia (AML) and is negatively correlated with patient prognosis. Genetic deletion of HVEM in EL4 cells markedly inhibited tumour progression and prolonged the survival of tumour-bearing mice. Our experiments proved that HVEM exerted its immunosuppressive effect by inhibiting antitumour function of CD8+ T cell through CRD1 domain both in vivo and in vitro. Additionally, we identified a combination therapy capable of completely eradicating ALL tumours, which induces immune memory toward tumour protection. CONCLUSIONS: Our study reveals the potential mechanisms by which HVEM facilitates ALL progression, and highlights HVEM as a promising target for clinical applications in relapsed ALL therapy.

Design, synthesis and bioactivity evaluation of 4-hydroxycoumarin derivatives as potential anti-inflammatory agents against acute lung injury and colitis.

Acute lung injury (ALI) and inflammatory bowel disease (IBD) are common inflammatory illnesses that seriously affect people's health. Herein, a series of 4-hydroxylcoumarin (4-HC) derivatives were designed and synthesized. The inhibitory effects of these compounds on LPS-induced interleukin-6 (IL-6) release from J774A.1 cells were then screened via ELISA assay, compound B8 showed 3 times more active than the lead compound 4-HC. The most active compound B8 had the IC50 values of 4.57 µM and 6.51 µM for IL-6 release on mouse cells J774A.1 and human cells THP-1, respectively. Furthermore, we also found that B8 could act on the MAPK pathway. Based on the target prediction results of computer virtual docking, kinase inhibitory assay was carried out, and it revealed that targeting IRAK1 was a key mechanism for B8 to exert anti-inflammatory activity. Moreover, B8 exerted a good therapeutic effect on the dextran sulfate sodium (DSS)-induced colitis model and liposaccharide (LPS)-induced ALI mouse models. The acute toxicity experiments indicated that high-dose B8 caused no adverse reactions in mice, confirming its safety in vivo. Additionally, the preliminary pharmacokinetic (PK) parameters of B8 in SD rats were also examined, revealing a bioavailability (F) of 28.72 %. In conclusion, B8 is a potential candidate of drug for the treatment of ALI and colitis.

A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review.

Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.

Exploring the Causal Effects of Mineral Metabolism Disorders on Telomere and Mitochondrial DNA: A Bidirectional Two-Sample Mendelian Randomization Analysis.

The aim of this study was to assess the causal relationships between mineral metabolism disorders, representative of trace elements, and key aging biomarkers: telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN). Utilizing bidirectional Mendelian randomization (MR) analysis in combination with the two-stage least squares (2SLS) method, we explored the causal relationships between mineral metabolism disorders and these aging indicators. Sensitivity analysis can be used to determine the reliability and robustness of the research results. The results confirmed that a positive causal relationship was observed between mineral metabolism disorders and TL (p < 0.05), while the causal relationship with mtDNA-CN was not significant (p > 0.05). Focusing on subgroup analyses of specific minerals, our findings indicated a distinct positive causal relationship between iron metabolism disorders and both TL and mtDNA-CN (p < 0.05). In contrast, disorders in magnesium and phosphorus metabolism did not exhibit significant causal effects on either aging biomarker (p > 0.05). Moreover, reverse MR analysis did not reveal any significant causal effects of TL and mtDNA-CN on mineral metabolism disorders (p > 0.05). The combination of 2SLS with MR analysis further reinforced the positive causal relationship between iron levels and both TL and mtDNA-CN (p < 0.05). Notably, the sensitivity analysis did not indicate significant pleiotropy or heterogeneity within these causal relationships (p > 0.05). These findings highlight the pivotal role of iron metabolism in cellular aging, particularly in regulating TL and sustaining mtDNA-CN, offering new insights into how mineral metabolism disorders influence aging biomarkers. Our research underscores the importance of trace element balance, especially regarding iron intake, in combating the aging process. This provides a potential strategy for slowing aging through the adjustment of trace element intake, laying the groundwork for future research into the relationship between trace elements and healthy aging.

Genetic Prediction of Causal Relationships between Osteoporosis and Sepsis: Evidence from Mendelian Randomization with two-sample Designs.

BACKGROUND: Recent observational studies have suggested that osteoporosis may be a risk factor for sepsis. To mitigate confounding factors and establish the causal relationship between sepsis and osteoporosis, we conducted a two-sample Mendelian randomization analysis using publicly available summary statistics. METHODS: Utilizing summary data from FinnGen Biobank, we employed a two-sample Mendelian randomization (MR) analysis to predict the causal relationship between osteoporosis and sepsis. The MR analysis primarily utilized the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, weighted mode, and simple mode analyses, with Bayesian weighted MR (BWMR) analysis employed for result validation. Sensitivity analyses included MR-PRESSO, "leave-one-out" analysis, MR-Egger regression, and Cochran's Q test. RESULTS: In the European population, an increase of one standard deviation in osteoporosis was associated with an 11% increased risk of sepsis, with an odds ratio (OR) of 1.11 (95% CI, 1.06 - 1.16; p = 3.75E-06). BWMR yielded an OR of 1.11 (95% CI, 1.06 - 1.67; p = 1.21E-05), suggesting osteoporosis as a risk factor for sepsis. Conversely, an increase of one standard deviation in sepsis was associated with a 26% increased risk of osteoporosis, with an OR of 1.26 (95% CI, 1.11 - 1.16; p = 0.45E-03). BWMR yielded an OR of 1.26 (95% CI, 1.09 - 1.45; p = 1.45E-03), supporting sepsis as a risk factor for osteoporosis. CONCLUSION: There is a association between osteoporosis and sepsis, with osteoporosis may serving as a risk factor for the development of sepsis, while sepsis may also promote the progression of osteoporosis.

How dyadic appraisal moderate the association between dyadic coping and diabetes management efficacy.

To explore the moderating role of dyadic appraisal in the association between dyadic coping and diabetes management efficacy. Two hundred seventy six middle-aged and older couple pairs with one spouse who had diabetes were recruited from 14 community healthcare centers across Guangzhou. The moderating role of dyadic appraisal was investigated using the actor-partner interdependence moderation model. When both couples considered diabetes to be a shared condition, statistically-significant associations were found between patients' negative (ß = -22.7, p = 0.008) and neutral behaviors (ß = 13.6, p = 0.017), plus spouses' positive behaviors (ß = 22.8, p = 0.009) on their own diabetes management efficacy, respectively (i.e. actor effects); as well as between spouses' positive (ß = 16.8, p = 0.028), negative (ß = -28.5, p < 0.001), and neutral behaviors (ß = 16.9, p = 0.006) on patient's diabetes management efficacy (i.e. partner effects). Dyadic appraisal moderates the association between dyadic coping and diabetes management efficacy.

Learning A Single Network for Robust Medical Image Segmentation with Noisy Labels.

Robust segmenting with noisy labels is an important problem in medical imaging due to the difficulty of acquiring high-quality annotations. Despite the enormous success of recent developments, these developments still require multiple networks to construct their frameworks and focus on limited application scenarios, which leads to inflexibility in practical applications. They also do not explicitly consider the coarse boundary label problem, which results in sub-optimal results. To overcome these challenges, we propose a novel Simultaneous Edge Alignment and Memory-Assisted Learning (SEAMAL) framework for noisy-label robust segmentation. It achieves single-network robust learning, which is applicable for both 2D and 3D segmentation, in both Set-HQ-knowable and Set-HQ-agnostic scenarios. Specifically, to achieve single-model noise robustness, we design a Memory-assisted Selection and Correction module (MSC) that utilizes predictive history consistency from the Prediction Memory Bank to distinguish between reliable and non-reliable labels pixel-wisely, and that updates the reliable ones at the superpixel level. To overcome the coarse boundary label problem, which is common in practice, and to better utilize shape-relevant information at the boundary, we propose an Edge Detection Branch (EDB) that explicitly learns the boundary via an edge detection layer with only slight additional computational cost, and we improve the sharpness and precision of the boundary with a thinning loss. Extensive experiments verify that SEAMAL outperforms previous works significantly.

Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19.

As a disease causing a global pandemic, the progression of symptoms to severe disease in patients with COVID-19 often has adverse outcomes, but research on the immunopathology of COVID-19 severe disease remains limited. In this study, we used mRNA-seq data from the peripheral blood of COVID-19 patients to identify six COVID-19 severe immune characteristic genes (FPR1, FCGR2A, TLR4, S100A12, CXCL1, and L TF), and found neutrophils to be the critical immune cells in COVID-19 severe disease. Subsequently, using scRNA-seq data from bronchoalveolar lavage fluid from COVID-19 patients, neutrophil subtypes highly expressing the S100A family were found to be located at the end of cellular differentiation and tended to release neutrophil extracellular traps. Finally, it was also found that alveolar macrophages, macrophages, and monocytes with a high expression of COVID-19 severe disease immune characteristic genes may influence neutrophils through intercellular ligand-receptor pairs to promote neutrophil extracellular trap release. This study provides immune characteristic genes, critical immune pathways, and immune cells in COVID-19 severe disease, explores intracellular immune transitions of critical immune cells and pit-induced intercellular communication of immune transitions, and provides new biomarkers and potential drug targets for the treatment of patients with COVID-19 severe disease.

Bibliometric and visualized analysis of type 2 diabetic osteoporosis from 2013 to 2022.

Type 2 diabetic osteoporosis (T2DOP) has received increasing attention from researchers. In this study, a total of 453 publications related to T2DOP from 2013 to 2022 were analyzed using bibliometric and visual analysis to identify the research trends and research hotspots in the field of T2DOP. PURPOSE: The objective of this study was to conduct a comprehensive bibliometric analysis of T2DOP-related publications from 2013 to 2022 to determine global research trends in T2DOP in terms of number of publications, countries/regions, institutions, authors, journals, funding agencies, and keywords. METHODS: All data were collected from the Web of Science Core Collection (WoSCC). All original research publications regarding T2DOP from 2013 to 2022 were retrieved. VOSviewer and Microsoft Office Excel were used to conduct the bibliometric and visual analysis. RESULTS: From 2013 to 2022, 515 relevant publications were published, with a peak in 2022 in the annual number of publications. The countries leading the research were USA and China. Sugimoto was the most influential authors. Capital Medical University and Nanjing Medical University were the most prolific institutions. Osteoporosis International was the most productive journal concerning T2DOP research. National Natural Science Foundation of China was the primary funding source for this research area. "Bone-mineral density", "fracture risk", and "postmenopausal women" were the most high-frequency keywords over the past 10 years. CONCLUSION: This was the first bibliometric study of diabetes mellitus and osteoporosis to exclusively examine type 2 diabetes mellitus. Our findings would provide guidance to understand the research frontiers and hot directions in the near future.

Factors Impacting One-year Follow-up Visit Adherence after Bariatric Surgery in West China: A Mixed Methods Study.

PURPOSE: Quality follow-up (FU) is crucial after bariatric surgery. However, poor adherence after surgery is prevalent. This research aimed to explore the factors related to FU adherence after bariatric surgery in West China. MATERIALS AND METHODS: This study used a sequential explanatory mixed-methods research design. Participants (n = 177) were identified from the West China Hospital. Demographic information, disease profile, treatment information, and post-surgery FU information were obtained from the bariatric surgery database of the Division of Gastrointestinal Surgery of the West China Hospital. The survey data were analyzed using logistic regression. Semi-structured interviews with participants (n = 10) who had low adherence were conducted. The recording was transcribed verbatim and entered into qualitative data analysis software. Qualitative data were analyzed using a content analysis approach. RESULTS: Multiple logistic regression revealed that living in Chengdu (OR, 2.308), being employed (OR, 2.532), non-smoking (OR, 2.805), and having less than five years of obesity (OR, 2.480) were positive predictors of FU adherence within one year. Semi-structured interviews suggested that factors related to adherence to FU were lack of motivation, lack of opportunity, insufficient ability, and beliefs regarding consequences. CONCLUSION: Factors impacting one-year FU visit adherence after bariatric surgery include not only demographic and disease-related factors but also social and family factors. These results will provide evidence to support healthcare professionals in developing personalized postoperative FU management strategies.

Discovery and validation of anti-arthritic ingredients and mechanisms of Qingfu Juanbi Tang, a Chinese herbal formulation, on rheumatoid arthritis.

ETHNOPHARMACOLOGICAL RELEVANCE: Qingfu Juanbi Tang (QFJBT), a novel and improved Chinese herbal formulation, has surged in recent years for its potential in the therapy of rheumatoid arthritis (RA). Anti-arthritic effects and underlying molecular mechanisms of QFJBT have increasingly become a focal point in research. AIM OF THE STUDY: This study utilized network pharmacology, molecular docking, and experimental validation to elucidate effective ingredients and anti-arthritic mechanisms of QFJBT. MATERIALS AND METHODS: Targets associated with QFJBT and RA were identified from relevant databases and standardized using the Uniprot for gene nomenclature. A "QFJBT-ingredient-target network" and a "Venn diagram of QFJBT and RA targets" were created from the data. The overlap in the Venn diagram highlighted potential targets of QFJBT in the treatment of RA. These targets were subjected to PPI network, GO, and KEGG pathway analysis. The findings were subsequently confirmed through molecular docking and pharmacological experiments to propose the mechanism of action of QFJBT. RESULTS: The study identified 236 active ingredients in QFJBT, with 120 predicted to be effective against RA. Molecular docking showed high binding affinity of key targets (JUN, PTGS2, and TNF-α) with bioactive compounds (rhein, sinomenine, calycosin, and paeoniflorin) of QFJBT. Pharmacodynamic evaluation demonstrated the effects of QFJBT at the dose of 4.56 g/kg in ameliorating symptoms of AIA rats and in reducing levels of JUN, PTGS2, and TNF-α in synovial tissues. In vitro studies further exhibited that rhein, paeoniflorin, sinomenine, calycosin, and QFJBT-containing serum significantly inhibited abnormal proliferation of RA fibroblast-like synoviocytes. Interestingly, rhein and paeoniflorin specifically decreased p-JUN/JUN expression and TNF-α release, respectively, while sinomenine and calycosin selectively increased PTGS2 expression. Consistently, QFJBT-containing serum demonstrated similar effects as those active ingredients identified in QFJBT did. CONCLUSIONS: QFJBT, QFJBT-containing serum, and its active ingredients (rhein, paeoniflorin, sinomenine, and calycosin) suppress inflammatory responses in RA. Anti-arthritic effects of QFJBT and its active ingredients are likely linked to their modulatory impact on identified hub targets.

Effects of haemodiafiltration or haemofiltration compared with haemodialysis on prognosis in patients with end-stage renal disease: protocol an updated systematic review and meta-analysis of randomised trials with trial sequential analysis.

INTRODUCTION: Haemodialysis is the most common treatment option for patients with life-sustaining end-stage kidney disease (ESKD). In recent years, haemodiafiltration or haemofiltration has been widely used in patients with ESKD, and there are still conflicting findings as to whether both are superior to traditional haemodialysis. This systematic review and meta-analysis were designed to determine whether haemodiafiltration or haemofiltration is more effective than haemodialysis in reducing all-cause mortality risk in patients with ESKD. METHODS AND ANALYSIS: We will perform a systematic PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library and Scopus search, including studies published before September 2023. Randomised controlled trials will be included exploring the effects of haemodiafiltration or haemofiltration compared with haemodialysis on prognosis in patients with ESKD. Outcomes of interest include all-cause mortality, cardiovascular events, dialysis adequacy and adverse effects. The Cochrane Collaboration tools (ROB-2) will assess the bias risk. Available data will be used to calculate effect sizes. Heterogeneity between studies will be evaluated with I2. The trial sequential analysis will be used to eliminate false-positive results. The certainty of the evidence will be assessed using Grading of Recommendations, Assessment, Development and Evaluation criteria. ETHICS AND DISSEMINATION: This systematic review and meta-analysis was deemed exempt from ethics review. Results will be disseminated through publication in peer-reviewed journals and research conferences. PROSPERO REGISTRATION NUMBER: CRD42023464509.

Broad-spectrum hydrocarbon-degrading microbes in the global ocean metagenomes.

Understanding the diversity and functions of hydrocarbon-degrading microorganisms in marine environments is crucial for both advancing knowledge of biogeochemical processes and improving bioremediation methods. In this study, we leveraged nearly 20,000 metagenome-assembled genomes (MAGs), recovered from a wide array of marine samples across the global oceans, to map the diversity of aerobic hydrocarbon-degrading microorganisms. A broad bacterial diversity was uncovered, with a notable preference for degrading aliphatic hydrocarbons over aromatic ones, primarily within Proteobacteria and Actinobacteriota. Three types of broad-spectrum hydrocarbon-degrading bacteria were identified for their ability to degrade various hydrocarbons and possession of multiple copies of hydrocarbon biodegradation genes. These bacteria demonstrate extensive metabolic versatility, aiding their survival and adaptability in diverse environmental conditions. Evidence of gene duplication and horizontal gene transfer in these microbes suggested a potential enhancement in the diversity of hydrocarbon-degrading bacteria. Positive correlations were observed between the abundances of hydrocarbon-degrading genes and environmental parameters such as temperature (-5 to 35 °C) and salinity (20 to 42 PSU). Overall, our findings offer valuable insights into marine hydrocarbon-degrading microorganisms and suggest considerations for selecting microbial strains for oil pollution remediation.

Heavy metal contamination in duck eggs from a mercury mining area, southwestern China.

Objective: Mercury (Hg) contamination in the environment around mercury mines is often accompanied by heavy metal contamination. Methods: Here, we determined concentrations of chromium (Cr), zinc (Zn), strontium (Sr), barium (Ba), and lead (Pb) in duck eggs from a Hg mining area in Southwest China to assess the contamination and health risk. Results: Duck eggs obtained from the mining area exhibit higher concentrations of Cr, Zn, Sr, Ba, and Pb compared to those from the background area, with egg yolks containing higher metal levels than egg whites. Specifically, the mean Cr, Zn, Sr, Ba, and Pb concentrations of duck eggs from the Hg mining area are 0.38, 63.06, 4.86, 10.08, and 0.05 µg/g, respectively, while those from the background area are only 0.21, 24.65, 1.43, 1.05, and 0.01 µg/g. Based on the single-factor contamination index and health risk assessment, heavy metal contamination in duck eggs poses an ecological risk and health risk. Conclusion: This study provides important insight into heavy metal contamination in duck eggs from Hg mining areas.

Robust Model Watermarking for Image Processing Networks via Structure Consistency.

The intellectual property of deep networks can be easily "stolen" by surrogate model attack. There has been significant progress in protecting the model IP in classification tasks. However, little attention has been devoted to the protection of image processing models. By utilizing consistent invisible spatial watermarks, the work [1] first considered model watermarking for deep image processing networks and demonstrated its efficacy in many downstream tasks. Its success depends on the hypothesis that if a consistent watermark exists in all prediction outputs, that watermark will be learned into the attacker's surrogate model. However, when the attacker uses common data augmentation attacks (e.g., rotate, crop, and resize) during surrogate model training, it will fail because the underlying watermark consistency is destroyed. To mitigate this issue, we propose a new watermarking methodology, "structure consistency", based on which a new deep structure-aligned model watermarking algorithm is designed. Specifically, the embedded watermarks are designed to be aligned with physically consistent image structures, such as edges or semantic regions. Experiments demonstrate that our method is more robust than the baseline in resisting data augmentation attacks. Besides that, we test the generalization ability and robustness of our method to a broader range of adaptive attacks.

A Review of Chloride Penetration of Recycled Concrete with Enhancement Treatment and Service Life Prediction.

The application of recycled coarse aggregate (RA) in structural concrete can save non-renewable resources and reduce land occupation. Developing comprehensive knowledge of chloride penetration and service life modeling of recycled coarse aggregate concrete (RAC) is a prerequisite for practice. However, compared with the natural aggregate concrete (NAC), the inferior durability performance, especially chloride penetration resistance, of RAC hinders its application in structural concrete. Therefore, many RAC performance enhancement methods have been proposed. This paper presents a holistic review focused on the chloride penetration of RAC with/without enhancement methods and service life prediction. The current RAC performance enhancement methods are introduced. The improvement effect of the corresponding enhancement methods on the chloride penetration resistance of RAC are discussed and analyzed in turn. Based on the reviewed data on the chloride diffusion coefficient, the modification efficiencies of assorted enhancement methods are summarized. With the hope of promoting RAC application in structural concrete, the current literature on chloride-ingress-based service life prediction for RAC is also overviewed. In addition, the typical influencing factors on chloride transport properties are also discussed, i.e., RA quality. It can be concluded that enhancement techniques can effectively improve the chloride penetration resistance of RAC. The old mortar enhancement or removal methods can improve the chloride penetration resistance by 15-30%, depending on the specific treatment measures. The modification efficiency of the modifier material depends on the specific type and content of the incorporated substance, which ranges from approximately 5% to 95%. The estimated service life of RAC structures decreases with the increasing RA replacement ratio. Finally, concluding remarks are provided concerning future research on the chloride transport behavior of RAC.

Transcriptome-based analysis reveals a crucial role of the 20E/HR3 pathway in the diapause of Pieris rapae.

Pieris rapae is among the most damaging pests globally, and diapause makes it highly resistant to environmental stresses, playing a crucial role in the survival and reproduction of P. rapae while exacerbating the challenges of pest management and control. However, the mechanisms of its diapause regulation remain poorly understood. This research used RNA sequencing to profile the transcriptomes of three diapause phases (induction and preparation, initiation, maintenance) and synchronous nondiapause phases in P. rapae. During each comparison phase, 759, 1045, and 4721 genes were found to be differentially expressed. Among these, seven clock genes and seven pivotal hormone synthesis and metabolism genes were identified as having differential expression patterns in diapause type and nondiapause type. The weighted gene co-expression network analysis (WGCNA) revealed the red and blue modules as pivotal for diapause initiation, while the grey module was identified to be crucial to diapause maintenance. Meanwhile, the hub genes HDAC11, METLL16D, Dyw-like, GST, and so on, were identified within these hub modules. Moreover, an ecdysone downstream nuclear receptor gene, HR3, was found to be a shared transcription factor across all three phases. RNA interference of HR3 resulted in delayed pupal development, indicating its involvement in regulating pupal dipause in P. rapae. The further hormone assays revealed that the 20-hydroxyecdysone (20E) titer in diapause type pupae was lower than that in nondiapause type pupae, which exhibited a similar trend to HR3. When 20E was injected into diapause pupae, the HR3 expression levels were improved, and the pupal diapause were broken. These results indicate that the 20E/HR3 pathway is a critical pathway for the diapause regulation of P. rapae, and perturbing this pathway by ecdysone treatment or RNAi would result in the disruption of diapause. These findings provide initial insights into the molecular mechanisms of P. rapae diapause and suggest the potential use of ecdysone analogs and HR3 RNAi pesticides, which specifically target to diapause, as a means of pest control in P. rapae.