Case report: a cataract induced by bleomycin in a patient with testicular cancer.

Background: Bleomycin is a glycopeptide antibiotic with outstanding anti-tumor effects. A major adverse effect of bleomycin is lung fibrosis. However, the development of cataracts as a severe adverse effect has not been reported. Case summary: Herein, we describe the first case of cataract induced by bleomycin therapy in a 22-year-old male with testicular cancer. After surgical intervention and following five successive chemotherapy cycles of the BEP regimen, including bleomycin, etoposide and cisplatin, the patient reported a gradual painless loss of vision, with substantial decline in visual ability, especially in the right eye. Following comprehensive eye examinations, a cataract was diagnosed. Eventually, the patient underwent phacoemulsification and received replacement of the intraocular lenses. Conclusion: Bleomycin can cause cataracts, which induces a significant loss of vision. Therefore, clinicians should observe early symptoms and properly adjust treatment to prevent aggravation of symptoms.

Farmland's silent threat: Comprehensive multimedia assessment of micropollutants through non-targeted screening and targeted analysis in agricultural systems.

Intricate agricultural ecosystems markedly influence the dynamics of organic micropollutants, posing substantial threats to aquatic organisms and human health. This study examined the occurrence and distribution of organic micropollutants across soils, ditch sediment, and water within highly intensified farming setups. Using a non-targeted screening method, we identified 405 micropollutants across 10 sampling sites, which mainly included pesticides, pharmaceuticals, industrial chemicals, and personal care products. This inventory comprised emerging contaminants, banned pesticides, and controlled pharmaceuticals that had eluded detection via conventional monitoring. Targeted analysis showed concentrations of 3.99-1021 ng/g in soils, 4.67-2488 ng/g in sediment, and 12.5-9373 ng/L in water, respectively, for Σ40pesticides, Σ8pharmaceuticals, and Σ3industrial chemicals, indicating notable spatial variability. Soil organic carbon content and wastewater discharge were likely responsible for their spatial distribution. Principal component analysis and correlation analysis revealed a potential transfer of micropollutants across the three media. Particularly, a heightened correlation was decerned between soil and sediment micropollutant levels, highlighting the role of sorption processes. Risk quotients surpassed the threshold of 1 for 13-23 micropollutants across the three media, indicating high environmental risks. This study highlights the importance of employing non-targeted and targeted screening in assessing and managing environmental risks associated with micropollutants.

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to assess comprehensive pathologic characteristics of EGC using white-light endoscopic images and videos. METHODS: To train the model, we retrospectively collected 4,336 images and prospectively included 153 videos from patients with EGC who underwent endoscopic or surgical resection. The performance of the model was tested and compared to that of 16 endoscopists (nine experts and seven novices) using a mutually exclusive set of 260 images and 10 videos. Finally, we conducted external validation using 436 images and 89 videos from another institution. RESULTS: After training, the model achieved predictive accuracies of 89.7% for undifferentiated histology, 88.0% for submucosal invasion, 87.9% for lymphovascular invasion (LVI), and 92.7% for lymph node metastasis (LNM), using endoscopic videos. The area under the curve values of the model were 0.992 for undifferentiated histology, 0.902 for submucosal invasion, 0.706 for LVI, and 0.680 for LNM in the test. In addition, the model showed significantly higher accuracy than the experts in predicting undifferentiated histology (92.7% vs. 71.6%), submucosal invasion (87.3% vs. 72.6%), and LNM (87.7% vs. 72.3%). The external validation showed accuracies of 75.6% and 71.9% for undifferentiated histology and submucosal invasion, respectively. CONCLUSIONS: AI may assist endoscopists with high predictive performance for differentiation status and invasion depth of EGC. Further research is needed to improve the detection of LVI and LNM.

Development and Comparison of Visual LAMP and LAMP-TaqMan Assays for Colletotrichum siamense.

Strawberry anthracnose caused by Colletotrichum spp. has resulted in significant losses in strawberry production worldwide. Strawberry anthracnose occurs mainly at the seedling and early planting stages, and Colletotrichum siamense is the main pathogen in North China, where mycelia, anamorphic nuclei, and conidia produced in the soil are the main sources of infection. The detection of pathogens in soil is crucial for predicting the prevalence of anthracnose. In this study, a visualized loop-mediated isothermal amplification (LAMP) assay and a loop-mediated isothermal amplification method combined with a TaqMan probe (LAMP-TaqMan) assay were developed for the ß-tubulin sequence of C. siamense. Both methods can detect Colletotrichum siamense genomic DNA at very low concentrations (104 copies/g) in soil, while both the visualized LAMP and LAMP-TaqMan assays exhibited a detection limit of 50 copies/µL, surpassing the sensitivity of conventional PCR and qPCR techniques, and both methods showed high specificity for C. siamense. The two methods were compared: LAMP-TaqMan exhibited enhanced specificity due to the incorporation of fluorescent molecular beacons, while visualized LAMP solely necessitated uncomplicated incubation at a constant temperature, with the results determined by the color change; therefore, the requirements for the instrument are relatively straightforward and user-friendly. In conclusion, both assays will help monitor populations of C. siamense in China and control strawberry anthracnose in the field.

Chiral 3D Perovskite Formation Induced by Chiral Templates.

Chiral 3D perovskites pose challenges compared to lower-dimensional variants due to limited chiral organic cation options. Here, we present a universal and controlled method for synthesizing chiral 3D lead halide perovskites using organic amines or alcohols as chiral templates. Introducing these templates to PbCl2 in N,N-dimethylformamide (DMF) under acidic conditions induces the crystallization of R/S [DMA]PbCl3 (DMA = dimethylamine). The resulting structure aligns with the templates used, stemming from the helical Pb2Cl95- chain as verified by single-crystal X-ray diffraction. Furthermore, the chiral perovskite exhibits absorption and circular dichroism (CD) signals in the high-energy band, enabling the circularly polarized light (CPL) detection in the UV spectrum. A CPL detector constructed by this chiral perovskite demonstrates excellent performance, boasting an anisotropy factor for photocurrent (gIph) of 0.296. Our work not only introduces a novel and controllable method for crafting chiral perovskites but also opens new avenues for circularly polarized light detection.

High-yield synthesis of hydroxylated boron nitride nanosheets and their utilization in thermally conductive polymeric nanocomposites.

Hexagonal boron nitride nanosheets (BNNSs) possess remarkable potential for various applications due to their unprecedented properties. However, the scalable production of BNNSs with both expansive surface and high solubility continues to present a significant challenge. Herein, we propose an innovative and efficient two-step method for manufacturing hydroxyl-functionalized BNNSs (OH-BNNSs). Initially, hydroxyl groups are covalently attached to bulk hexagonal boron nitride (h-BN) surfaces through H2O2 treatment. Then, the hydroxyl-functionalized h-BN undergoes exfoliation on account of a sudden increase in interlayer gas pressure generated by the vigorous decomposition of H2O2 in alkali solutions, resulting in the creation of OH-BNNSs. This approach produces relatively large flakes with an average dimension of 1.65 µm and a high yield of 45.2%. The resultant OH-BNNSs exhibit remarkable stability and dispersibility in a range of solvents. Their integration into thermoplastic polyurethane (TPU) significantly enhances both thermal conductivity and stability, attributed to the excellent compatibility with the resin matrix. This study represents a significant advancement in the functionalization and exfoliation of h-BN, opening new avenues for its promising applications in polymer composites.

Volatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase-Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysis.

This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry. Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.

The growth-promoting and disease-suppressing mechanisms of Trichoderma inoculation on peanut seedlings.

Trichoderma spp. is known for its ability to enhance plant growth and suppress disease, but the mechanisms for its interaction with host plants and pathogens remain unclear. This study investigated the transcriptomics and metabolomics of peanut plants (Arachis hypogaea L.) inoculated with Trichoderma harzianum QT20045, in the absence and presence of the stem rot pathogen Sclerotium rolfsii JN3011. Under the condition without pathogen stress, the peanut seedlings inoculated with QT20045 showed improved root length and plant weight, increased indole acetic acid (IAA) production, and reduced ethylene level, with more active 1-aminocyclopropane-1-carboxylate acid (ACC) synthase (ACS) and ACC oxidase (ACO), compared with the non-inoculated control. Under the pathogen stress, the biocontrol efficacy of QT20045 against S. rolfsii was 78.51%, with a similar effect on plant growth, and IAA and ethylene metabolisms to the condition with no biotic stress. Transcriptomic analysis of peanut root revealed that Trichoderma inoculation upregulated the expression of certain genes in the IAA family but downregulated the genes in the ACO family (AhACO1 and AhACO) and ACS family (AhACS3 and AhACS1) consistently in the absence and presence of pathogens. During pathogen stress, QT20045 inoculation leads to the downregulation of the genes in the pectinesterase family to keep the host plant's cell wall stable, along with upregulation of the AhSUMM2 gene to activate plant defense responses. In vitro antagonistic test confirmed that QT20045 suppressed S. rolfsii growth through mechanisms of mycelial entanglement, papillary protrusions, and decomposition. Our findings highlight that Trichoderma inoculation is a promising tool for sustainable agriculture, offering multiple benefits from pathogen control to enhanced plant growth and soil health.

Investigating the mechanism of Fuling-Banxia-Dafupi in the treatment of diabetic kidney disease using network pharmacology and molecular docking.

Go deeply into the molecular mechanism of Fuling-Banxia-Dafupi in the treatment of diabetic kidney disease (DKD) by network pharmacology and molecular docking. Fuling-Banxia-Dafupi is a pair of traditional Chinese medicine for diabetic kidney disease, which can slow down the development of diabetic kidney disease. Screening active components and targets of Fuling-Banxia-Dafupi using the TCMSP database. The Uniprot database was also used to identify effective drug targets. DKD-related Targets were retrieved from the Gene Cards database, and the overlap between these targets and Fuling-Banxia-Dafupi was obtained. GO and KEGG pathway concentration analyses were showed using Metascape, and the results were presented by the microcredit platform. A total of 616 active ingredients and targets were confrimed and intersected with 3,951 diabetic neuropathy-related targets, resulting in 306 common targets. Baicalein and cerevisterol are the core components of Fuling-Banxia-Dafupi, and the key targets are TP53, SRC, and STAT 3. PI3K-Akt signalling pathway is an important pathway. The molecular docking indicated that its main active components and target proteins have good binding activity.

Safety and feasibility of single-incision laparoscopic distal gastrectomy in overweight and obese gastric cancer patients: a propensity score-matched analysis.

BACKGROUND: The technical challenges and safety concerns of single-incision laparoscopic gastrectomy for overweight and obese gastric cancer patients remain unclear. This study aimed to evaluate the safety and feasibility of single-incision laparoscopic distal gastrectomy (SIDG) compared to multiport laparoscopic distal gastrectomy (MLDG) in overweight and obese gastric cancer patients. METHODS: This study retrospectively analyzed overweight and obese patients (body mass index ≥ 25 kg/m2) and pathologic stage T1 primary gastric adenocarcinoma treated with either SIDG or MLDG. The SIDG and MLDG groups were propensity score matched at a 1:2 ratio using age, sex, height, body weight, American Society of Anesthesiologists classification, year of surgery, pathologic N stage, and anastomosis method as covariates. RESULTS: After 1:2 matching, the study included patients who underwent SIDG (n = 179) and MLDG (n = 358). No significant difference in the number of retrieved lymph nodes was found between the SIDG and MLDG groups (52.8 ± 19.3 vs. 53.9 ± 21.0, P = 0.56). Operation times were significantly shorter in the SIDG group (170.8 ± 60.0 min vs. 186.1 ± 52.6 min, P = 0.004). The postoperative hospital length of stay was comparable between the 2 groups (SIDG: 5.9 ± 3.4 days vs. MLDG: 6.3 ± 5.1 days, P = 0.23), as was postoperative complication rate (SIDG: 13.4% vs. MLDG: 12.8%, P = 0.89). CONCLUSIONS: SIDG was shown to be as safe and feasible as MLDG for overweight and obese gastric cancer patients, with comparable early postoperative complication rates without compromising operation time compared to MLDG.

Associations between body mass index and all-cause and CVD mortality in agriculture, forestry, and fishing occupations: A prospective cohort study using NHANES data (1999-2014).

INTRODUCTION: Obesity, as indicated by elevated Body Mass Index (BMI), is a well-established global health concern associated with increased morbidity and mortality across diverse populations. However, the influence of BMI on individuals in Agriculture, Forestry, and Fishing (AFF) occupations, characterized by unique challenges and environmental factors, has received limited research attention. METHODS: Our study, a prospective cohort analysis, utilized National Health and Nutrition Examination Survey (NHANES) data from 1999-2014, targeting adults above 18 in AFF occupations with comprehensive BMI data, omitting individuals with a history of cancer. Mortality outcomes were extracted from the NHANES mortality file, and BMI was segmented into eight categories. Essential covariates such as age, sex, race, and various health factors were incorporated. The statistical analysis encompassed Cox regression, generalized additive models, smooth curve fitting, and stratified analyses. RESULTS: During 1,005 person-years with 201 all-cause and 57 CVD deaths, we observed L-shaped and U-shaped correlations of BMI with all-cause and CVD mortality, featuring a pivotal inflection at 26.69 and 27.40 kg/m2. Above this BMI threshold of 26.69 and 27.4 kg/m2, all-cause mortality association was not significant while CVD mortality was positive. CONCLUSIONS: This study highlights a unique BMI-mortality association in AFF occupations, diverging from standard patterns. The rigorous labor and environmental conditions in AFF jobs suggest that a certain range of higher BMI could reduce mortality risk. This highlights the necessity for tailored health guidelines in different occupations. Future research should concentrate on diverse health indicators and enhanced risk assessment for physically strenuous occupations.

Resistin Regulates Inflammation and Insulin Resistance in Humans via the Endocannabinoid System.

Resistin plays an important role in the pathophysiology of obesity-mediated insulin resistance in mice. However, the biology of resistin in humans is quite different from that in rodents. Therefore, the association between resistin and insulin resistance remains unclear in humans. Here, we tested whether and how the endocannabinoid system (ECS) control circulating peripheral blood mononuclear cells (PBMCs) that produce resistin and infiltrate into the adipose tissue, heart, skeletal muscle, and liver, resulting in inflammation and insulin resistance. Using human PBMCs, we investigate whether the ECS is connected to human resistin. To test whether the ECS regulates inflammation and insulin resistance in vivo, we used 2 animal models such as "humanized" nonobese diabetic/Shi-severe combined immunodeficient interleukin-2Rγ (null) (NOG) mice and "humanized" resistin mouse models, which mimic human body. In human atheromatous plaques, cannabinoid 1 receptor (CB1R)-positive macrophage was colocalized with the resistin expression. In addition, resistin was exclusively expressed in the sorted CB1R-positive cells from human PBMCs. In CB1R-positive cells, endocannabinoid ligands induced resistin expression via the p38-Sp1 pathway. In both mouse models, a high-fat diet increased the accumulation of endocannabinoid ligands in adipose tissue, which recruited the CB1R-positive cells that secrete resistin, leading to adipose tissue inflammation and insulin resistance. This phenomenon was suppressed by CB1R blockade or in resistin knockout mice. Interestingly, this process was accompanied by mitochondrial change that was induced by resistin treatment. These results provide important insights into the ECS-resistin axis, leading to the development of metabolic diseases. Therefore, the regulation of resistin via the CB1R could be a potential therapeutic strategy for cardiometabolic diseases.

Multi-modality risk prediction of cardiovascular diseases for breast cancer cohort in the All of Us Research Program.

OBJECTIVE: This study leverages the rich diversity of the All of Us Research Program (All of Us)'s dataset to devise a predictive model for cardiovascular disease (CVD) in breast cancer (BC) survivors. Central to this endeavor is the creation of a robust data integration pipeline that synthesizes electronic health records (EHRs), patient surveys, and genomic data, while upholding fairness across demographic variables. MATERIALS AND METHODS: We have developed a universal data wrangling pipeline to process and merge heterogeneous data sources of the All of Us dataset, address missingness and variance in data, and align disparate data modalities into a coherent framework for analysis. Utilizing a composite feature set including EHR, lifestyle, and social determinants of health (SDoH) data, we then employed Adaptive Lasso and Random Forest regression models to predict 6 CVD outcomes. The models were evaluated using the c-index and time-dependent Area Under the Receiver Operating Characteristic Curve over a 10-year period. RESULTS: The Adaptive Lasso model showed consistent performance across most CVD outcomes, while the Random Forest model excelled particularly in predicting outcomes like transient ischemic attack when incorporating the full multi-model feature set. Feature importance analysis revealed age and previous coronary events as dominant predictors across CVD outcomes, with SDoH clustering labels highlighting the nuanced impact of social factors. DISCUSSION: The development of both Cox-based predictive model and Random Forest Regression model represents the extensive application of the All of Us, in integrating EHR and patient surveys to enhance precision medicine. And the inclusion of SDoH clustering labels revealed the significant impact of sociobehavioral factors on patient outcomes, emphasizing the importance of comprehensive health determinants in predictive models. Despite these advancements, limitations include the exclusion of genetic data, broad categorization of CVD conditions, and the need for fairness analyses to ensure equitable model performance across diverse populations. Future work should refine clinical and social variable measurements, incorporate advanced imputation techniques, and explore additional predictive algorithms to enhance model precision and fairness. CONCLUSION: This study demonstrates the liability of the All of Us's diverse dataset in developing a multi-modality predictive model for CVD in BC survivors risk stratification in oncological survivorship. The data integration pipeline and subsequent predictive models establish a methodological foundation for future research into personalized healthcare.

Two-dimensional and high-order directional information modulations for secure communications based on programmable metasurface.

Conventional wireless communication schemes indiscriminately transmit information into the whole space and pose inherent security risks. Recently, directional information modulation (DIM) has attracted enormous attention as a promising technology. DIM generates correct constellation symbols in the desired directions and distorts them in undesired directions, thus ensuring the security of the transmitted information. Although several DIM schemes have been reported, they suffer from defects of bulkiness, energy consumption, high cost, and inability to support two-dimensional (2D) and high-order modulations. Here, we propose a DIM scheme based on a 2-bit programmable metasurface (PM) that overcomes these defects. A fast and efficient discrete optimization algorithm is developed to optimize the digital coding sequences, and the correct constellation symbols can be generated and transmitted in multi-directional beams. As a proof-of-concept, three sets of constellation diagrams (8 phase shift keying (PSK), 16 quadrature amplitude modulation (QAM), and 64QAM) are realized in the multi-channel modes. This work provides an important route of employing DIM for ensuring physical-layer security and serves as a stepping stone toward endogenous secure communications.

A Soft-Fiber Bioelectronic Device with Axon-Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities.

Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long-standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high-quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium-sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network-in-liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300 kPa), low specific impedance (579 kΩ µm2), and high electrical conductivity (32 700 S m-1) - ≈1-3 times higher than hydrogels. Stable single-unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

Correlation between lipoprotein(a) and recurrent ischemic events post-cerebral vascular stent implantation.

BACKGROUND AND AIM: The association of Lipoprotein(a) (Lp[a]) with recurrent ischemic events in stented patients remains uncertain. So, this research aimed to investigate the impact of elevated Lp(a) levels on the occurrence of ischemic events in this specific patient population. METHODS: Totally 553 patients who underwent intracranial or extracranial artery stent implantation were included. Baseline data were collected and postoperative ischemic outcomes were followed up. Cox regression analysis was used to investigate the association between Lp(a) and outcomes, while accounting for confounding factors. Finally, we established prediction models based on nomogram. RESULTS: Of total 553 patients, a number of 107 (19.3%) experienced outcomes. These included 46 cases (34.7%) in group with elevated Lp(a) levels (>30 mg/dL) and 61 cases (18.4%) in non-elevated group (χ2=6.343, p=0.012). The group with elevated Lp(a) was 1.811 times more likely to experience ischemic events than the non-elevated group, each 1 mg/dL increase in Lp(a) resulted in a 1.008-fold increase in the recurrence rate of ischemic events. In addition, sex (male), previous history of coronary heart disease, decreased albumin, elevated very low density lipoprotein cholesterol and poorly controlled risk factors (including blood pressure and blood sugar) were also associated with a high risk of recurrent ischemic events after stent implantation. CONCLUSION: Lp(a) elevation was a significant risk factor for ischemic events in symptomatic patients who underwent intracranial or extracranial artery stenting.

Long-term outcomes of high bleeding risk patients undergoing percutaneous coronary intervention: a Korean nationwide registry.

BACKGROUND AND AIMS: Patients with high bleeding risk (HBR) undergoing percutaneous coronary intervention (PCI) are at increased risk of not only bleeding, but also ischaemic events. This study aimed to determine the long-term relative risk of ischaemic and bleeding events in HBR patients. METHODS: This study was a nationwide cohort study, based on the Korean National Health Insurance Review and Assessment Service database. Patients diagnosed with stable angina or acute coronary syndrome and those who underwent PCI in Korea between 2009 and 2018 were included in the analysis. According to the Academic Research Consortium HBR criteria, the total population was divided into HBR and non-HBR groups. The co-primary outcomes were major bleeding events and ischaemic (composite of cardiac death, myocardial infarction, and ischaemic stroke) events. RESULTS: Among a total of 325 417 patients who underwent PCI, 66 426 patients (20.4%) had HBR. During the follow-up period, HBR patients had a higher risk for major bleeding events (23.9% vs. 8.9%, P < .001) and ischaemic events (33.8% vs. 14.4%, P < .001). However, the impact of HBR was significant for major bleeding events [hazard ratio (HR) 3.12, 95% confidence interval (CI) 3.04-3.21, P < .001] and for ischaemic events (HR 2.50, 95% CI 2.45-2.56, P < .001). The HBR group was also associated with a greater risk of all-cause mortality (HR 3.73, 95% CI 3.66-3.79, P < .001). The average annual rate of major bleeding events within the first year after PCI was 5.5% for a single major criterion, and 2.9% for a single minor criterion. CONCLUSIONS: Among patients undergoing PCI, those with HBR were at increased long-term risk for both bleeding and ischaemic events, with a greater risk of mortality compared to non-HBR patients.

Paeonol alleviates ox-LDL-induced endothelial cell injury by targeting the heme oxygenase-1/phosphoinositide 3-kinase/protein kinase B pathway.

Atherosclerosis is a leading cause of vascular disease worldwide. Paeonol has been reported to have therapeutical potential in atherosclerosis. The aim of this study is to explore the effect of paeonol on oxidized low-density lipoprotein (ox-LDL)-induced endothelial cells injury and the underlying mechanism. Human umbilical vein endothelial cells (HUVECs) were treated with ox-LDL (100 µg/ml) to mimic atherosclerosis in vitro. The cell viability, proliferation, and apoptosis were assessed by cell counting kit-8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU), and flow cytometry, respectively. The angiogenesis was detected by tube formation assay. The levels of inflammatory factor were measured by enzyme-linked immunosorbent assay (ELISA). In addition, the levels of Fe2+, reactive oxygen species (ROS), and glutathione (GSH) were detected to assess ferroptosis. The western blot was used to detect the protein expression. Ox-LDL inhibited cell viability, proliferation, and angiogenesis, but induced apoptosis and inflammation in HUVECs, and paeonol (75 µM) relieves ox-LDL-induced HUVEC injury. Also, paeonol inhibited ox-LDL-induced ferroptosis of HUVECs. Interestingly, heme oxygenase-1 (HMOX1) knockdown alleviated ox-LDL-induced HUVECs injury and ferroptosis. Paeonol affected ox-LDL-induced HUVECs via regulating HMOX1. In addition, paeonol regulated PI3K/AKT pathway via HMOX1, and the inhibitor of phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) pathway reversed the effects of HMOX1 knockdown on ox-LDL-induced HUVECs. Paeonol alleviated ox-LDL-induced HUVEC injury by regulating the PI3K/AKT pathway via targeting HMOX1.

Study on the Determination of Flavor Value of Rice Based on Grid Iterative Search Swarm Optimization Support Vector Machine Model and Hyperspectral Imaging.

In the field of rice processing and cultivation, it is crucial to adopt efficient, rapid and user-friendly techniques to detect the flavor values of various rice varieties. The conventional methods for flavor value assessment mainly rely on chemical analysis and technical evaluation, which not only deplete the rice resources but also incur significant time and labor costs. In this study, hyperspectral imaging technology was utilized in combination with an improved Particle Swarm Optimization Support Vector Machine (PSO-SVM) algorithm, i.e., the Grid Iterative Search Particle Swarm Optimization Support Vector Machine (GISPSO-SVM) algorithm, introducing a new non-destructive technique to determine the flavor value of rice. The method captures the hyperspectral feature data of different rice varieties through image acquisition, preprocessing and feature extraction, and then uses these features to train a model using an optimized machine learning algorithm. The results show that the introduction of GIS algorithms in a PSO-optimized SVM is very effective and can improve the parameter finding ability. In terms of flavor value prediction accuracy, the Principal Component Analysis (PCA) combined with the GISPSO-SVM algorithm achieved 96% accuracy, which was higher than the 93% of the Competitive Adaptive Weighted Sampling (CARS) algorithm. And the introduction of the GIS algorithm in different feature selection can improve the accuracy to different degrees. This novel approach helps to evaluate the flavor values of new rice varieties non-destructively and provides a new perspective for future rice flavor value detection methods.

Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by various compositional features. This study aimed to develop an artificial intelligence-driven multiomics predictive model for AAA subtypes to identify heterogeneous immune cell infiltration and predict disease progression. Additionally, we investigated neutrophil heterogeneity in patients with different AAA subtypes to elucidate the relationship between the immune microenvironment and AAA pathogenesis. METHODS: This study enrolled 517 patients with AAA, who were clustered using k-means algorithm to identify AAA subtypes and stratify the risk. We utilized residual convolutional neural network 200 to annotate and extract contrast-enhanced computed tomography angiography images of AAA. A precise predictive model for AAA subtypes was established using clinical, imaging, and immunological data. We performed a comparative analysis of neutrophil levels in the different subgroups and immune cell infiltration analysis to explore the associations between neutrophil levels and AAA. Quantitative polymerase chain reaction, Western blotting, and enzyme-linked immunosorbent assay were performed to elucidate the interplay between CXCL1, neutrophil activation, and the nuclear factor (NF)-κB pathway in AAA pathogenesis. Furthermore, the effect of CXCL1 silencing with small interfering RNA was investigated. RESULTS: Two distinct AAA subtypes were identified, one clinically more severe and more likely to require surgical intervention. The CNN effectively detected AAA-associated lesion regions on computed tomography angiography, and the predictive model demonstrated excellent ability to discriminate between patients with the two identified AAA subtypes (area under the curve, 0.927). Neutrophil activation, AAA pathology, CXCL1 expression, and the NF-κB pathway were significantly correlated. CXCL1, NF-κB, IL-1ß, and IL-8 were upregulated in AAA. CXCL1 silencing downregulated NF-κB, interleukin-1ß, and interleukin-8. CONCLUSION: The predictive model for AAA subtypes demonstrated accurate and reliable risk stratification and clinical management. CXCL1 overexpression activated neutrophils through the NF-κB pathway, contributing to AAA development. This pathway may, therefore, be a therapeutic target in AAA.