Structure-based virtual screening identifies small-molecule inhibitors of O-fucosyltransferase SPINDLY in Arabidopsis.

Protein O-glycosylation is a nutrient signaling mechanism that plays an essential role in maintaining cellular homeostasis across different species. In plants, SPINDLY (SPY) and SECRET AGENT (SEC) posttranslationally modify hundreds of intracellular proteins with O-fucose and O-linked N-acetylglucosamine, respectively. SPY and SEC play overlapping roles in cellular regulation, and loss of both SPY and SEC causes embryo lethality in Arabidopsis (Arabidopsis thaliana). Using structure-based virtual screening of chemical libraries followed by in vitro and in planta assays, we identified a SPY O-fucosyltransferase inhibitor (SOFTI). Computational analyses predicted that SOFTI binds to the GDP-fucose-binding pocket of SPY and competitively inhibits GDP-fucose binding. In vitro assays confirmed that SOFTI interacts with SPY and inhibits its O-fucosyltransferase activity. Docking analysis identified additional SOFTI analogs that showed stronger inhibitory activities. SOFTI treatment of Arabidopsis seedlings decreased protein O-fucosylation and elicited phenotypes similar to the spy mutants, including early seed germination, increased root hair density, and defective sugar-dependent growth. In contrast, SOFTI did not visibly affect the spy mutant. Similarly, SOFTI inhibited the sugar-dependent growth of tomato (Solanum lycopersicum) seedlings. These results demonstrate that SOFTI is a specific SPY O-fucosyltransferase inhibitor that can be used as a chemical tool for functional studies of O-fucosylation and potentially for agricultural management.

Suppression of SMXL4 and SMXL5 confers enhanced thermotolerance through promoting HSFA2 transcription in Arabidopsis.

Identifying the essential factors and underlying mechanisms regulating plant heat stress (HS) responses is crucial for mitigating the threat posed by HS on plant growth, development, distribution, and productivity. Here, we found that the Arabidopsis (Arabidopsis thaliana) super-killer2 (ski2) dicer-like4 (dcl4) mutant, characterized by RNA processing defects and accumulation of abundant 22-nt small interfering RNAs (siRNAs) derived from protein-coding transcripts, displayed significantly increased expression levels of HS-responsive genes and enhanced thermotolerance. These traits primarily resulted from the suppression of SMAX1-LIKE4 (SMXL4) and SMXL5, which encode two putative transcriptional regulators that belong to the SMXL protein family. While smxl4 and smxl5 single mutants were similar to wild type, the smxl4 smxl5 double mutant displayed substantially heightened seedling thermotolerance. Further investigation demonstrated that SMXL4 and SMXL5 repressed the transcription of HEAT SHOCK TRANSCRIPTION FACTOR A2 (HSFA2), encoding a master regulator of thermotolerance, independently of EAR motifs. Moreover, SMXL4 and SMXL5 interacted with HSFA1d and HSFA1e, central regulators sensing and transducing HS stimuli, and antagonistically affected their transactivation activity. In addition, HSFA2 directly bound to the SMXL4 and SMXL5 promoters, inducing their expression during recovery from HS. Collectively, our findings elucidate the role of the SMXL4/SMXL5-HSFA2 regulatory module in orchestrating plant thermotolerance under HS.

Dissecting the pleiotropic roles of reactive oxygen species (ROS) in lung cancer: From carcinogenesis toward therapy.

Lung cancer is a major cause of morbidity and mortality. The specific pulmonary structure to directly connect with ambient air makes it more susceptible to damage from airborne toxins. External oxidative stimuli and endogenous reactive oxygen species (ROS) play a crucial role in promoting lung carcinogenesis and development. The biological properties of higher ROS levels in tumor cells than in normal cells make them more sensitive and vulnerable to ROS injury. Therefore, the strategy of targeting ROS has been proposed for cancer therapy for decades. However, it is embarrassing that countless attempts at ROS-based therapies have had very limited success, and no FDA approval in the anticancer list was mechanistically based on ROS manipulation. Even compared with the untargetable proteins, such as transcription factors, ROS are more difficult to be targeted due to their chemical properties. Thus, the pleiotropic roles of ROS provide therapeutic potential for anticancer drug discovery, while a better dissection of the mechanistic action and signaling pathways is a prerequisite for future breakthroughs. This review discusses the critical roles of ROS in cancer carcinogenesis, ROS-inspired signaling pathways, and ROS-based treatment, exemplified by lung cancer. In particular, an eight considerations rule is proposed for ROS-targeting strategies and drug design and development.

Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)，and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.

Targeting LRP6: A new strategy for cancer therapy.

Targeting specific molecular drivers of tumor growth is a key approach in cancer therapy. Among these targets, the low-density lipoprotein receptor-related protein 6 (LRP6), a vital component of the Wnt signaling pathway, has emerged as an intriguing candidate. As a cell-surface receptor and vital co-receptor, LRP6 is frequently overexpressed in various cancer types, implicating its pivotal role in driving tumor progression. The pursuit of LRP6 as a target for cancer treatment has gained substantial traction, offering a promising avenue for therapeutic intervention. Here, this comprehensive review explores recent breakthroughs in our understanding of LRP6's functions and underlying molecular mechanisms, providing a profound discussion of its involvement in cancer pathogenesis and drug resistance. Importantly, we go beyond discussing LRP6's role in cancer by discussing diverse potential therapeutic approaches targeting this enigmatic protein. These approaches encompass a wide spectrum, including pharmacological agents, natural compounds, non-coding RNAs, epigenetic factors, proteins, and peptides that modulate LRP6 expression or disrupt its interactions. In addition, also discussed the challenges associated with developing LRP6 inhibitors and their advantages over Wnt inhibitors, as well as the drugs that have entered phase II clinical trials. By shedding light on these innovative strategies, we aim to underscore LRP6's significance as a valuable and multifaceted target for cancer treatment, igniting enthusiasm for further research and facilitating translation into clinical applications.

Preparation, biological activity and antibacterial properties of tantalum surface-doped Ca2+/Zn2+nanorods.

In this research, we utilize porous tantalum, known for its outstanding elastic modulus and biological properties, as a base material in biomedical applications. The human skeletal system is rich in elements like Ca and Zn. The role of Zn is crucial for achieving a spectrum of sterilizing effects, while Ca is known to effectively enhance cell differentiation and boost cellular activity. The focus of this study is the modification of porous tantalum using a hydrothermal method to synthesize Ca2+/Zn2+-doped Ta2O5nanorods. These nanorods are subjected to extensive characterization techniques to confirm their structure and composition. Additionally, their biological performance is evaluated through a range of tests, including antibacterial assessments, MTT assays, and bacteria/cell scanning electron microscopy (SEM) analyses. The objective is to determine the most effective method of surface modification for porous tantalum, thereby laying a foundational theoretical framework for its surface enhancement.

UPLC/Q-TOF-MS-based metabolomics and molecular docking analysis of Bifidobacterium adolescentis exposure to levofloxacin.

Antibiotic-associated diarrhea is a common adverse reaction caused by the widespread use of antibiotics. The decrease in probiotics is one of the reasons why antibiotics cause drug-induced diarrhea. However, few studies have addressed the intrinsic mechanism of antibiotics inhibiting probiotics. To investigate the underlying mechanism of levofloxacin against Bifidobacterium adolescentis, we used a metabolomics mass spectrometry-based approach and molecular docking analysis for a levofloxacin-induced B. adolescentis injury model. The results showed that levofloxacin reduced the survival rate of B. adolescentis and decreased the number of B. adolescentis. The untargeted metabolomics analysis identified 27 potential biomarkers, and many of these metabolites are involved in energy metabolism, amino acid metabolism and the lipid metabolism pathway. Molecular docking showed that levofloxacin can bind with aminoacyl-tRNA synthetase and lactic acid dehydrogenase. This result provides a novel insight into the mechanism of the adverse reactions of levofloxacin.

Compound probiotics regulate the NRF2 antioxidant pathway to inhibit aflatoxin B1-induced autophagy in mouse Sertoli TM4 cells.

This study investigated the effects of compound probiotics (CP) on AFB1-induced cytotoxicity in Sertoli TM4 cells. The L9 (3 × 3) orthogonal test was conducted to determine the optimal CP required for high AFB1 degradation in the artificial gastrointestinal fluid in vitro. The maximal AFB1 degradation rate was 40.55 % (P < 0.05) when the final viable count was 1.0 × 105 CFU/mL for Bacillus subtilis, Lactobacillus casein, and Saccharomyces cerevisiae. The effects of CP and the CP supernatant (CPS) on TM4 cell viability were evaluated to achieve the optimal protective conditions. When CPS4 (corresponding to CP viable counts of 1.0 × 104 CFU/mL) was added to the TM4 cells for 24 h, the cell viability reached 108.86 % (P < 0.05). AFB1 reduced TM4 cell viability in a concentration- and time-dependent manner at an AFB1 concentration ranging from 0 to 1.5 µM after 48-h AFB1 exposure. The optimal AFB1 concentration/times for low- and high damage models were 0.5 and 1.25 µM both for 24 h, which decreased viability to 76.04 % and 65.35 %, respectively. however, CPS4 added to low- and high-damage models increased the cell viability to 97.43 % and 75.12 %, respectively (P < 0.05). Transcriptome sequencing was performed based on the following designed groups: the control, 0.5 µM AFB1, 1.25 µM AFB1, CPS4, and CPS4+0.5 µM AFB1. The Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis was further performed to identify significantly enriched signaling pathways, which were subsequently verified. It was shown that AFB1 induced apoptosis by blocking the PI3K-AKT-mTOR pathway and upregulating autophagy proteins such as LC3B, Beclin1, and ATG5 while inhibiting autophagic flux. CPS4 promoted AFB1 degradation, activated the p62-NRF2 antioxidant, and inhibited ROS/TRPML1 pathways, thereby reducing ROS production and inflammation and ultimately alleviating AFB1-induced autophagy and apoptosis. These findings supports the potential of probiotics to protect the male reproductive system from toxin damage.

Endoribonuclease DNE1 Promotes Ethylene Response by Modulating EBF1/2 mRNA Processing in Arabidopsis.

The gaseous phytohormone ethylene plays a crucial role in plant growth, development, and stress responses. In the ethylene signal transduction cascade, the F-box proteins EIN3-BINDING F-BOX 1 (EBF1) and EBF2 are identified as key negative regulators governing ethylene sensitivity. The translation and processing of EBF1/2 mRNAs are tightly controlled, and their 3' untranslated regions (UTRs) are critical in these regulations. However, despite their significance, the exact mechanisms modulating the processing of EBF1/2 mRNAs remain poorly understood. In this work, we identified the gene DCP1-ASSOCIATED NYN ENDORIBONUCLEASE 1 (DNE1), which encodes an endoribonuclease and is induced by ethylene treatment, as a positive regulator of ethylene response. The loss of function mutant dne1-2 showed mild ethylene insensitivity, highlighting the importance of DNE1 in ethylene signaling. We also found that DNE1 colocalizes with ETHYLENE INSENSITIVE 2 (EIN2), the core factor manipulating the translation of EBF1/2, and targets the P-body in response to ethylene. Further analysis revealed that DNE1 negatively regulates the abundance of EBF1/2 mRNAs by recognizing and cleaving their 3'UTRs, and it also represses their translation. Moreover, the dne1 mutant displays hypersensitivity to 1,4-dithiothreitol (DTT)-induced ER stress and oxidative stress, indicating the function of DNE1 in stress responses. This study sheds light on the essential role of DNE1 as a modulator of ethylene signaling through regulation of EBF1/2 mRNA processing. Our findings contribute to the understanding of the intricate regulatory process of ethylene signaling and provide insights into the significance of ribonuclease in stress responses.

Least-squares method constrained by phase smoothness for correcting illumination fluctuation errors in phase-shifting profilometry: erratum.

This erratum corrects an error in Eq. (29) of the original paper, Appl. Opt.62, 8451 (2023)APOPAI0003-693510.1364/AO.505327.

A multi-information fusion anomaly detection model based on convolutional neural networks and AutoEncoder.

Network traffic anomaly detection, as an effective analysis method for network security, can identify differentiated traffic information and provide secure operation in complex and changing network environments. To avoid information loss caused when handling traffic data while improving the detection performance of traffic feature information, this paper proposes a multi-information fusion model based on a convolutional neural network and AutoEncoder. The model uses a convolutional neural network to extract features directly from the raw traffic data, and a AutoEncoder to encode the statistical features extracted from the raw traffic data, which are used to supplement the information loss due to cropping. These two features are combined to form a new integrated feature for network traffic, which has the load information from the original traffic data and the global information of the original traffic data obtained from the statistical features, thus providing a complete representation of the information contained in the network traffic and improving the detection performance of the model. The experiments show that the classification accuracy of network traffic anomaly detection using this model outperforms that of classical machine learning methods.

Spatiotemporal variation reconstruction of total phosphorus in the Great Lakes since 2002 using remote sensing and deep neural network.

Total phosphorus (TP) is non-optically active, thus TP concentration (CTP) estimation using remote sensing still exists grand challenge. This study developed a deep neural network model (DNN) for CTP estimation with synchronous in-situ measurements and MODIS-derived remote sensing reflectance (Rrs) (N = 3916). Using DNN, the annual and intra-annual CTP spatial distributions of the Great Lakes since 2002 were reconstructed. Then, the reconstructions were correlated to nine potential factors, e.g., Chlorophyll-a, snowmelt, and cropland, to explain seasonal and long-term CTP variations. The results showed that DNN reliably estimated CTP from MODIS Rrs, with R2, mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and root mean squared logarithmic error (RMSLE) of 0.83, 1.05 µg/L, 2.95 µg/L, 9.92%, and 0.13 on the test set. The near-surface CTP in the Great Lakes decreased significantly (p < 0.05) during 2002 - 2022, primarily attributed to cropland reduction, coupled with improvements in basin natural ecosystems. The sensitivity analysis verified the model robustness when confronted with input feature changes < 35%. This result along with the marginal difference between CTP derived from two sensors (R2 = 0.76, MAE = 2.12 µg/L, RMSE = 2.51 µg/L, MAPE = 11.52%, RMSLE = 0.24) suggested the model transferability from MODIS to VIIRS. This transformation facilitated optimal usage of MODIS-related archive and enhanced the continuity of CTP estimation at moderate resolution. This study presents a practical method for spatiotemporal reconstruction of CTP using remote sensing, and contributes to better understandings of driving factors behind CTP variations in the Great Lakes.

Reconfigurable origami-inspired multistable metamorphous structures.

Origami-inspired metamorphous structures can adjust their shapes and mechanical behaviors according to operational requirements. However, they are typically composed of nonrigid origami, where required facet deformation complicates actuation and makes them highly material dependent. In this study, we present a type of origami metamorphous structure composed of modular bistable units, each of which is a rigid origami. The elasticity within the origami creases and switching of mountain and valley crease lines enable it to have bistability. The resultant metamorphous structure has multistability, allowing it to switch among multifarious configurations with programmable profiles. This concept was validated by potential energy analysis and experiments. Using this concept, we developed a robotic limb capable of both lifting and gripping through configuration changes. Furthermore, we used the origami units to construct a metamaterial whose properties could change with the variation of configurations. These examples demonstrate the concept's remarkable versatility and potential for many applications.

Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma.

BACKGROUND: To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression. METHODS: We retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis. RESULTS: For the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was - 0.03 and cumulative risk rates were calculated. DATA CONCLUSION: To assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.

Characterization of key aroma compounds in a novel Chinese rice wine Xijiao Huojiu during its biological-ageing-like process by untargeted metabolomics.

Xijiao Huojiu (Xijiao), an ancient Chinese rice wine (ACRW), is produced using traditional methods, which involve biological-ageing-like process and result in distinctive sensory profiles. However, its aroma composition is still unclear. In this study, the aroma characteristics of three samples with varying ageing times were examined. Xijiao_SCT, with a short cellar time, exhibited a strong fruity and floral aroma and a less grain-like aroma. Conversely, Xijiao_LCT, which had a long cellar time, had a deep cocoa- and caramel-like aroma. A total of 27 key odorants that greatly influenced the aroma characteristics of Xijiao were identified. Comparative studies were used to identify 12 key odorants that distinguish Xijiao from modern Chinese rice wine (MCRW) and grape wines (GW). Additionally, 13 dominant latent ageing markers differentiated Xijiao_SCT from Xijiao_LCT. Our results suggested that ACRW and MCRW have overlapping but distinct volatile metabolomic profiles, highlighting the characteristics of ACRW during ageing process.

COVID-19 prevention and control effect of non-pharmaceutical interventions-fuzzy-sets qualitative comparative analysis based on 69 countries in the world.

Introduction: Coronavirus disease 2019 occurred unexpectedly in late December 2019, it was difficult to immediately develop an effective vaccine or propose targeted medical interventions in the early stages of the outbreak. At this point, non-pharmaceutical interventions (NPIs) are essential components of the public health response to COVID-19. How to combine different NPIs in the early stages of an outbreak to control the spread of epidemics and ensure that the policy combination does not incur high socio-economic costs became the focus of this study. Methods: We mainly used the fuzzy set qualitative comparative analysis to assess the impact of different combinations of NPIs on the effectiveness of control in the COVID-19 pandemic early stage, using open datasets containing case numbers, country populations and policy responses. Results: We showed that the configuration of high morbidity results includes one, which is the combination of non-strict face covering, social isolation and travel restrictions. The configuration of non-high morbidity results includes three, one is strict mask wearing measures, which alone constitute sufficient conditions for interpreting the results; the second is strict testing and contact tracing, social isolation; the third is strict testing and contact tracing, travel restriction. The results of the robustness test showed that the number, components and consistency of the configurations have not changed after changing the minimum case frequency, which proved that the analysis results are reliable. Conclusion: In the early stages of the epidemic, the causes of high morbidity are not symmetrical with the causes of non-high morbidity. Strict face covering is the most basic measure required to prevent and control epidemics, and the combination of non-strict face covering and containment is the most important factor leading to poor prevention and control, and the combination of strict containment and proactive pursuit is the way to achieve superior prevention and control, timely and proactive containment strategies have better prevention and control, and should mobilize the public to cooperate.

Mycobacterium marinum cutanous infection misdiagnosed as sporotrichosis in a patient with systemic lupus erythematosus: A case report.

Mycobacterium marinum(M. marinum ), a slow-growing bacterium in freshwater and seawater, can cause cutanous and extracutaneous infections. A fisher-woman with systemic lupus erythematosus (SLE) presented with chronic polymorphic rashes in a lymphangitic pattern was initially misdiagnosed as sporotrichosis. The final diagnosis of M. marinum and Candida dubliniensis co-infection was confirmed based on the skin histopathology, pustule culture, MetaCAP sequencing and effective antibiotic combination treatments.

A network pharmacology-based approach to explore the molecular mechanism of Aidi injection against prostate cancer.

Objective: To explore the molecular mechanism of Aidi injection in the treatment of prostate cancer (PCa). Materials and methods: CCK-8 and colony formation assays were used to detect the effects of Aidi on PC3 and DU145 cells; effects on the cell cycle and apoptosis of DU145 cells were detected by flow cytometry; effects on migration and invasion of PC3 and DU145 cells were detected by wound healing and transwell assay, respectively. The main active components of Aidi, their corresponding targets, and PCa associated pathways were predicted and analyzed by network pharmacology. Then predicted key targets and related signaling pathways were further verified by western blotting. The potential active components of Aidi were predicted by molecular docking technology. Results: Aidi significantly inhibited the proliferation, colony formation, migration, and invasion of PC3 and DU145 cells; Aidi induced apoptosis and cell cycle G2/M phase arrest of DU145 cells. Network pharmacology analysis yielded 36 potential core targets of Aidi against PCa, and the top 10 signaling pathways including MAPK, PI3K-Akt, and HIF-1α and so on were enriched. Western blotting confirmed that Aidi upregulated the expression levels of p-JNK, p-p38, p-ERK, and ERK in DU145 cells. Molecular docking study showed that kaempferol, (Z)-1-(2,4-dihydroxyphenyl)-3-(4-hydroxyphenyl)prop-2-en-1-one, 7-O-methylisomucronulatol, calycosin, and N-salicylidene-salicylamine can be well binding with JNK and p38. Conclusion: Aidi could inhibit PCa cell proliferation and metastasis through induction of apoptosis and cell cycle arrest, which may be related to activating JNK and p38 signaling pathway.

Leaf Senescence Database v5.0: A Comprehensive Repository for Facilitating Plant Senescence Research.

Through an extensive literature survey, we have upgraded the Leaf Senescence Database (LSD v5.0; https://ngdc.cncb.ac.cn/lsd/), a curated repository of comprehensive senescence-associated genes (SAGs) and their corresponding mutants. Since its inception in 2010, LSD undergoes frequent updates to encompass the latest advances in leaf senescence research and its current version comprises a high-quality collection of 31,740 SAGs and 1,209 mutants from 148 species, which were manually searched based on robust experimental evidence and further categorized according to their functions in leaf senescence. Furthermore, LSD was greatly enriched with comprehensive annotations for the SAGs through meticulous curation using both manual and computational methods. In addition, it was equipped with user-friendly web interfaces that facilitate text queries, BLAST searches, and convenient download of SAG sequences for localized analysis. Users can effortlessly navigate the database to access a plethora of information, including literature references, mutants, phenotypes, multi-omics data, miRNA interactions, homologs in other plants, and cross-links to various databases. Taken together, the upgraded version of LSD stands as the most comprehensive and informative plant senescence-related database to date, incorporating the largest collection of SAGs and thus bearing great utility for a wide range of studies related to plant senescence.

Clinical outcomes of aortic root repair using pericardial autograft for acute type a aortic dissection.

BACKGROUND: For acute type A aortic dissection involving the aortic root with root diameter no more than 45 mm, there are various aortic root repair techniques. In this study, a novel surgical technique using a pericardial autograft for aortic root repair was introduced. We described its surgical steps in detail and compare its clinical outcomes with direct suture technique. METHODS: Between July 2017 and August 2022, 95 patients with acute type A aortic dissection who underwent aortic root repair were enrolled, including aortic root repair using pericardial autograft (group A, n = 49) or direct suture (group B, n = 46). The patient's clinical data were retrospectively analyzed, and a 5-year follow-up was conducted. RESULTS: The 30-day mortality, re-exploration for bleeding, postoperative new-onset renal failure requiring continuous renal replacement therapy, stroke, and paraplegia occurred in 3%, 4%, 11%, 5%, and 2% of the overall patients, respectively. There was no significant difference in the 30-day mortality and complication rate between the two groups. The 30-day mortality and re-exploration for bleeding marked the primary endpoint events. Logistic regression analysis indicated that there was a significant correlation between the primary endpoint events and surgical technique (odds ratio, 0.002; 95% confidence interval, 0-0.159; P = 0.026). The aortic valve insufficiency of the two groups were significantly improved after operation (group A, P < 0.001; group B, P < 0.001). During follow-up, there was no significant difference in short-term survival between the two groups after surgery (log-rank P = 0.75), and all patients were free from reoperation for aortic disease. CONCLUSIONS: Patients who underwent aortic root repair using pericardial autograft tended to have reduced 30-day mortality and a lower risk of re-exploration for bleeding. Using pericardial autograft for aortic root repair is a safe and useful approach for patients with acute type A aortic dissection involving the aortic root.