Preoperative Quantitative Flow Ratio, Intraoperative Transit Time Flow Measurement Parameters, and Their Predictive Value for Short-Term Graft Failure After Coronary Artery Bypass Grafting.

BACKGROUND: Studies on the relationship between the preoperative quantitative flow ratio (QFR) and parameters of intraoperative transit time flow measurement (TTFM) are extremely rare. In addition, the predictive value of QFR and TTFM parameters for early internal mammary artery (IMA) failure after coronary artery bypass grafting still needs to be validated.Methods and Results: We retrospectively collected data from 510 patients who underwent in situ IMA grafting to the left anterior descending (LAD) artery at Fuwai Hospital. Spearman correlation coefficients between preoperative QFR of the LAD artery and intraoperative TTFM parameters of the IMA were -0.13 (P=0.004) for mean graft flow (Qm) and 0.14 (P=0.002) for the pulsatility index (PI). QFR and TTFM exhibited similar and good predictive value for early IMA failure (5.7% at 1 year), and they were better than percentage diameter stenosis (area under the curve 0.749 for QFR, 0.733 for Qm, 0.688 for PI, and 0.524 for percentage diameter stenosis). The optimal cut-off value of QFR was 0.765. Both univariate and multivariable regression analyses revealed that QFR >0.765, Qm ≤15 mL/min, and PI >3.0 independently contributed to early IMA failure. CONCLUSIONS: There were statistically significant correlations between preoperative QFR of the LAD artery and intraoperative TTFM parameters (Qm, PI) of the IMA. Preoperative QFR and intraoperative Qm and PI exhibited excellent predictive value for early IMA failure.

Novel Amphiphilic PROTAC with Enhanced Pharmacokinetic Properties for ALK Protein Degradation.

Advancements in anticancer strategies spotlight proteolysis targeting chimera (PROTAC) technology, yet it is hindered by poor water solubility and bioavailability. This study introduces a novel amphiphilic PROTAC, B1-PEG, synthesized through PEGylation of an optimized PROTAC molecule, B1, to enhance its properties. B1-PEG is engineered to self-organize into micelles in water and releases its active form in response to the tumor-specific high GSH environment. Comparative pharmacokinetic analysis revealed B1-PEG's superior bioavailability at 84.8%, outperforming the unmodified PROTAC molecule B1. When tested in a H3122 xenograft mouse model, B1-PEG significantly regressed tumors, underscoring its potential as a formidable candidate in targeted cancer therapy. Our findings offer a promising direction for overcoming bioavailability limitations in PROTAC drug design.

Electron transferring with oxygen defects on Ni-promoted Pd/Al2O3 catalysts for low-temperature lean methane combustion.

Methane (CH4) is the second most consequential greenhouse gas after CO2, with a substantial global warming potential. The CH4 catalytic combustion offers an efficient method for the elimination of CH4. However, improving the catalytic performance of Pd-based materials for low-temperature CH4 combustion remains a big challenge. In this study, we synthesized an enhanced Pd/5NiAlOx catalyst that demonstrated superior catalytic activity and improved water resistance compared to the Pd/Al2O3 catalyst. Specifically, the T90 was decreased by over 100 °C under both dry and wet conditions. Introducing Ni resulted in an enormously enhanced number of oxygen defects on the obtained 5NiAlOx support. This defect-rich support facilitates the anchoring of PdO through increased electron transfer, thereby inhibiting the production of high-valence Pd(2+δ)+ and stimulating the generation of unsaturated Pd sites. Pd0 can effectively activate surface oxygen and PdO plays a significant role in activating CH4, resulting in high activity for Pd/5NiAlOx. On the other hand, the increased water resistance of Pd/5NiAlOx was mainly due to the generation of *OOH species and the lower accumulation of surface -OH species during the reaction process.

Discovery of a Promising CBP/p300 Degrader XYD129 for the Treatment of Acute Myeloid Leukemia.

The epigenetic target CREB (cyclic-AMP responsive element binding protein) binding protein (CBP) and its homologue p300 were promising therapeutic targets for the treatment of acute myeloid leukemia (AML). Herein, we report the design, synthesis, and evaluation of a class of CBP/p300 PROTAC degraders based on our previously reported highly potent and selective CBP/p300 inhibitor 5. Among the compounds synthesized, 11c (XYD129) demonstrated high potency and formed a ternary complex between CBP/p300 and CRBN (AlphaScreen). The compound effectively degraded CBP/p300 proteins and exhibited greater inhibition of growth in acute leukemia cell lines compared to its parent compound 5. Furthermore, 11c demonstrated significant inhibition of tumor growth in a MOLM-16 xenograft model (TGI = 60%) at tolerated dose schedules. Our findings suggest that 11c is a promising lead compound for the treatment of AML.

Comparative analysis of corneal parameters in simple myopic anisometropia using Scheimpflug technology.

Purpose: This study aims to investigate the differences in binocular corneal parameters and their interrelation with binocular biometric parameters asymmetry in patients with simple myopic anisometropia, thereby elucidating the influence of myopia process on various corneal parameters. Methods: In this cross-sectional study, 65 patients with anisometropia in monocular myopia were included. They were divided into low anisometropia group: 3.00D<Δ spherical equivalent (SE)≤-1.00D (Δ represents the difference between the two eyes, i.e., myopic data minus emmetropic data) and high anisometropia group: ΔSE ≤ -3.00D. Corneal and ocular biometric parameters were measured using Pentacam, Corvis ST, and IOL Master 700. Statistical analyses focused on the binocular corneal parameters asymmetry, using the contralateral emmetropia as a control. Results: The mean age of participants was 18.5 ± 1.3 years, with the average SE for myopia and emmetropia being -2.93 ± 1.09D and -0.16 ± 0.41D, respectively. The central corneal thickness (CCT), flat keratometry (Kf), keratometry astigmatism (Ka), total corneal aberration (6 mm) (TOA), surface variance index (ISV), vertical asymmetry index (IVA), stress-strain index (SSI), and first applanation stiffness parameter (SPA1) and ambrosia relational thickness-horizontal (ARTh) showed significant differences between anisometropic fellow eyes (p < 0.05). There were significant differences in ΔIVA, Δ the difference between the mean refractive power of the inferior and superior corneas (I-S), Δ deviation value of Belin/Ambrósio enhanced ectasia display (BAD-D), Δ deformation amplitude ratio max (2 mm) (DAR)and Δ tomographic biomechanical index (TBI) (p < 0.05) in two groups. Asymmetry of corneal parameters was correlated with asymmetry of ocular biometric parameters. Anisometropia (ΔSE) was positively correlated with ΔIVA (r = 0.255, p = 0.040), ΔBAD-D (r = 0.360, p = 0.006), and ΔSSI (r = 0.276, p = 0.039) and negatively correlated with ΔDAR (r = -0.329, p = 0.013) in multiple regression analysis. Δ mean keratometry (Km), Δ anterior chamber depth (ACD), and Δ biomechanically corrected intraocular pressure (bIOP) were also associated with binocular corneal differences. Conclusion: Compared to contralateral emmetropia, myopic eyes have thinner corneas and smaller corneal astigmatism. Myopic corneas exhibit relatively more regular surface morphology but are more susceptible to deformation and possess marginally inferior biomechanical properties. In addition, there is a certain correlation between anisometropia and corneal parameter asymmetry, which would be instrumental in predicting the development of myopia.

Distinct time trends in colorectal cancer incidence in countries with SDI levels from 1990 to 2019: an age-period-cohort analysis for the Global Burden of Disease 2019 study.

Introduction: The burden of colorectal cancer (CRC) plays a pivotal role in the global cancer epidemic. Our study reported the incidence trends in CRC and the associated effects of age, period, and birth cohort in 204 countries and territories over the past 30 years. Methods: The incidence data of CRC were extracted from the Global Burden of Disease Study (GBD) 2019. We performed the age-period-cohort (APC) model to estimate the overall annual percentage change (net drift) in the incidence rate, the annual percentage change by age group (local drift), and the relative risk (period and cohort effects) of the period and cohort in CRC during 1990-2019. This approach allows examining and distinguishing age, period, and cohort effects in incidence and potentially distinguishing colorectal cancer gaps in prevention and screening. Results: In 2019, the incidence of CRC was 2.17 (95% UI 2.00-2.34) million, of which China, the United States of America, and Japan had the highest incidence population, accounting for 45.9% of the global population. The age-standardized incidence rate (ASIR) was 26.7 (95% UI 28.9-24.6) per 100,000 people, of which 30 countries had an incidence rate greater than 40.0 per 100,000 people. From 1990 to 2019, the middle SDI region had the largest increase in incidence rate, with a net drift of 2.33% (95% CI 2.2-2.46%, p < 0.001). Globally, the incidence population was concentrated in the age group of 50-69 years, and the age group of 30-34 years had the largest increase in incidence rate (local drift 1.19% (95% CI 1.01-1.37%)). At the same time, the sex and age distributions of CRC incidence had significant heterogeneity across regions and countries. In the past 30 years, the incidence rate in 31 countries has been well controlled (net drift <0), and most of them were concentrated in high-and high-middle-SDI regions, such as Australia, Czechia, and Belgium, and the relative risk of incidence generally improved over time and consecutive young birth cohorts. CRC incidence showed an unfavorable trend (net drift ≥1%) in 89 countries, of which 27 countries were more significant (net drift >2%), mostly concentrated in the middle SDI region, such as China, Mexico, and Brazil, and the risk of period and birth cohort was unfavorable. Conclusion: Globally, the incidence of CRC has shown an overall upward trend over the past 30 years, with the exception of some countries with higher SDI values. Significant age-period-cohort differences were observed in the risk of incidence in CRC worldwide. Effective prevention and control policies need to take into account the age-period-cohort effect characteristics of different regions.

Three exonic variants in the PHEX gene cause aberrant splicing in a minigene assay.

Background: X-linked hypophosphatemia (XLH, OMIM 307800) is a rare phosphorus metabolism disorder caused by PHEX gene variants. Many variants simply classified as missense or nonsense variants were only analyzed at the DNA level. However, growing evidence indicates that some of these variants may alter pre-mRNA splicing, causing diseases. Therefore, this study aimed to use bioinformatics tools and a minigene assay to ascertain the effects of PHEX variations on pre-mRNA splicing. Methods: We analyzed 174 variants in the PHEX gene described as missense or nonsense variants. Finally, we selected eight candidate variants using bioinformatics tools to evaluate their effects on pre-mRNA splicing using a minigene assay system. The complementary DNA (cDNA) sequence for the PHEX gene (RefSeq NM_000444.6) serves as the basis for DNA variant numbering. Results: Of the eight candidate variants, three were found to cause abnormal splicing. Variants c.617T>G p.(Leu206Trp) and c.621T>A p.(Tyr207*) in exon 5 altered the splicing of pre-mRNA, owing to the activation of a cryptic splice site in exon 5, which produced an aberrant transcript lacking a part of exon 5, whereas variant c.1700G>C p.(Arg567Pro) in exon 16 led to the activation of a cryptic splice site in intron 16, resulting in a partial inclusion of intron 16. Conclusion: Our study employed a minigene system, which has a great degree of flexibility to assess abnormal splicing patterns under the circumstances of patient mRNA samples that are not available, to explore the impact of the exonic variants on pre-mRNA splicing. Based on the aforementioned experimental findings, we demonstrated the importance of analyzing exonic variants at the mRNA level.

A CD36-dependent non-canonical lipid metabolism program promotes immune escape and resistance to hypomethylating agent therapy in AML.

Environmental lipids are essential for fueling tumor energetics, but whether these exogenous lipids transported into cancer cells facilitate immune escape remains unclear. Here, we find that CD36, a transporter for exogenous lipids, promotes acute myeloid leukemia (AML) immune evasion. We show that, separately from its established role in lipid oxidation, CD36 on AML cells senses oxidized low-density lipoprotein (OxLDL) to prime the TLR4-LYN-MYD88-nuclear factor κB (NF-κB) pathway, and exogenous palmitate transfer via CD36 further potentiates this innate immune pathway by supporting ZDHHC6-mediated MYD88 palmitoylation. Subsequently, NF-κB drives the expression of immunosuppressive genes that inhibit anti-tumor T cell responses. Notably, high-fat-diet or hypomethylating agent decitabine treatment boosts the immunosuppressive potential of AML cells by hijacking CD36-dependent innate immune signaling, leading to a dampened therapeutic effect. This work is of translational interest because lipid restriction by US Food and Drug Administration (FDA)-approved lipid-lowering statin drugs improves the efficacy of decitabine therapy by weakening leukemic CD36-mediated immunosuppression.

Inhibiting mitochondrial citrate shuttling induces hepatic triglyceride deposition in Nile tilapia (Oreochromis niloticus) through lipid anabolic remodeling.

The solute carrier family 25 member 1 (Slc25a1)-dependent mitochondrial citrate shuttle is responsible for exporting citrate from the mitochondria to the cytoplasm for supporting lipid biosynthesis and protein acetylation. Previous studies on Slc25a1 concentrated on pathological models. However, the importance of Slc25a1 in maintaining metabolic homeostasis under normal nutritional conditions remains poorly understood. Here, we investigated the mechanism of mitochondrial citrate shuttle in maintaining lipid metabolism homeostasis in male Nile tilapia (Oreochromis niloticus). To achieve the objective, we blocked the mitochondrial citrate shuttle by inhibiting Slc25a1 under normal nutritional conditions. Slc25a1 inhibition was established by feeding Nile tilapia with 250 mg/kg 1,2,3-benzenetricarboxylic acid hydrate for six weeks or intraperitoneal injecting them with dsRNA to knockdown slc25a1b for seven days. The Nile tilapia with Slc25a1 inhibition exhibited an obesity-like phenotype accompanied by fat deposition, liver damage and hyperglycemia. Moreover, Slc25a1 inhibition decreased hepatic citrate-derived acetyl-CoA, but increased hepatic triglyceride levels. Furthermore, Slc25a1 inhibition replenished cytoplasmic acetyl-CoA through enhanced acetate pathway, which led to hepatic triglycerides accumulation. However, acetate-derived acetyl-CoA caused by hepatic Slc25a1 inhibition did not activate de novo lipogenesis, but rather modified protein acetylation. In addition, hepatic Slc25a1 inhibition enhanced fatty acids esterification through acetate-derived acetyl-CoA, which increased Lipin1 acetylation and its protein stability. Collectively, our results illustrate that inhibiting mitochondrial citrate shuttle triggers lipid anabolic remodeling and results in lipid accumulation, indicating the importance of mitochondrial citrate shuttle in maintaining lipid metabolism homeostasis.

[Construction and validation of a predictive model for early occurrence of lower extremity deep venous thrombosis in ICU patients with sepsis].

OBJECTIVE: To investigate the risk factors of lower extremity deep venous thrombosis (LEDVT) in patients with sepsis during hospitalization in intensive care unit (ICU), and to construct a nomogram prediction model of LEDVT in sepsis patients in the ICU based on the critical care scores combined with inflammatory markers, and to validate its effectiveness in early prediction. METHODS: 726 sepsis patients admitted to the ICU of the Affiliated Hospital of Jining Medical University from January 2015 to December 2021 were retrospectively included as the training set to construct the prediction model. In addition, 213 sepsis patients admitted to the ICU of the Affiliated Hospital of Jining Medical University from January 2022 to June 2023 were retrospectively included as the validation set to verify the performance of the prediction model. Clinical data of patients were collected, such as demographic information, vital signs at the time of admission to the ICU, underlying diseases, past history, various types of scores within 24 hours of admission to the ICU, the first laboratory indexes of admission to the ICU, lower extremity venous ultrasound results, treatment, and prognostic indexes. Lasso regression analysis was used to screen the influencing factors for the occurrence of LEDVT in sepsis patients, and the results of Logistic regression analysis were synthesized to construct a nomogram model. The nomogram model was evaluated by receiver operator characteristic curve (ROC curve), calibration curve, clinical impact curve (CIC) and decision curve analysis (DCA). RESULTS: The incidence of LEDVT after ICU admission was 21.5% (156/726) in the training set of sepsis patients and 21.6% (46/213) in the validation set of sepsis patients. The baseline data of patients in both training and validation sets were comparable. Lasso regression analysis showed that seven independent variables were screened from 67 parameters to be associated with the occurrence of LEDVT in patients with sepsis. Logistic regression analysis showed that the age [odds ratio (OR) = 1.03, 95% confidence interval (95%CI) was 1.01 to 1.04, P < 0.001], body mass index (BMI: OR = 1.05, 95%CI was 1.01 to 1.09, P = 0.009), venous thromboembolism (VTE) score (OR = 1.20, 95%CI was 1.11 to 1.29, P < 0.001), activated partial thromboplastin time (APTT: OR = 0.98, 95%CI was 0.97 to 0.99, P = 0.009), D-dimer (OR = 1.03, 95%CI was 1.01 to 1.04, P < 0.001), skin or soft-tissue infection (OR = 2.53, 95%CI was 1.29 to 4.98, P = 0.007), and femoral venous cannulation (OR = 3.72, 95%CI was 2.50 to 5.54, P < 0.001) were the independent influences on the occurrence of LEDVT in patients with sepsis. The nomogram model was constructed by combining the above variables, and the ROC curve analysis showed that the area under the curve (AUC) of the nomogram model for predicting the occurrence of LEDVT in patients with sepsis was 0.793 (95%CI was 0.746 to 0.841), and the AUC in the validation set was 0.844 (95%CI was 0.786 to 0.901). The calibration curve showed that its predicted probability was in good agreement with the actual probabilities were in good agreement, and both CIC and DCA curves suggested a favorable net clinical benefit. CONCLUSIONS: The nomogram model based on the critical illness scores combined with inflammatory markers can be used for early prediction of LEDVT in ICU sepsis patients, which helps clinicians to identify the risk factors for LEDVT in sepsis patients earlier, so as to achieve early treatment.

Essential oils with anti-breast cancer activities from Aralia chinensis L. (roots, stems, and leaves) via gas chromatography-mass spectrometry analyses and molecular docking.

Aralia chinensis L. is a traditional Miao ethnic medicine known for its pain and inflammation relief and its ability to dispel wind and dampness. This study aimed to assess its antitumour activity and identify the chemical constituents of A. chinensis essential oils. Gas chromatography-mass spectrometry was used to analyse the volatile oil composition, which identified 35, 35, and 24 constituents in essential oils from roots, stems, and leaves, respectively. Network pharmacology predicted the possible key targets of common components in breast-cancer treatment, which revealed AKT1, SRC, EGFR, STAT3, and MAPK3 as high-priority targets with high active-constituent affinity. CCK-8 assay confirmed the inhibitory effect of the essential oils on MCF-7 breast-cancer cells, with oils from Aralia rhizomes, stems, and leaves inhibiting cell viability by 77%, 64%, and 62%, respectively. The active components of Aralia essential oils show promise for breast-cancer treatment by targeting AKT1, SRC, EGFR, and other key factors.

Precise Molecular Subtyping Reveals Heterogeneity of Lung Adenocarcinoma Based on DNA Methylation.

BACKGROUND: Due to the high heterogeneity of lung adenocarcinoma (LUAD), which restricts the effectiveness of therapy, precise molecular subgrouping of LUAD is of great significance. Clinical research has demonstrated the significant potential of DNA methylation as a classification indicator for human malignancies. METHODS: WGML framework (which was developed based on weighted gene correlation network analysis (WGCNA), Gene Ontology (GO), and machine learning) was developed to precisely subgroup molecular subtypes of LUAD. This framework included two parts: the WG algorithm and the machine learning part. The WG algorithm part was an original algorithm used to obtain a crucial module, which was characterized by weighted correlation network analysis, functional annotation, and mathematical algorithms. The machine learning part utilized the Boruta algorithm, random forest algorithm, and Gradient Boosting Regression Tree algorithm to select feature genes. Then, based on the results of the WGML framework, subtypes were computed by the hierarchical clustering algorithm. A series of analyses, including dimensionality reduction methods, survival analysis, clinical stage analysis, immune infiltration analysis, tumor environment analysis, immune checkpoints analysis, TIDE analysis, CYT analysis, somatic mutation analysis, and drug sensitivity analysis, were utilized to demonstrate the effectiveness of subgrouping. GEO datasets were used to externally validate the results. Meanwhile, another subgrouping method of LUAD from another study was employed to compare with the WGML framework. RESULT: By importing DNA methylation data into the WGML framework, nine genes were obtained to further subgroup LUAD. Three subtypes, the Carcinogenesis subtype, Immune-infiltration subtype, and Chemoresistance subtype, were identified. The dimensionality reduction method exhibited great distinctness between subtypes. A series of analyses were employed to exhibit the difference among the three subtypes and to demonstrate the accuracy of the definition of subtypes. Besides, the WGML framework was compared with a LUAD subgrouping method from another research, which demonstrated that WGML had better efficiency for subgrouping LUAD. CONCLUSION: This study provides a novel LUAD subgrouping framework named WGML for the accurate subgrouping of lung adenocarcinoma.

Folic acid supplementation for stroke prevention: A systematic review and meta-analysis of 21 randomized clinical trials worldwide.

BACKGROUND & AIMS: The AHA/ASA guidelines for primary stroke prevention are almost a decade old. The current recommendation regarding folic acid supplementation is based on only 8 clinical trials, and an additional 13 folate trials have been published since then. This meta-analysis aims to fill in critical evidence gaps by comprehensively evaluating 21 published trials with particular attention given to identifying the true influences through stratification. METHODS: PubMed, the Cochrane Central Register of Controlled Trials, and Embase were searched from inception to April 4, 2023. This study included all randomized controlled trials (RCTs) of folic acid with stroke as one of the reporting endpoints. Relative risks and 95% confidence intervals were used to assess the association between folic acid supplementation and the risk of stroke in a random-effects model. RESULTS: Results from the 21 pooled RCTs totaling 115,559 participants showed that folic acid supplementation significantly reduced the risk of stroke by 10% (RR 0.90, 95%CI 0.83 to 0.98). Subgroup analyses showed that folic acid efficacy was greater in areas without fortified grain or with partially-fortified grain (RR = 0.83, 95% CI 0.75 to 0.93; RR = 1.04 in areas with grain fortification, P-interaction = 0.003). In this group, folic acid supplementation was most efficacious in those without a history of stroke or myocardial infarction (RR = 0.77, 95% CI 0.68 to 0.86; RR = 0.94 for participants with a history of stroke or myocardial infarction, P-interaction = 0.008). The efficacy of folic acid remained consistent regardless of baseline folate levels, folic acid dosage, baseline vitamin B12 levels, vitamin B12 dosage, homocysteine reduction, intervention duration, and whether folic acid was taken alone or in combination (all P-interaction>0.05). All 21 trials were free of attrition bias and reporting bias, and there was no significant publication bias. CONCLUSIONS: This is by far the largest meta-analysis of RCTs regarding folic acid supplementation and stroke, demonstrating the overall benefit of folic acid for stroke prevention. Grain fortification and history of stroke or myocardial infarction may be the most important influences on the efficacy of folic acid for stroke prevention.

Trained immunity: A link between risk factors and cardiovascular disease.

Cardiovascular diseases are significant contributors to human mortality, closely associated with inflammation. With the changing living conditions and the extension of human lifespan, greater attention has been directed towards understanding the impact of early, long-term events on the development of cardiovascular events. Lifestyle factors such as stress, unhealthy diet and physical inactivity can increase the risk of cardiovascular diseases. Interestingly, even if the risk factors are addressed later, their influence may persist. Recently, the concept of trained innate immunity (TRIM), defined as sustained alterations in the function of innate immunocyte that promote a more robust response to downstream stimuli, has been proposed to be involved in cardiovascular diseases. It is hypothesized that TRIM may serve as a mediator bridging the impacts of aforementioned risk factors. This review aims to elucidate the role of TRIM in cardiovascular diseases and highlight its significance in uncovering new mechanisms and therapeutic targets.

Exploring the relationship between hemodynamics and the immune microenvironment in carotid atherosclerosis: Insights from CFD and CyTOF technologies.

Carotid atherosclerosis is a major cause of stroke. Hemodynamic forces, such as shear stress and oscillatory shear, play an important role in the initiation and progression of atherosclerosis. The alteration of the immune microenvironment is the fundamental pathological mechanism by which diverse external environmental factors impact the formation and progression of plaques. However, Current research on the relationship between hemodynamics and immunity in atherosclerosis still lack of comprehensive understanding. In this study, we combined computational fluid dynamics (CFD) and Mass cytometry (CyTOF) technologies to explore the changes in the immune microenvironment within plaques under different hemodynamic conditions. Our results indicated that neutrophils were enriched in adverse flow environments. M2-like CD163+CD86+ macrophages were predominantly enriched in high WSS and low OSI environments, while CD163-CD14+ macrophages were enriched in low WSS and high OSI environments. Functional analysis further revealed T cell pro-inflammatory activation and dysregulation in modulation, along with an imbalance in M1-like/M2-like macrophages, suggesting their potential involvement in the progression of atherosclerotic lesions mediated by adverse flow patterns. Our study elucidated the potential mechanisms by which hemodynamics regulated the immune microenvironment within plaques, providing intervention targets for future precision therapies.

Research on the generation and annotation method of thin section images of tight oil reservoir based on deep learning.

The cast thin sections of tight oil reservoirs contain important parameters such as rock mineral composition and content, porosity, permeability and stratigraphic characteristics, which are of great significance for reservoir evaluation. The use of deep learning technology for intelligent identification of thin section images is a development trend of mineral identification. However, the difficulty of making cast thin sections, the complexity of the making process and the high cost of thin section annotation have led to a lack of cast thin section images, which cannot meet the training requirements of deep learning image recognition models. In order to increase the sample size and improve the training effect of deep learning model, we proposed a generation and annotation method of thin section images of tight oil reservoir based on deep learning, by taking Fuyu reservoir in Sanzhao Sag as the target area. Firstly, the Augmentor strategy space was used to preliminarily augment the original images while preserving the original image features to meet the requirements of the model. Secondly, the category attention mechanism was added to the original StyleGAN network to avoid the influence of the uneven number of components in thin sections on the quality of the generated images. Then, the SALM annotation module was designed to achieve semi-automatic annotation of the generated images. Finally, experiments on image sharpness, distortion, standard accuracy and annotation efficiency were designed to verify the advantages of the method in image quality and annotation efficiency.

Recent research progress of selenotungstate-based biomolecular sensing materials.

Polyoxometalates (POMs) have drawn significant attention on account of their structural designability, compositional diversity and great potential applications. As an indispensable branch of POMs, selenotungstates (SeTs) have been synthesized extensively. Some SeTs have been applied as sensing materials for detecting biomarkers (e.g., metabolites, hormones, cancer markers). To gain a comprehensive understanding of advancements in SeT-based sensing materials, we present an overview that encapsulates the sensing performances and mechanisms of SeT-based biosensors. SeT-based biosensors are categorized into electrochemical catalytic biosensors, electrochemical affinity biosensors, "turn-off" fluorescence biosensors and "turn-on" fluorescence biosensors. We anticipate the expansive potential of SeT-based biosensors in wearable and implantable sensing technologies, which promises to catalyze significant breakthroughs in SeT-based biosensors.

Numerical prediction model for long- and short-term concentration of indoor volatile organic compounds from building materials.

Emission models of volatile organic compounds (VOCs) from individual indoor building materials have been developed and validated. However, multiple indoor building materials release VOCs simultaneously, and neither single building material nor multiple building material emission models can predict the entire release cycle of VOCs accurately. This study established a long- and short-term numerical prediction model for indoor VOC concentration. The model includes an attenuation coefficient θ. To describe the decay rate of the total VOC content, which is mainly influenced by time, and by designing experiments and testing in environmental warehouses under different seasonal conditions, the value of θ was first obtained. Then, after successfully plotting the emission curve of indoor pollutant concentration over time through numerical solution and using θ, the VOC content was corrected for various seasonal conditions. On the basis of this model, an exposure dose integration algorithm was proposed to evaluate the environmental health risks, as an application of this model. In comparison with previous research results and experimental data, this model has better predictive performance.