Deep learning facilitated superhigh-resolution recognition of structured light ellipticities.

Elliptical beams (EBs), an essential family of structured light, have been investigated theoretically due to their intriguing mathematical properties. However, their practical application has been significantly limited due to the inability to determine all their physical quantities, particularly the ellipticity factor, a unique parameter for EBs of different families. In this paper, to our knowledge, we proposed the first high-accuracy approach that can effectively distinguish EBs with an ellipticity factor difference of 0.01, equivalent to 99.9% field similarities. The method is based on a transformer deep learning (DL) network, and the accuracy has reached 99% for two distinct families of exemplified EBs. To prove that the high performance of this model can dramatically extend the practical aspect of EBs, we used EBs as information carriers in free-space optical communication for an image transmission task, and an error bit rate as low as 0.22% is achieved. Advancing the path of such a DL approach will facilitate the research of EBs for many practical applications such as optical imaging, optical sensing, and quantum-related systems.

Transcriptomic analysis reveals molecular characterization and immune landscape of PANoptosis-related genes in atherosclerosis.

BACKGROUND: Atherosclerosis is a chronic inflammatory disease characterized by abnormal lipid deposition in the arteries. Programmed cell death is involved in the inflammatory response of atherosclerosis, but PANoptosis, as a new form of programmed cell death, is still unclear in atherosclerosis. This study explored the key PANoptosis-related genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis. METHODS: We evaluated differentially expressed genes (DEGs) and immune infiltration landscape in atherosclerosis using microarray datasets and bioinformatics analysis. By intersecting PANoptosis-related genes from the GeneCards database with DEGs, we obtained a set of PANoptosis-related genes in atherosclerosis (PANoDEGs). Functional enrichment analysis of PANoDEGs was performed and protein-protein interaction (PPI) network of PANoDEGs was established. The machine learning algorithms were used to identify the key PANoDEGs closely linked to atherosclerosis. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of key PANoDEGs. CIBERSORT was used to analyze the immune infiltration patterns in atherosclerosis, and the Spearman method was used to study the relationship between key PANoDEGs and immune infiltration abundance. The single gene enrichment analysis of key PANoDEGs was investigated by GSEA. The transcription factors and target miRNAs of key PANoDEGs were predicted by Cytoscape and online database, respectively. The expression of key PANoDEGs was validated through animal and cell experiments. RESULTS: PANoDEGs in atherosclerosis were significantly enriched in apoptotic process, pyroptosis, necroptosis, cytosolic DNA-sensing pathway, NOD-like receptor signaling pathway, lipid and atherosclerosis. Four key PANoDEGs (ZBP1, SNHG6, DNM1L, and AIM2) were found to be closely related to atherosclerosis. The ROC curve analysis demonstrated that the key PANoDEGs had a strong diagnostic potential in distinguishing atherosclerotic samples from control samples. Immune cell infiltration analysis revealed that the proportion of initial B cells, plasma cells, CD4 memory resting T cells, and M1 macrophages was significantly higher in atherosclerotic tissues compared to normal tissues. Spearman analysis showed that key PANoDEGs showed strong correlations with immune cells such as T cells, macrophages, plasma cells, and mast cells. The regulatory networks of the four key PANoDEGs were established. The expression of key PANoDEGs was verified in further cell and animal experiments. CONCLUSIONS: This study evaluated the expression changes of PANoptosis-related genes in atherosclerosis, providing a reference direction for the study of PANoptosis in atherosclerosis and offering potential new avenues for further understanding the pathogenesis and treatment strategies of atherosclerosis.

Putative causal relations among gut flora, serums metabolites and arrhythmia: a Mendelian randomization study.

BACKGROUND: The pathogenesis of cardiac arrhythmias is multifaceted, encompassing genetic, environmental, hemodynamic, and various causative factors. Emerging evidence underscores a plausible connection between gut flora, serum metabolites, and specific types of arrhythmias. Recognizing the role of host genetics in shaping the microbiota, we employed two-sample Mendelian randomization analyses to investigate potential causal associations between gut flora, serum metabolites, and distinct arrhythmias. METHODS: Mendelian randomization methods were deployed to ascertain causal relationships between 211 gut flora, 575 serum metabolites, and various types of arrhythmias. To ensure the reliability of the findings, five complementary Mendelian randomization methods, including inverse variance weighting methods, were employed. The robustness of the results was scrutinized through a battery of sensitivity analyses, incorporating the Cochran Q test, leave-one-out test, and MR-Egger intercept analysis. RESULTS: Eighteen gut flora and twenty-six serum metabolites demonstrated associations with the risk of developing atrial fibrillation. Moreover, ten gut flora and fifty-two serum metabolites were linked to the risk of developing supraventricular tachycardia, while eight gut flora and twenty-five serum metabolites were associated with the risk of developing tachycardia. Additionally, six gut flora and twenty-one serum metabolites exhibited associations with the risk of developing bradycardia. CONCLUSION: This study revealed the potential causal relationship that may exist between gut flora, serum metabolites and different cardiac arrhythmias and highlights the need for further exploration. This study provides new perspectives to enhance diagnostic and therapeutic strategies in the field of cardiac arrhythmias.

Explore the genetic exposure to alopecia areata.

BACKGROUND: Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation. METHODS: This study employed Mendelian randomization (MR), utilizing data from genome-wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR-Egger regression intercept test, MR-PRESSO global test, and leave-one-out analysis, to assess the robustness of the results. RESULTS: MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75-0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values < 0.05). CONCLUSION: This study provides genetic evidence of the relationships between trace elements, serum metabolites, and alopecia areata, underscoring the potential value of targeted therapeutic strategies and preventive measures. Future research should expand to diverse populations and further explore the specific roles of these biomarkers in the disease mechanism.

Motion screening of fiducial marker for improved localization precision and resolution in SMLM.

Single-molecule localization microscopy (SMLM) provides unmatched high resolution but relies on accurate drift correction due to the long acquisition time for each field of view. A popular drift correction is implemented via referencing to fiducial markers that are assumed to be firmly immobilized and remain stationary relative to the imaged sample. However, there is so far lack of efficient approaches for evaluating other motions except sample drifting of immobilized markers and for addressing their potential impacts on images. Here, we developed a new approach for quantitatively assessing the motions of fiducial markers relative to the sample via mean squared displacement (MSD) analysis. Our findings revealed that over 90% of immobilized fluorescent beads in the SMLM imaging buffer exhibited higher MSDs compared to stationary beads in dry samples and displayed varying degrees of wobbling relative to the imaged field. By excluding extremely high-MSD beads in each field from drift correction, we optimized drift correction and experimentally measured localization precision. In SMLM experiments of cellular microtubules, we also found that including only relatively low-MSD beads for drift correction significantly improved the image resolution and quality. Our study presents a simple and effective approach to assess the potential relative motions of fiducial markers and emphasizes the importance of pre-screening fiducial markers for improved image quality and resolution in SMLM imaging.

Diagnosis and detection of pneumonia using weak-label based on X-ray images: a multi-center study.

PURPOSE: Development and assessment the deep learning weakly supervised algorithm for the classification and detection pneumonia via X-ray. METHODS: This retrospective study analyzed two publicly available dataset that contain X-ray images of pneumonia cases and normal cases. The first dataset from Guangzhou Women and Children's Medical Center. It contains a total of 5,856 X-ray images, which are divided into training, validation, and test sets with 8:1:1 ratio for algorithm training and testing. The deep learning algorithm ResNet34 was employed to build diagnostic model. And the second public dataset were collated by researchers from Qatar University and the University of Dhaka along with collaborators from Pakistan and Malaysia and some medical doctors. A total of 1,300 images of COVID-19 positive cases, 1,300 normal images and 1,300 images of viral pneumonia for external validation. Class activation map (CAM) were used to location the pneumonia lesions. RESULTS: The ResNet34 model for pneumonia detection achieved an AUC of 0.9949 [0.9910-0.9981] (with an accuracy of 98.29% a sensitivity of 99.29% and a specificity of 95.57%) in the test dataset. And for external validation dataset, the model obtained an AUC of 0.9835[0.9806-0.9864] (with an accuracy of 94.62%, a sensitivity of 92.35% and a specificity of 99.15%). Moreover, the CAM can accurately locate the pneumonia area. CONCLUSION: The deep learning algorithm can accurately detect pneumonia and locate the pneumonia area based on weak supervision information, which can provide potential value for helping radiologists to improve their accuracy of detection pneumonia patients through X-ray images.

Feasibility analysis of combined surgery for esophageal cancer.

BACKGROUND: As the preoperative examination of esophageal cancer has improved, the likelihood of finding diseases in other organs that require surgical treatment has also increased. The purpose of this study was to explore the feasibility of combined surgery for esophageal cancer by analyzing the occurrence of postoperative complications in patients with esophageal cancer. METHODS: The clinical characteristics of 1566 patients with esophageal cancer who underwent thoracic surgery in our hospital between January 2017 and September 2022 were analyzed retrospectively. The feasibility of combined surgery for esophageal cancer was analyzed by comparing postoperative complications in patients who underwent simple esophageal cancer surgery (SEC) with those in patients who underwent combined surgery for esophageal cancer (COEC). The tendency scores of patients in the COEC and SEC groups (1:2) were matched to balance the confounding clinical factors, and the difference in postoperative complications was further analyzed. Moreover, we performed a subgroup analysis of esophagectomy combined with lung resection (ECL). In addition, the independent risk factors for postoperative Clavien-Dindo ≥ grade III complications of esophageal cancer were analyzed by multivariate logistic regression. RESULTS: A total of 1566 patients (1147 (73.2%) males and 419 (26.8%) females), with an average age of 64.2 years, were analyzed. There was no significant difference in postoperative complications between the SEC and COEC groups according to the Clavien-Dindo classification (P=0.713). An analysis of the complications revealed that those in the COEC group had a higher incidence of lung consolidation than those in the SEC group (P=0.007). However, when we performed propensity score matching (PSM) on the SEC and COEC groups, there was still no significant difference in complications according to the Clavien-Dindo classification (P=0.346); furthermore, when a detailed analysis of complications was performed, there was no significant difference between the two. In subgroup analysis, after we performed PSM in ECL patients and SEC patients, we also found no significant difference in postoperative complications between patients with ECL and patients with SEC. In addition, we found that a history of diabetes (OR=1.604, P=0.029, 95% CI=1.049-2.454), a history of coronary heart disease (OR=1.592, P=0.046, 95% CI=1.008-2.515), diffusing capacity of the lungs for carbon monoxide (DLCO) (OR=0.916, P=0.024, 95% CI=0.849-0.988), and ALB level (OR=0.955, P=0.007, 95% CI=0.924-0.987) were independent factors that influenced postoperative complications in esophageal cancer patients with grade III or higher complications. CONCLUSION: Combined surgery for esophageal cancer does not increase the incidence of postoperative complications. In addition, a history of diabetes mellitus or coronary heart disease, carbon monoxide dispersion, and preoperative ALB level are independent risk factors for grade III or higher postoperative complications of esophageal cancer.

Roles of p53-Mediated Host-Virus Interaction in Coronavirus Infection.

The emergence of the SARS-CoV-2 coronavirus has garnered global attention due to its highly pathogenic nature and the resulting health crisis and economic burden. Although drugs such as Remdesivir have been considered a potential cure by targeting the virus on its RNA polymerase, the high mutation rate and unique 3' to 5' exonuclease with proofreading function make it challenging to develop effective anti-coronavirus drugs. As a result, there is an increasing focus on host-virus interactions because coronaviruses trigger stress responses, cell cycle changes, apoptosis, autophagy, and the dysregulation of immune function and inflammation in host cells. The p53 tumor suppressor molecule is a critical regulator of cell signaling pathways, cellular stress responses, DNA repair, and apoptosis. However, viruses can activate or inhibit p53 during viral infections to enhance viral replication and spread. Given its pivotal role in cell physiology, p53 represents a potential target for anti-coronavirus drugs. This review aims to summarize the relationship between p53 and coronaviruses from various perspectives, to shed light on potential targets for antiviral drug development and vaccine design.

Impacts of carbon markets and subsidies on carbon capture and storage retrofitting of existing coal-fired units in China.

Carbon capture and storage (CCS) is a feasible technology option to reduce carbon emission in the power industry. However, the high cost of CCS deployment in power plants precludes its large-scale application. Carbon markets may act as an incentive for CCS, but the impact of auction and quota allocation mechanisms in carbon markets on CCS is unclear. In order to investigate the roles of the auction and quota allocation mechanism on the CCS retrofitting in coal-fired units, the life-cycle cost method was used to evaluate the CCS retrofitting cost of China's coal-fired units in the carbon market after supplementing the existing database. The impact of subsidies on stimulating CCS retrofitting was jointly considered. The results show that most units have a CCS retrofit Levelized additional cost of electricity (Lacoe) of $25.24/MWh to $64.57/MWh, making the CCS retrofitting burdensome, even for ultra-supercritical unit that has a low cost. The combination of grandfathering quota allocation mechanism and subsidy will effectively promote CCS retrofitting of coal-fired units, especially when the auction ratio is 30%-40%, about 400-540 GW units will be retrofitted under the carbon market using grandfathering and 12.05$/MWh-22.77$/MWh subsidies. Additionally, there are significant differences among provinces in terms of the lifetime costs of the CCS retrofitting of coal-fired units. Xinjiang, Guangdong, and Jiangsu, with retrofitting potentials of respectively 20.68 GW, 10.58 GW-43.00 GW and 15.00 GW-52.27 GW are best suited for the CCS retrofitting of coal-fired units.

Potentially toxic elements in smoke particles and residual ashes by biomass combustion from Huangshi National Mine Park, China.

This paper investigates the fractional and spatial distribution characteristics of potentially toxic elements (PTEs) in smoke particles and residual ashes from mine-park-biomass combustion. It then evaluates the consequential potential environment risk by using a Geo-accumulation index and Nemerow pollution index methods. Biomass combustibles are comprised of Camphor leaves (CL), Camphor dead-branch (CB), Ramie (RA), Miscanthus sinensis (MS), and Dryopteris (DR). The results show that the products of combustion contain PTEs, As, Cr, Cu, and Zn, etc. Among them, the content of As, Cr, Cu, Pb elements in smoke particles of CB was higher than other combustibles. Moreover, Cr, Mn, Ni, and Pb in residual ashes of CL were higher than others. The proportion of acid-soluble and reducible fraction of As in residual ash was higher, while Cr existed mainly in the oxidizable and residual fraction. Besides, the available state of As gradually decreased from 74% (400 °C) to 41% (800 °C), indicating that the increase of temperature significantly reduced the bioavailability of As. Meanwhile, with the increase of temperature, the concentration of PTEs in smoke particles decreased and PTEs in residual ashes increased in different degrees. The risk evaluation results indicate that PTEs may cause moderate or higher levels of contamination. The overall contamination level of PTEs in the residual ashes of CB was higher than that of other plant. The results show in this study would contribute to understanding the environmental risks of wildfire and prescribed burning in PTEs-contaminated areas.

Different gastric tubes in esophageal reconstruction during esophagectomy.

Esophagectomy is currently the mainstay of treatment for resectable esophageal carcinoma. Gastric grafts are the first substitutes in esophageal reconstruction. According to the different tailoring methods applied to the stomach, gastric grafts can be classified as whole stomach, subtotal stomach and gastric tube. Gastric-tube placement has been proven to be the preferred method, with advantages in terms of postoperative complications and long-term survival. In recent years, several novel methods involving special-shaped gastric tubes have been proposed, which have further decreased the incidence of perioperative complications. This article will review the progress and clinical application status of different types of gastric grafts from the perspectives of preparation methods, studies of anatomy and perioperative outcomes, existing problems and future outlook.

Macrophage-derived exosomal miR-4532 promotes endothelial cells injury by targeting SP1 and NF-κB P65 signalling activation.

Atherosclerosis is a complex pathological process involving macrophages, endothelial cells and vascular smooth muscle cells that can lead to ischemic heart disease; however, the mechanisms underlying cell-to-cell communication in atherosclerosis are poorly understood. In this study, we focused on the role of exosomal miRNAs in crosstalk between macrophages and endothelial cells and explored the rarely studied molecular mechanisms involved. Our in vitro result showed that macrophage-derived exosomal miR-4532 significantly disrupted human umbilical vein endothelial cells (HUVECs) function by targeting SP1 and downstream NF-κB P65 activation. In turn, increased endothelin-1 (ET-1), intercellular cell adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) and decreased endothelial nitric oxide synthase (eNOS) expression in HUVECs increased attraction of macrophages, exacerbating foam cell formation and transfer of exosomal miR-4532 to HUVECs. MiR-4532 overexpression significantly promoted endothelial injury and pretreatment with an inhibitor of miR-4532 or GW4869 (exosome inhibitor) could reverse this injury. In conclusion, our data reveal that exosomes have a critical role in crosstalk between HUVECs and macrophages. Further, exosomal miR-4532 transferred from macrophages to HUVECs and targeting specificity protein 1 (SP1) may be a novel therapeutic target in patients with atherosclerosis.

Triacetyl Resveratrol Inhibits PEDV by Inducing the Early Apoptosis In Vitro.

PEDV represents an ancient Coronavirus still causing huge economic losses to the porcine breeding industry. Resveratrol has excellent antiviral effects. Triacetyl resveratrol (TCRV), a novel natural derivative of resveratrol, has been recently discovered, and its pharmacological effects need to be explored further. This paper aims to explore the relationship between PEDV and TCRV, which offers a novel strategy in the research of antivirals. In our study, Vero cells and IPEC-J2 cells were used as an in vitro model. First, we proved that TCRV had an obvious anti-PEDV effect and a strong inhibitory effect at different time points. Then, we explored the mechanism of inhibition of PEDV infection by TCRV. Our results showed that TCRV could induce the early apoptosis of PEDV-infected cells, in contrast to PEDV-induced apoptosis. Moreover, we observed that TCRV could promote the expression and activation of apoptosis-related proteins and release mitochondrial cytochrome C into cytoplasm. Based on these results, we hypothesized that TCRV induced the early apoptosis of PEDV-infected cells and inhibited PEDV infection by activating the mitochondria-related caspase pathway. Furthermore, we used the inhibitors Z-DEVD-FMK and Pifithrin-α (PFT-α) to support our hypothesis. In conclusion, the TCRV-activated caspase pathway triggered early apoptosis of PEDV-infected cells, thereby inhibiting PEDV infections.

Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy.

The photosynthetic capacity or the CO2-saturated photosynthetic rate (Vmax), chlorophyll, and nitrogen are closely linked leaf traits that determine C4 crop photosynthesis and yield. Accurate, timely, rapid, and non-destructive approaches to predict leaf photosynthetic traits from hyperspectral reflectance are urgently needed for high-throughput crop monitoring to ensure food and bioenergy security. Therefore, this study thoroughly evaluated the state-of-the-art physically based radiative transfer models (RTMs), data-driven partial least squares regression (PLSR), and generalized PLSR (gPLSR) models to estimate leaf traits from leaf-clip hyperspectral reflectance, which was collected from maize (Zea mays L.) bioenergy plots with diverse genotypes, growth stages, treatments with nitrogen fertilizers, and ozone stresses in three growing seasons. The results show that leaf RTMs considering bidirectional effects can give accurate estimates of chlorophyll content (Pearson correlation r=0.95), while gPLSR enabled retrieval of leaf nitrogen concentration (r=0.85). Using PLSR with field measurements for training, the cross-validation indicates that Vmax can be well predicted from spectra (r=0.81). The integration of chlorophyll content (strongly related to visible spectra) and nitrogen concentration (linked to shortwave infrared signals) can provide better predictions of Vmax (r=0.71) than only using either chlorophyll or nitrogen individually. This study highlights that leaf chlorophyll content and nitrogen concentration have key and unique contributions to Vmax prediction.

Efficacy of New Zeolite-Based Hemostatic Gauze in a Gunshot Model of Junctional Femoral Artery Hemorrhage in Swine.

BACKGROUND: This work sought to (1) establish a reliable gunshot model of junctional femoral artery rupture in swine that accurately simulates field rescue conditions and (2) use the gunshot model to compare the efficacy and ease of application of zeolite nanometer hemostatic gauze with other hemostatic materials. METHODS: Thirty-six healthy landrace swine (body weight 50 ± 5 kg) were randomly divided into three groups which were treated with Combat Gauze (CG), FeiChuang hemostatic gauze (FG), or standard medical gauze (SG). A gunshot model of femoral artery hemorrhage in landrace swine was used with portable ultrasound to accurately position the wound. After the shooting, when mean arterial pressure of swine decreased by at least 30% for 10 s, wounds were pressed with standard packing (39 g) of gauze materials for 3 min to stop bleeding, then bandaged with pressure. Blood samples were taken 15 min before injury, then 10 min, 30 min, and 60 min after injury to determine hemodynamic, coagulation, and arterial blood gas indexes. Wound temperatures were taken at 5 min, 10 min, 30 min, and 60 min after injury, and survival times were recorded. The volume of blood loss and survival time were used to evaluate hemostatic effect, whereas the fill time, wound temperature, and physiological indexes were used to evaluate the safety and operation of the product. RESULTS: The CG (11.15 ± 3.09 mL/kg) and FG (12.19 ± 3.5 mL/kg) groups had significantly less blood loss than the SG group (16.8 ± 5.14 mL/kg) (P = 0.04; P = 0.039, respectively). After gauze packing, bleeding in CG (5.85 ± 1.17 mL/kg) and FG (5.37 ± 0.93 mL/kg) groups remained significantly lower than that of the SG group (6.93 ± 1.03 mL/kg) (P = 0.011; P = 0.003, respectively). Wound temperature rose with time for all groups (P < 0.001). The wound temperatures in the FG group and the CG group were significantly higher than that of the SG group (P = 004 and 0.009, respectively). Survival rates and times were not significantly different among the three groups, although the FG group had the longest average survival time (standard deviation [SD] 204.8 s), compared with the SG group (SD 177.8 s) and CG (SD 187.5 s) groups. No significant differences in hemodynamics, blood gas, and coagulation were observed among the three groups. CONCLUSIONS: The gunshot model of junctional femoral arterial hemorrhage guided by ultrasound had high accuracy for femoral arterial rupture by bullet wound and provided consistent and reproducible field-simulation conditions for comparison of hemostatic materials. FeiChuang zeolite hemostatic gauze effectively controlled bleeding as well as combat gauze, without excessive heat as found in other zeolite-based products. However, improvements to application technique, such as a packing device, are needed to improve operating time.

Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide.

Acoustic emission (AE) monitoring has become an optional technology to quantify slope deformation. However, there are still challenges in developing generic AE interpretation strategies. Dynamics and kinematics models are two physical methods for analysing slope stability, which appear to improve the interpretability of AE monitoring data. The aim of this study is to explore the change patterns and interrelations of dynamics, kinematics, and AE measurements using a model test and physical analysis, to further understand the development process of a progressive landslide. A model test is designed based on the kinematics model of landslide three-stage deformation. An equation between factor of safety (FoS) and thrust is proposed based on the mechanical model of a landslide test. There is a clear correspondence between the displacement and inverse velocity during the deformation-controlled process. Relationships are uncovered between the thrust and FoS as well as the thrust and acceleration. As a characteristic parameter of AE, ring down count (RDC) is able to quantify the deformation process of the soil slope. Moreover, acceleration and RDC can reflect the sudden change of the slope state and, hence, can be effective indicators for the early warning in a progressive landslide.

Roles of the 2-Oxoglutarate-Dependent Dioxygenase Superfamily in the Flavonoid Pathway: A Review of the Functional Diversity of F3H, FNS I, FLS, and LDOX/ANS.

The 2-oxoglutarate-dependent dioxygenase (2-OGD) superfamily is one of the largest protein families in plants. The main oxidation reactions they catalyze in plants are hydroxylation, desaturation, demethylation, epimerization, and halogenation. Four members of the 2-OGD superfamily, i.e., flavonone 3ß-hydroxylase (F3H), flavones synthase I (FNS I), flavonol synthase (FLS), and anthocyanidin synthase (ANS)/leucoanthocyanidin dioxygenase (LDOX), are present in the flavonoid pathway, catalyzing hydroxylation and desaturation reactions. In this review, we summarize the recent research progress on these proteins, from the discovery of their enzymatic activity, to their functional verification, to the analysis of the response they mediate in plants towards adversity. Substrate diversity analysis indicated that F3H, FNS Ⅰ, ANS/LDOX, and FLS perform their respective dominant functions in the flavonoid pathway, despite the presence of functional redundancy among them. The phylogenetic tree classified two types of FNS Ⅰ, one mainly performing FNS activity, and the other, a new type of FNS present in angiosperms, mainly involved in C-5 hydroxylation of SA. Additionally, a new class of LDOXs is highlighted, which can catalyze the conversion of (+)-catechin to cyanidin, further influencing the starter and extension unit composition of proanthocyanidins (PAs). The systematical description of the functional diversity and evolutionary relationship among these enzymes can facilitate the understanding of their impacts on plant metabolism. On the other hand, it provides molecular genetic evidence of the chemical evolution of flavonoids from lower to higher plants, promoting plant adaptation to harsh environments.

On the Reliability of a Solitary Wave Based Transducer to Determine the Characteristics of Some Materials.

In the study presented in this article we investigated the feasibility and the reliability of a transducer design for the nondestructive evaluation (NDE) of the stiffness of structural materials. The NDE method is based on the propagation of highly nonlinear solitary waves (HNSWs) along a one-dimensional chain of spherical particles that is in contact with the material to be assessed. The chain is part of a built-in system designed and assembled to excite and detect HNSWs, and to exploit the dynamic interaction between the particles and the material to be inspected. This interaction influences the time-of-flight and the amplitude of the solitary pulses reflected at the transducer/material interface. The results of this study show that certain features of the waves are dependent on the modulus of elasticity of the material and that the built-in system is reliable. In the future the proposed NDE method may provide a cost-effective tool for the rapid assessment of materials' modulus.

Identification of ferroptosis biomarkers and immune infiltration landscapes in atrial fibrillation: A bioinformatics analysis.

Ferroptosis has been recognized as a critical factor in the development of atrial fibrillation (AF), but its precise mechanisms remain unclear. We downloaded the GSE115574 dataset from the gene expression omnibus database to analyze the expression levels of ferroptosis-related genes (FRGs) and identify differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) machine learning techniques were employed to identify key genes associated with AF. The diagnostic performance of these genes was evaluated using Receiver operating characteristic curves (ROC) and validated in an independent AF dataset. miRNA and lncRNA predictions for potential binding to these key genes were conducted using miRBase, miRDB, and TargetScan. Furthermore, gene set enrichment analysis (GSEA) enrichment analysis, immune cell infiltration analysis, and targeted drug prediction were performed. The intersection of LASSO regression and SVM-RFE analyses identified 7 DEGs significantly associated with AF. Validation through ROC and an additional dataset confirmed the importance of MAPK14, CAV1, and ADAM23. Significant infiltration of memory B cells, regulatory T cells, and monocytes was observed in atrial tissues. Seventy-two miRNAs were predicted to potentially target MAPK14, and 2 drugs were identified as targeting CAV1. This study underscores the involvement of FRGs in AF through machine learning and validation approaches. The observed immune cell infiltration suggests a potential link between immune response and AF. The predicted ceRNA network offers new insights into gene regulation, presenting potential biomarkers and therapeutic targets for AF.

Total organic carbon content estimation for mixed shale using Xgboost method and implication for shale oil exploration.

In this study, the Xgboost method is employed for TOC estimation in mixed carbonate and siliciclastic shale from the Hashan area, Junggar Basin. The results show that this approach is effective for TOC estimation in this area although the model performance is not very excellent with a correlation coefficient of 0.54 between measured TOC and predicted TOC values, likely due to a small samples dataset. Therefore, the PCA method is applied to debase dimension of well log data from five dimensional to two-dimensional data, which enhances the correlation coefficient between the predicted and measured TOC from 0.54 to 0.68. Based on the model, the isopleth maps of TOC distributions in Fengcheng Formation were redrawn showing two shale oil exploration targets, which likely correspond to two depositional centers of this strata. All the same, the model in this work provides reliable data for shale oil evaluation in the study area and a good example under similar geological setting.