Detecting the therapeutic drugs in blood samples through PDMS-printed paper spray mass spectrometry.

In this paper, paper microfluidic channel fabricated by directly screen-printing of polydimethylsiloxane (PDMS) is proposed for paper spray mass spectrometry analysis of therapeutic drugs in the blood samples. Compared with traditional paper spray, PDMS-printed paper spray (PP-PS) allows fluid to flow to the tip of paper with less sample loss which significantly improved the signal intensity of target compounds in blood samples. As paper can reduce the matrix effect, PP-PS also has a greater advantage than electro-spray Ionization (ESI) when directly analyzing complex biological sample in terms of the detection efficiency. Linearity and limits of detection (LOD) were evaluated for five psychotropic drugs: olanzapine, quetiapine, 9-hydroxyrisperidone, clozapine, risperidone. As a result, PP-PS improved the signal intensity of the psychotropic drugs at a concentration of 250 ng/ml in blood samples by a factor of 2-5 times and lowered the relative standard deviation (RSD) by a factor of 2-5.6 times compared with traditional paper spray. And PP-PS also improved signal intensity by a factor of 9-33 times compared with ESI. Quantitative experiments of PP-PS mass spectrometry indicated that the linear range was 5-500 ng/ml and the LOD were improved by a factor of 5-71 times for all these drugs compared with traditional paper spray. In addition, PP-PS was applied to the home-made miniaturized mass spectrometer and the precursor ions of all five psychotropic drugs (250 ng/ml) in the mass spectrometry results were obtained as well. These could prove that PP-PS has the potential to analyze complex biological samples in application on the miniaturized mass spectrometer which can be used outside the laboratory.

Silk Sericin and Its Composite Materials with Antibacterial Properties to Enhance Wound Healing: A Review.

Wound infections may disrupt the normal wound-healing process. Large amounts of antibiotics are frequently used to prevent pathogenic infections; however, this can lead to resistance development. Biomaterials possessing antimicrobial properties have promising applications for reducing antibiotic usage and promoting wound healing. Silk sericin (SS) has been increasingly explored for skin wound healing applications owing to its excellent biocompatibility and antioxidant, antimicrobial, and ultraviolet-resistant properties. In recent years, SS-based composite biomaterials with a broader antimicrobial spectrum have been extensively investigated and demonstrated favorable efficacy in promoting wound healing. This review summarizes various antimicrobial agents, including metal nanoparticles, natural extracts, and antibiotics, that have been incorporated into SS composites for wound healing and elucidates their mechanisms of action. It has been revealed that SS-based biomaterials can achieve sustained antimicrobial activity by slow-release-loaded antimicrobial agents. The antimicrobial-loaded SS composites may promote wound healing through anti-infection, anti-inflammation, hemostasis, angiogenesis, and collagen deposition. The manufacturing methods, benefits, and limitations of antimicrobial-loaded SS materials are briefly discussed. This review aims to enhance the understanding of new advances and directions in SS-based antimicrobial composites and guide future biomedical research.

Cascading social-ecological benefits of biodiversity for agriculture.

Cultivated species diversity can provide numerous benefits to agricultural systems. Many ecological theories have been proposed to understand the relationships between plant species diversity and trophic interactions. However, extending such theories to socioeconomic systems has been rare for agriculture. Here, we establish ten hypotheses (e.g., the natural enemy hypothesis, resource concentration hypothesis, insurance hypothesis, and aggregation hypothesis) about the relationships between cultivated species diversity (i.e., crop diversification, co-cultures of crops and domestic animals, and co-cultures of crops and edible fungi) and trophic cascades of crops, invertebrate herbivores and natural enemies in cropping systems. We then explore the socioeconomic advantages (e.g., yield, economic and environmental performance) of these trophic cascades. Finally, we propose a multi-perspective framework to promote the cascading social-ecological benefits of species diversity for agricultural sustainability. Integrating the benefits of trophic cascades into agricultural socioeconomic systems requires policies and legislation that support multi-species co-culture practices and the willingness of consumers to pay for these practices through higher prices for agricultural products.

Accurate Density Prediction of Sesquiterpenoid HEDFs and the Multiproperty Computing Server SesquiterPre.

Accurate and rapid evaluation of density is crucial for evaluating the packing and combustion characteristics of high-energy-density fuels (HEDFs). This parameter is pivotal in the selection of high-performance HEDFs. Our study leveraged a polycyclic compound density data set and quantum chemical (QC) descriptors to establish a correlation with the target properties using the XGBoost algorithm. We utilized a recursive feature elimination method to simplify the model and developed a concise and interpretable density prediction model incorporating only six QC descriptors. The model demonstrated robust performance, achieving coefficients of determination (R 2) of 0.967 and 0.971 for internal and external test sets, respectively, and root-mean-square errors (RMSE) of 0.031 and 0.027 g/cm3, respectively. Compared to the other two mainstream methods, the marginal discrepancy between the predicted and actual molecular densities underscores the model's superior predictive ability and more usefulness for energy density calculation. Furthermore, we developed a web server (SesquiterPre, https://sespre.cmdrg.com/#/) that can simultaneously calculate the density, enthalpy of combustion, and energy density of sesquiterpenoid HEDFs, which greatly facilitates the use of researchers and is of great significance for accelerating the design and screening of novel sesquiterpenoid HEDFs.

Serum brain derived neurotrophic factor levels and post-stroke depression in ischemic stroke patients.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) is crucial for neuronal survival and may be implicated in the pathophysiological process of depression. This study aimed to prospectively investigate the association between serum BDNF and post-stroke depression (PSD) at 3 months in a multicenter cohort study. METHODS: A total of 611 ischemic stroke patients with serum BDNF measurements from the China Antihypertensive Trial in Acute Ischemic Stroke were included in this analysis. We used the 24-item Hamilton Depression Rating Scale to assess depression status at 3 months after ischemic stroke, and PSD was defined as a score of ≥8. RESULTS: Baseline serum BDNF was inversely associated with the risk of depression after ischemic stroke. The multivariable-adjusted odds ratio of PSD for the highest tertile of BDNF was 0.53 (95 % confidence interval, 0.34-0.82; P for trend = 0.004) compared with the lowest tertile. Multivariable-adjusted spline regression model also showed a linear does-response association between serum BDNF levels and PSD at 3 months (P for linearity = 0.006). In addition, adding serum BDNF to conventional risk factors significantly improved the risk reclassification of PSD (net reclassification improvement: 16.98 %, P = 0.039; integrated discrimination index: 0.93 %, P = 0.026). LIMITATIONS: All patients in this study were Chinese, so our findings should be applied to other populations cautiously. CONCLUSIONS: Higher serum BDNF levels at baseline were significantly associated with a decreased risk of PSD at 3 months, suggesting that BDNF might be a valuable predictive biomarker and potential therapeutic target for PSD among ischemic stroke patients.

FBXO45 levels regulated ferroptosis renal tubular epithelial cells in a model of diabetic nephropathy by PLK1.

Objective: This research aims to investigate the role and underlying biological mechanism of FBXO45 in regulating ferroptosis of renal fibrocytes in a diabetic nephropathy (DN) model. Methods: C57BL/6 mice were fed with a high-fat diet and injected with streptozotocin to induce diabetes. Human renal glomerular endothelial cells stimulated with d-glucose. Results: Serum FBXO45 mRNA expression was found to be down-regulated in patients with DN. There was a negative correlation between the expression of serum FBXO45 mRNA and serum α-SMA, Collagen I, and E-cadherin mRNA in patients with DN. Additionally, the expression of serum FBXO45 mRNA showed a negative correlation with blood sugar levels. Based on a 3D model prediction, it was observed that FBXO45 interacts with polo-like kinase 1 (PLK1) at GLY-271, ILE-226, GLY-166, LEU-165, ARG-245, and ASN-220, while PLK1 interacts with FBXO45 at TYR-417, ARG-516, HIS-489, TYR-485, GLN-536, and ARG-557. This interaction was confirmed through immunoprecipitation assay, which showed the interlinking of FBXO45 protein with PLK1 protein. Conclusions: These findings indicate that FBXO45 plays a role in mitigating ferroptosis in DN through the regulation of the PLK1/GPX4/SOX2 pathway. This highlights the potential of targeting FBXO45 as a therapeutic approach to ameliorate ferroptosis in DN.

Unlocking Clinical Insights: Lymphocyte-Specific Protein Tyrosine Kinase Candidates as Promising Therapeutic Targets for Pancreatic Cancer Risk Stratification.

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer. Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined. Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis. Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Examining the cultural influence on online stances towards COVID-19 preventive measures and their impact on incidence and mortality: A global stance detection analysis of tweets.

During the COVID-19 pandemic, nations implemented various preventive measures, triggering varying online responses. This study examines cultural influences on public online stances toward these measures and their impacts on COVID-19 cases/deaths. Stance detection analysis was used to analyze 16,428,557 Tweets regarding COVID-19 preventive measures from 95 countries, selected based on Hofstede's cultural dimensions. To ensure the variety of population, countries were chosen based on Twitter data availability and a minimum sample size of 385 tweets, achieving a 95% confidence level with a 5% margin of error. The weighted regression analysis revealed that the relationship between culture and online stances depends on the cultural congruence of each measure. Specifically, power distance positively predicted stances for all measures, while indulgence had a negative effect overall. Effects of other cultural indices varied across measures. Individualism negatively affected face coverings stances. Uncertainty avoidance influenced lockdown and vaccination stances negatively but had a positive effect on social distancing stances. Long-term orientation negatively affected lockdown and social distancing stances but positively influenced quarantine stances. Cultural tightness only negatively affected face coverings and quarantine stances. Online stances toward face coverings mediated the relationship between cultural indices and COVID-19 cases/deaths. As such, public health officials should consider cultural profiles and use culturally congruent communication strategies when implementing preventive measures for future pandemics. Furthermore, leveraging digital tools is vital in navigating and shaping online stances to enhance the effectiveness of these measures.

Faults locating of power distribution systems based on successive PSO-GA algorithm.

As the terminal of the power system, the distribution network is the main area where failures occur. In addition, with the integration of distributed generation, the traditional distribution network becomes more complex, rendering the conventional fault location algorithms based on a single power supply obsolete. Therefore, it is necessary to seek a new algorithm to locate the fault of the distributed power distribution network. In existing fault localization algorithms for distribution networks, since there are only two states of line faults, which can usually be represented by 0 and 1, most algorithms use discrete algorithms with this characteristic for iterative optimization. Therefore, this paper combines the advantages of the particle swarm algorithm and genetic algorithm and uses continuous real numbers for iteration to construct a successive particle swarm genetic algorithm (SPSO-GA) different from previous algorithms. The accuracy, speed, and fault tolerance of SPSO-GA, discrete particle swarm Genetic algorithm, and artificial fish swarm algorithm are compared in an IEEE33-node distribution network with the distributed power supply. The simulation results show that the SPSO-GA algorithm has high optimization accuracy and stability for single, double, or triple faults. Furthermore, SPSO-GA has a rapid convergence velocity, requires fewer particles, and can locate the fault segment accurately for the distribution network containing distorted information.

Structural annotation of unknown molecules in a miniaturized mass spectrometer based on a transformer enabled fragment tree method.

Structural annotation of small molecules in tandem mass spectrometry has always been a central challenge in mass spectrometry analysis, especially using a miniaturized mass spectrometer for on-site testing. Here, we propose the Transformer enabled Fragment Tree (TeFT) method, which combines various types of fragmentation tree models and a deep learning Transformer module. It is aimed to generate the specific structure of molecules de novo solely from mass spectrometry spectra. The evaluation results on different open-source databases indicated that the proposed model achieved remarkable results in that the majority of molecular structures of compounds in the test can be successfully recognized. Also, the TeFT has been validated on a miniaturized mass spectrometer with low-resolution spectra for 16 flavonoid alcohols, achieving complete structure prediction for 8 substances. Finally, TeFT confirmed the structure of the compound contained in a Chinese medicine substance called the Anweiyang capsule. These results indicate that the TeFT method is suitable for annotating fragmentation peaks with clear fragmentation rules, particularly when applied to on-site mass spectrometry with lower mass resolution.

IGSF8 is an innate immune checkpoint and cancer immunotherapy target.

Antigen presentation defects in tumors are prevalent mechanisms of adaptive immune evasion and resistance to cancer immunotherapy, whereas how tumors evade innate immunity is less clear. Using CRISPR screens, we discovered that IGSF8 expressed on tumors suppresses NK cell function by interacting with human KIR3DL2 and mouse Klra9 receptors on NK cells. IGSF8 is normally expressed in neuronal tissues and is not required for cell survival in vitro or in vivo. It is overexpressed and associated with low antigen presentation, low immune infiltration, and worse clinical outcomes in many tumors. An antibody that blocks IGSF8-NK receptor interaction enhances NK cell killing of malignant cells in vitro and upregulates antigen presentation, NK cell-mediated cytotoxicity, and T cell signaling in vivo. In syngeneic tumor models, anti-IGSF8 alone, or in combination with anti-PD1, inhibits tumor growth. Our results indicate that IGSF8 is an innate immune checkpoint that could be exploited as a therapeutic target.

FsCGBP, a Cutinase G-Box Binding Protein, Regulates the Growth, Development, and Virulence of Fusarium sacchari, the Pathogen of Sugarcane Pokkah Boeng Disease.

Fusarium sacchari is a causal agent of sugarcane Pokkah boeng, an important fungal disease that causes a considerable reduction in yield and sugar content in susceptible varieties of sugarcane worldwide. Despite its importance, the fungal factors that regulate the virulence of this pathogen remain largely unknown. In our previous study, mapping of an insertional mutant defect in virulence resulted in the identification of a cutinase G-box binding protein gene, designated FsCGBP, that encodes a C2H2-type transcription factor (TF). FsCGBP was shown to localize in the nuclei, and the transcript level of FsCGBP was significantly upregulated during the infection process or in response to abiotic stresses. Deletion or silencing of FsCGBP resulted in a reduction in mycelial growth, conidial production, and virulence and a delay in conidial germination in the F. sacchari. Cutinase genes FsCUT2, FsCUT3, and FsCUT4 and the mitogen-activated protein kinase (MAPK) genes FsHOG1, FsMGV1, and FsGPMK1, which were significantly downregulated in ΔFsCGBP. Except for FsHOG1, all of these genes were found to be transcriptionally activated by FsCGBP using the yeast one-hybrid system in vitro. The deletion of individual cutinase genes did not result in any of the phenotypes exhibited in the ΔFsCGBP mutant, except for cutinase activity. However, disruption of the MAPK pathway upon deletion of FsMGV1 or FsGPMK1 resulted in phenotypes similar to those of the ΔFsCGBP mutant. The above results suggest that FsCGBP functions by regulating the MAPK pathway and cutinase genes, providing new insights into the mechanism of virulence regulation in F. sacchari.

Progress of lymphocyte activation gene 3 and programmed cell death protein 1 antibodies for cancer treatment: A review.

The application of immune checkpoint inhibitors has proven to be an effective treatment for cancer. Immune checkpoints such as programmed cell death protein 1/programmed cell death protein 1 ligand 1 (PD-1/PD-L1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), T-cell immunoglobulin-3 (TIM-3), T-cell immunoglobulin and ITIM domain (TIGIT), and lymphocyte activation gene-3 (LAG-3) have received extensive attention, and the efficacy of antibodies or inhibitors against these checkpoints (either alone or in combination) has been evaluated in many tumors. This paper provides a brief overview of the PD-1 and LAG-3 checkpoints, and then shifts focus to the combined use of PD-1 and LAG-3 antibodies in both in vivo and in vitro experiments. In the in vitro experiments, we examined the correlation between the expression and activation of these inhibitors on T cells, and also assessed toxicity in animals in preparation for in vivo experiments. The effects of the combined use of PD-1 and LAG-3 antibodies were then summarized in animal models of melanoma, MC38 carcinoma, and other tumors. In clinical studies, the combined application of these antibodies was assessed in patients with melanoma, colorectal, breast, and renal cell cancers, as well as other solid tumors. In general, the combination of PD-1 and LAG-3 antibodies has shown promising results in both in vivo and in vitro studies.

Bombyx mori voltage-dependent anion-selective channel induces programmed cell death to defend against Bombyx mori nucleopolyhedrovirus infection.

BACKGROUND: Voltage-dependent anion-selective channels (VDACs) serve as pore proteins within the mitochondrial membrane, aiding in the regulation of cell life and cell death. Although the occurrence of cell death is crucial for defense against virus infection, the function played by VDAC in Bombyx mori, in response to the influence of Bombyx mori nucleopolyhedrovirus (BmNPV), remains unclear. RESULTS: BmVDAC was found to be relatively highly expressed both during embryonic development, and in the Malpighian tubule and midgut. Additionally, the expression levels of BmVDAC were found to be different among silkworm strains with varying levels of resistance to BmNPV, strongly suggesting a connection between BmVDAC and virus infection. To gain further insight into the function of BmVDAC in BmNPV, we employed RNA interference (RNAi) to silence and overexpress it by pIZT/V5-His-mCherry. The results revealed that BmVDAC is instrumental in developing the resistance of host cells to BmNPV infection in BmN cell-line cells, which was further validated as likely to be associated with initiating programmed cell death (PCD). Furthermore, we evaluated the function of BmVDAC in another insect, Spodoptera exigua. Knockdown of the BmVDAC homolog in S. exigua, SeVDAC, made the larvae more sensitive to BmNPV. CONCLUSION: We have substantiated the pivotal role of BmVDAC in conferring resistance against BmNPV infection, primarily associated with the initiation of PCD. The findings of this study shine new light on the molecular mechanisms governing the silkworm's response to BmNPV infection, thereby supporting innovative approaches for pest biocontrol. © 2024 Society of Chemical Industry.

Diverse thermal desorption combined with self-aspirating corona discharge ionization for direct mass spectrometry analysis of complex samples.

The thermal desorption (TD) technique is widely employed in modern mass spectrometry to facilitate the detection of non-volatile analytes. In this study, we developed a compact TD device based on a small resistance wire and coupled it with a self-aspirating corona discharge ionization (CDI) source to conduct direct MS analysis of various liquid and solid samples. Due to its small size and low heat capacity, the temperature of the TD module can be flexibly and rapidly modulated by controlling the power sequence. Multiple heating modes, including pulse heating (PH), isothermal heating, and step heating (SH), are realized and characterized, and then applied for the detection of different real samples. In particular, the PH mode is suitable for the simultaneous detection of multiple components in samples with relatively simple matrices, while the SH mode is capable of component separation. In addition, the sensitivity and quantitative capability of the TD-CDI system for DEP solutions were tested, showing acceptable stability with a relative standard deviation of about 6.7% and a detection limit of 0.088 ng. Overall, the developed TD-CDI system provides a simple, convenient, and versatile tool for direct mass spectrometry analysis of real samples.

Studying the role of Bombyx mori molybdenum cofactor sulfurase in Bombyx mori nucleopolyhedrovirus infection.

Molybdenum cofactor sulfurase (MoCoS) is a key gene involved in the uric acid metabolic pathway that activates xanthine dehydrogenase to synthesise uric acid. Uric acid is harmful to mammals but plays crucial roles in insects, one of which is the immune responses. However, the function of Bombyx mori MoCoS in response to BmNPV remains unclear. In this study, BmMoCoS was found to be relatively highly expressed in embryonic development, gonads and the Malpighian tubules. In addition, the expression levels of BmMoCoS were significantly upregulated in three silkworm strains with different levels of resistance after virus infection, suggesting a close link between them. Furthermore, RNAi and overexpression studies showed that BmMoCoS was involved in resistance to BmNPV infection, and its antivirus effects were found to be related to the regulation of uric acid metabolism, which was uncovered by inosine- and febuxostat-coupled RNAi and overexpression. Finally, the BmMoCoS-mediated uric acid pathway was preliminarily confirmed to be a potential target to protect silkworms from BmNPV infection. Overall, this study provides new evidence for elucidating the molecular mechanism of silkworms in response to BmNPV infection and new strategies for the prevention of viral infections in sericulture.

Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was developed. Specifically, volatile compounds in coffee aroma were detected using self-aspiration corona discharge ionization mass spectrometry (SACDI-MS), and the acquired MS data were processed using a customized deep learning algorithm to perform origin authentication automatically. To facilitate high-throughput analysis, an air curtain sampling device was designed and coupled with SACDI-MS to prevent volatile mixing and signal overlap. An accuracy of 99.78% was achieved in the classification of coffee samples from six origins at a throughput of 1 s per sample. The proposed approach may be effective in preventing coffee fraud owing to its straightforward operation, rapidity, and high accuracy and thus benefit consumers.

Self-Efficacy in Patients With Hypertension and Their Perceived Usage of Patient Portals.

INTRODUCTION: Self-efficacy in individuals optimizes their hypertension management. Electronic patient portals are being increasingly used to support chronic disease management, as they raise the health literacy of patients and enable them in self-management. However, the association between the use of patient portals and self-efficacy in hypertension management remains unclear. The study aimed to determine the association between self-efficacy among patients with hypertension who are managed in primary care and their demographic characteristics and usage patterns of patient portals. METHOD: A cross-sectional survey was conducted at a public primary care clinic in urban Singapore. Multi-ethnic adult patients with hypertension were invited to participate in a self-administered electronic questionnaire. Chi-square test was performed for bivariate analysis; adjusted logistic regression models were used for factors with P value <.1. RESULTS: A total of 310 patients (66.8% Chinese, 55.5% males, mean age of 63.1 years) completed the survey. Patient portal users had higher self-efficacy scores than non-users (mean score=63 vs 60, maximum = 80, P = .011). The factors associated with increased patient portal access included younger age <65 years (absolute odds ratio [AOR] = 2.634, 95%CI = 1.432-4.847; P = .002), monthly income >$5000 (AOR = 2.324, 95%CI = 1.104-4.892; P = .026), and post-secondary education level (AOR = 3.128, 95%CI = 1.675-5.839; P < .001). Most patients (93.1%) used the portal to check medical appointments but only1.3% of them used it to record home blood pressure measurements (HBPM). CONCLUSIONS: Patient portal usage was associated with higher self-efficacy scores in patients with hypertension. These users were younger, more educated, and earned more than the non-users, but only 1.3% of them used it for HBPM documentation.

Deep learning for virtual orthodontic bracket removal: tool establishment and application.

OBJECTIVE: We aimed to develop a tool for virtual orthodontic bracket removal based on deep learning algorithms for feature extraction from bonded teeth and to demonstrate its application in a bracket position assessment scenario. MATERIALS AND METHODS: Our segmentation network for virtual bracket removal was trained using dataset A, containing 978 bonded teeth, 20 original teeth, and 20 brackets generated by scanners. The accuracy and segmentation time of the network were tested by dataset B, which included an additional 118 bonded teeth without knowing the original tooth morphology. This tool was then applied for bracket position assessment. The clinical crown center, bracket center, and orientations of separated teeth and brackets were extracted for analyzing the linear distribution and angular deviation of bonded brackets. RESULTS: This tool performed virtual bracket removal in 2.9 ms per tooth with accuracies of 98.93% and 97.42% (P < 0.01) in datasets A and B, respectively. The tooth surface and bracket characteristics were extracted and used to evaluate the results of manually bonded brackets by 49 orthodontists. Personal preferences for bracket angulation and bracket distribution were displayed graphically and tabularly. CONCLUSIONS: The tool's efficiency and precision are satisfactory, and it can be operated without original tooth data. It can be used to display the bonding deviation in the bracket position assessment scenario. CLINICAL SIGNIFICANCE: With the aid of this tool, unnecessary bracket removal can be avoided when evaluating bracket positions and modifying treatment plans. It has the potential to produce retainers and orthodontic devices prior to tooth debonding.

Endothelial extracellular vesicles induce acute lung injury via follistatin-like protein 1.

Cardiopulmonary bypass has been speculated to elicit systemic inflammation to initiate acute lung injury (ALI), including acute respiratory distress syndrome (ARDS), in patients after cardiac surgery. We previously found that post-operative patients showed an increase in endothelial cell-derived extracellular vesicles (eEVs) with components of coagulation and acute inflammatory responses. However, the mechanism underlying the onset of ALI owing to the release of eEVs after cardiopulmonary bypass, remains unclear. Plasma plasminogen-activated inhibitor-1 (PAI-1) and eEV levels were measured in patients with cardiopulmonary bypass. Endothelial cells and mice (C57BL/6, Toll-like receptor 4 knockout (TLR4-/-) and inducible nitric oxide synthase knockout (iNOS-/-)) were challenged with eEVs isolated from PAI-1-stimulated endothelial cells. Plasma PAI-1 and eEVs were remarkably enhanced after cardiopulmonary bypass. Plasma PAI-1 elevation was positively correlated with the increase in eEVs. The increase in plasma PAI-1 and eEV levels was associated with post-operative ARDS. The eEVs derived from PAI-1-stimulated endothelial cells could recognize TLR4 to stimulate a downstream signaling cascade identified as the Janus kinase 2/3 (JAK2/3)-signal transducer and activator of transcription 3 (STAT3)-interferon regulatory factor 1 (IRF-1) pathway, along with iNOS induction, and cytokine/chemokine production in vascular endothelial cells and C57BL/6 mice, ultimately contributing to ALI. ALI could be attenuated by JAK2/3 or STAT3 inhibitors (AG490 or S3I-201, respectively), and was relieved in TLR4-/- and iNOS-/- mice. eEVs activate the TLR4/JAK3/STAT3/IRF-1 signaling pathway to induce ALI/ARDS by delivering follistatin-like protein 1 (FSTL1), and FSTL1 knockdown in eEVs alleviates eEV-induced ALI/ARDS. Our data thus demonstrate that cardiopulmonary bypass may increase plasma PAI-1 levels to induce FSTL1-enriched eEVs, which target the TLR4-mediated JAK2/3/STAT3/IRF-1 signaling cascade and form a positive feedback loop, leading to ALI/ARDS after cardiac surgery. Our findings provide new insight into the molecular mechanisms and therapeutic targets for ALI/ARDS after cardiac surgery.