Combining metabolomics and network pharmacology to investigate the protective effect of Jiawei Xinglou Chengqi Granules in ischemic stroke.

Jiawei Xinglou Chengqi Granule (JXCG) is an effective herbal medicine for the treatment of ischemic stroke (IS). JXCG has been shown to effectively ameliorate cerebral ischemic symptoms in clinical practice, but the underlying mechanisms are unclear. In this study, we investigated the mechanisms of action of JXCG in the treatment of IS by combining metabolomics with network pharmacology. The chemical composition of JXCG was analyzed using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Ultra-high performance liquid chromatography-tandem time-of-flight mass spectrometry (UHPLC-Q-TOF MS) untargeted metabolomics were used to identify differential metabolites within metabolic pathways. Network pharmacology was applied to mine potential targets of JXCG in the treatment of IS. The identified key targets were validated by constructing an integrated network of metabolomics and network pharmacology and by molecular docking using Cytoscape. The effect of JXCG on IS was evaluated in vivo, and the predicted targets and pathways of JXCG in IS therapy were assessed using immunoblotting. Combining metabolomics and network pharmacology, we identified the therapeutic targets of JXCG for IS. Notably, JXCG lessened neuronal damage and reduced cerebral infarct size in rats with IS. Western blot analysis showed that JXCG upregulated PRKCH and downregulated PRKCE and PRKCQ proteins. Our combined network pharmacology and metabolomics findings showed that JXCG may have therapeutic potential in the treatment of IS by targeting multiple factors and pathways.

Bletilla striata polysaccharide-coated andrographolide nanomicelles for targeted drug delivery to enhance anti-colon cancer efficacy.

Background: Vitamin E, which is also known as tocopherol, is a compound with a polyphenol structure. Its esterified derivative, Vitamin E succinate (VES), exhibits unique anticancer and healthcare functions as well as immunomodulatory effects. Natural polysaccharides are proved to be a promising material for nano-drug delivery systems, which show excellent biodegradability and biocompatibility. In this study, we employed a novel bletilla striata polysaccharide-vitamin E succinate polymer (BSP-VES) micelles to enhance the tumor targeting and anti-colon cancer effect of andrographolide (AG). Methods: BSP-VES polymer was synthesized through esterification and its structure was confirmed using 1H NMR. AG@BSP-VES was prepared via the dialysis method and the drug loading, entrapment efficiency, stability, and safety were assessed. Furthermore, the tumor targeting ability of AG@BSP-VES was evaluated through targeted cell uptake and in vivo imaging. The antitumor activity of AG@BSP-VES was measured in vitro using MTT assay, Live&Dead cell staining, and cell scratch test. Results: In this study, we successfully loaded AG into BSP-VES micelles (AG@BSP-VES), which exhibited good stability, biosafety and sustained release effect. In addition, AG@BSP-VES also showed excellent internalization capability into CT26 cells compared with NCM460 cells in vitro. Meanwhile, the specific delivery of AG@BSP-VES micelles into subcutaneous and in-situ colon tumors was observed compared with normal colon tissues in vivo during the whole experiment process (1-24 h). What's more, AG@BSP-VES micelles exhibited significant antitumor activities than BSP-VES micelles and free AG. Conclusion: The study provides a meaningful new idea and method for application in drug delivery system and targeted treatment of colon cancer based on natural polysaccharides.

Association of Dietary Retinol Intake and Serum Neurofilament Light Chain Levels: Results from NHANES 2013-2014.

BACKGROUND: There is increasing evidence suggesting that serum neurofilament light chain (sNfL) levels can be used as biomarkers for axonal injury. Retinol is recognized for its significant involvement in nervous system function, but the precise connection between dietary retinol and sNfL levels remains uncertain. OBJECTIVE: Our objective was to investigate the relationship between dietary retinol intake and sNfL, and to find an optimal retinol intake level for neurological health. METHODS: In the National Health and Nutrition Examination Survey (NHANES), conducted from 2013 to 2014, a cohort of 1684 participants who met the criteria were selected for the study. sNfL levels were measured from stored serum samples using a novel high-throughput immunoassay platform from Siemens Healthineers. Assessment of dietary retinol intake was performed by a uniformly trained interviewer through a 24 h dietary recall method. A generalized linear model was evaluated to assess the correlation between dietary retinol intake and sNfL concentrations. Furthermore, the nonlinear association between the two is further explored using restricted cubic spline (RCS) analysis. RESULTS: Upon adjusting for potential confounders, a 10% increase in dietary retinol intake was associated with a 3.47% increase in sNfL levels (95% CI: 0.54%, 6.49%) across all participants. This relationship was more pronounced in specific subgroups, including those under 60 years of age, non-obese, impaired estimated glomerular filtration rate (eGFR), and non-diabetic. In subgroup analysis, among those younger than 60 years of age (percent change: 3.80%; 95% CI: 0.43%, 7.28%), changes were found in non-obese participants (percent change: 6.28%; 95% CI: 2.66%, 10.02%), those with impaired eGFR (percent change: 6.90%; 95% CI: 1.44%, 12.65%), and non-diabetic patients (percentage change: 4.17%; 95% CI: 1.08%, 7.36%). RCS analysis showed a linear relationship between dietary retinol intake and sNfL levels. Furthermore, the positive correlation between the two was more significant after the inflection point, according to piecewise linear analysis. CONCLUSION: This current investigation uncovered a J-shaped relationship between dietary retinol and sNfL levels, suggesting that axonal damage can occur when dietary retinol intake increases more than a specific threshold. These findings need to be further confirmed in future prospective studies to determine the precise intake level that may trigger axonal injury.

Mitochondrial glycerol 3-phosphate dehydrogenase deficiency exacerbates lipotoxic cardiomyopathy.

Metabolic diseases such as obesity and diabetes induce lipotoxic cardiomyopathy, which is characterized by myocardial lipid accumulation, dysfunction, hypertrophy, fibrosis and mitochondrial dysfunction. Here, we identify that mitochondrial glycerol 3-phosphate dehydrogenase (mGPDH) is a pivotal regulator of cardiac fatty acid metabolism and function in the setting of lipotoxic cardiomyopathy. Cardiomyocyte-specific deletion of mGPDH promotes high-fat diet induced cardiac dysfunction, pathological hypertrophy, myocardial fibrosis, and lipid accumulation. Mechanically, mGPDH deficiency inhibits the expression of desuccinylase SIRT5, and in turn, the hypersuccinylates majority of enzymes in the fatty acid oxidation (FAO) cycle and promotes the degradation of these enzymes. Moreover, manipulating SIRT5 abolishes the effects of mGPDH ablation or overexpression on cardiac function. Finally, restoration of mGPDH improves lipid accumulation and cardiomyopathy in both diet-induced and genetic obese mouse models. Thus, our study indicates that targeting mGPDH could be a promising strategy for lipotoxic cardiomyopathy in the context of obesity and diabetes.

Enhancing generalizability and performance in drug-target interaction identification by integrating pharmacophore and pre-trained models.

MOTIVATION: In drug discovery, it is crucial to assess the drug-target binding affinity (DTA). Although molecular docking is widely used, computational efficiency limits its application in large-scale virtual screening. Deep learning-based methods learn virtual scoring functions from labeled datasets and can quickly predict affinity. However, there are three limitations. First, existing methods only consider the atom-bond graph or one-dimensional sequence representations of compounds, ignoring the information about functional groups (pharmacophores) with specific biological activities. Second, relying on limited labeled datasets fails to learn comprehensive embedding representations of compounds and proteins, resulting in poor generalization performance in complex scenarios. Third, existing feature fusion methods cannot adequately capture contextual interaction information. RESULTS: Therefore, we propose a novel DTA prediction method named HeteroDTA. Specifically, a multi-view compound feature extraction module is constructed to model the atom-bond graph and pharmacophore graph. The residue concat graph and protein sequence are also utilized to model protein structure and function. Moreover, to enhance the generalization capability and reduce the dependence on task-specific labeled data, pre-trained models are utilized to initialize the atomic features of the compounds and the embedding representations of the protein sequence. A context-aware nonlinear feature fusion method is also proposed to learn interaction patterns between compounds and proteins. Experimental results on public benchmark datasets show that HeteroDTA significantly outperforms existing methods. In addition, HeteroDTA shows excellent generalization performance in cold-start experiments and superiority in the representation learning ability of drug-target pairs. Finally, the effectiveness of HeteroDTA is demonstrated in a real-world drug discovery study. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/daydayupzzl/HeteroDTA.

Heterologous expression of the insect SVWC peptide WHIS1 inhibits Candida albicans invasion into A549 and HeLa epithelial cells.

Candida albicans (C. albicans), a microbe commonly isolated from Candida vaginitis patients with vaginal tract infections, transforms from yeast to hyphae and produces many toxins, adhesins, and invasins, as well as C. albicans biofilms resistant to antifungal antibiotic treatment. Effective agents against this pathogen are urgently needed. Antimicrobial peptides (AMPs) have been used to cure inflammation and infectious diseases. In this study, we isolated whole housefly larvae insect SVWC peptide 1 (WHIS1), a novel insect single von Willebrand factor C-domain protein (SVWC) peptide from whole housefly larvae. The expression pattern of WHIS1 showed a response to the stimulation of C. albicans. In contrast to other SVWC members, which function as antiviral peptides, interferon (IFN) analogs or pathogen recognition receptors (PRRs), which are the prokaryotically expressed MdWHIS1 protein, inhibit the growth of C. albicans. Eukaryotic heterologous expression of WHIS1 inhibited C. albicans invasion into A549 and HeLa cells. The heterologous expression of WHIS1 clearly inhibited hyphal formation both extracellularly and intracellularly. Furthermore, the mechanism of WHIS1 has demonstrated that it downregulates all key hyphal formation factors (ALS1, ALS3, ALS5, ECE1, HWP1, HGC1, EFG1, and ZAP1) both extracellularly and intracellularly. These data showed that heterologously expressed WHIS1 inhibits C. albicans invasion into epithelial cells by affecting hyphal formation and adhesion factor-related gene expression. These findings provide new potential drug candidates for treating C. albicans infection.

A case report of pulmonary atresia with intact ventricular septum: an extraordinary finding of subsystemic right ventricle.

Background: Massive tricuspid regurgitation (TR) is the most common feature of pulmonary atresia with intact ventricular septum (PA/IVS), and mild or absent TR is observed in severe right ventricular (RV) dysplasia or RV-to-coronary fistulous connections, resulting in non-biventricular (BV) outcomes postnatally. Case summary: We report a case of fetal severe pulmonary stenosis with IVS diagnosed at 26 weeks of gestation. The severity of RV hypoplasia did not worsen or reach indications for intrauterine intervention, while the jet velocity of TR decreased significantly during pregnancy. The fetus was definitely diagnosed with PA/IVS with mild RV dysplasia after birth. Unusually, the fetus did not experience severe TR and myocardial sinusoids, the TR jet velocity was maintained at 2.0 m/s, and the coronary artery was almost normal. The incapable RV cannot pump blood into pulmonary circulation after RV decompression from valvular perforation and balloon dilation. It may be an extraordinary finding of subsystemic RV. Conclusion: PA/IVS is a heterogeneous disease with various degrees of RV dysplasia. Mild or no baseline TR is a reliable indicator with non-BV outcomes for fetal PA/IVS, even with acceptable dysplasia RV structures.

Neutrophil extracellular traps promote proliferation of pulmonary smooth muscle cells mediated by CCDC25 in pulmonary arterial hypertension.

BACKGROUND: Previous studies have indicated that neutrophil extracellular traps (NETs) play a pivotal role in pathogenesis of pulmonary arterial hypertension (PAH). However, the specific mechanism underlying the impact of NETs on pulmonary artery smooth muscle cells (PASMCs) has not been determined. The objective of this study was to elucidate underlying mechanisms through which NETs contribute to progression of PAH. METHODS: Bioinformatics analysis was employed in this study to screen for potential molecules and mechanisms associated with occurrence and development of PAH. These findings were subsequently validated in human samples, coiled-coil domain containing 25 (CCDC25) knockdown PASMCs, as well as monocrotaline-induced PAH rat model. RESULTS: NETs promoted proliferation of PASMCs, thereby facilitating pathogenesis of PAH. This phenomenon was mediated by the activation of transmembrane receptor CCDC25 on PASMCs, which subsequently activated ILK/ß-parvin/RAC1 pathway. Consequently, cytoskeletal remodeling and phenotypic transformation occur in PASMCs. Furthermore, the level of NETs could serve as an indicator of PAH severity and as potential therapeutic target for alleviating PAH. CONCLUSION: This study elucidated the involvement of NETs in pathogenesis of PAH through their influence on the function of PASMCs, thereby highlighting their potential as promising targets for the evaluation and treatment of PAH.

Using Smartphones to Enhance Vision Screening in Rural Areas: Pilot Study.

BACKGROUND: While it is treatable, uncorrected refractive error is the number one cause of visual impairment worldwide. This eye condition alone, or together with ocular misalignment, can also cause amblyopia, which is also treatable if detected early but still occurs in about 4% of the population. Mass vision screening is the first and most critical step to address these issues, but due to limited resources, vision screening in many rural areas remains a major challenge. OBJECTIVE: We aimed to pilot-test the feasibility of using smartphone apps to enhance vision screening in areas where access to eye care is limited. METHODS: A vision screening program was piggybacked on a charity summer camp program in a rural county in Sichuan, China. A total of 73 fourth and fifth graders were tested for visual acuity using a standard eye chart and were then tested for refractive error and heterophoria using 2 smartphone apps (a refraction app and a strabismus app, respectively) by nonprofessional personnel. RESULTS: A total of 5 of 73 (6.8%, 95% CI 2.3%-15.3%) students were found to have visual acuity worse than 20/20 (logarithm of minimal angle of resolution [logMAR] 0) in at least one eye. Among the 5 students, 3 primarily had refractive error according to the refraction app. The other 2 students had manifest strabismus (one with 72-prism diopter [PD] esotropia and one with 33-PD exotropia) according to the strabismus app. Students without manifest strabismus were also measured for phoria using the strabismus app in cover/uncover mode. The median phoria was 0.0-PD (IQR 2.9-PD esophoria to 2.2-PD exophoria). CONCLUSIONS: The results from this vision screening study are consistent with findings from other population-based vision screening studies in which conventional tools were used by ophthalmic professionals. The smartphone apps are promising and have the potential to be used in mass vision screenings for identifying risk factors for amblyopia and for myopia control. The smartphone apps may have significant implications for the future of low-cost vision care, particularly in resource-constrained and geographically remote areas.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

Identification of extracellular polymeric substances layer barrier in chloroquine phosphate-disturbed anammox consortia and mechanism dissection on cytotoxic behavior by computational chemistry.

The over-dosing use of chloroquine phosphate (CQ) poses severe threats to human beings and ecosystem due to the high persistence and biotoxicity. The discharge of CQ into wastewater would affect the biomass activity and process stability during the biological processes, e.g., anammox. However, the response mechanism of anammox consortia to CQ remain unknown. In this study, the accurate role of extracellular polymeric substances barrier in attenuating the negative effects of CQ, and the mechanism on cytotoxic behavior were dissected by molecular spectroscopy and computational chemistry. Low concentrations (≤6.0 mg/L) of CQ hardly affected the nitrogen removal performance due to the adaptive evolution of EPS barrier and anammox bacteria. Compact protein of EPS barrier can bind more CQ (0.24 mg) by hydrogen bond and van der Waals force, among which O-H and amide II region respond CQ binding preferentially. Importantly, EPS contributes to the microbiota reshape with selectively enriching Candidatus_Kuenenia for self-protection. Furthermore, the macroscopical cytotoxic behavior was dissected at a molecular level by CQ fate/distribution and computational chemistry, suggesting that the toxicity was ascribed to attack of CQ on functional proteins of anammox bacteria with atom N17 (f-=0.1209) and C2 (f+=0.1034) as the most active electrophilic and nucleophilic sites. This work would shed the light on the fate and risk of non-antibiotics in anammox process.

Azilsartan improves urinary albumin excretion in hypertension mice.

Hypertension is one of the most important risk factors for chronic kidney diseases, leading to hypertensive nephrosclerosis, including excessive albuminuria. Azilsartan, an angiotensin II type 1 receptor blocker, has been widely used for the treatment of hypertension. However, the effects of Azilsartan on urinary albumin excretion in hypertension haven't been reported before. In this study, we investigated whether Azilsartan possesses a beneficial property against albuminuria in mice treated with angiotensin II and a high-salt diet (ANG/HS). Compared to the control group, the ANG/HS group had higher blood pressure, oxidative stress, and inflammatory response, all of which were rescued by Azilsartan dose-dependently. Importantly, the ANG/HS-induced increase in urinary albumin excretion and decrease in the expression of occludin were reversed by Azilsartan. Additionally, it was shown that increased fluorescence intensity of FITC-dextran, declined trans-endothelial electrical resistance (TEER) values, and reduction of occludin and krüppel-like factor 2 (KLF2) were observed in ANG/HS-treated human renal glomerular endothelial cells (HrGECs), then prevented by Azilsartan. Moreover, the regulatory effect of Azilsartan on endothelial monolayer permeability in ANG/HS-treated HrGECs was abolished by the knockdown of KLF2, indicating KLF2 is required for the effect of Azilsartan. We concluded that Azilsartan alleviated diabetic nephropathy-induced increase in Uterine artery embolization (UAE) mediated by the KLF2/occludin axis.

Inhaled Nitric Oxide ReDuce postoperatIve pulmoNAry complicaTions in patiEnts with recent COVID-19 infection (INORDINATE): protocol for a randomised controlled trial.

BACKGROUND: A history of SARS-CoV-2 infection has been reported to be associated with an increased risk of postoperative pulmonary complications (PPCs). Even mild PPCs can elevate the rates of early postoperative mortality, intensive care unit (ICU) admission and prolong the length of ICU and/or hospital stays. Consequently, it is crucial to develop perioperative management strategies that can mitigate these increased risks in surgical patients who have recently been infected with SARS-CoV-2. Accumulating evidence suggests that nitric oxide (NO) inhalation might be effective in treating COVID-19. NO functions in COVID-19 by promoting vasodilation, anticoagulation, anti-inflammatory and antiviral effects. Therefore, our study hypothesises that the perioperative use of NO can effectively reduce PPCs in patients with recent SARS-CoV-2 infection. METHOD AND ANALYSIS: A prospective, double-blind, single-centre, randomised controlled trial is proposed. The trial aims to include participants who are planning to undergo surgery with general anaesthesia and have been recently infected with SARS-CoV-2 (within 7 weeks). Stratified allocation of eligible patients will be performed at a 1:1 ratio based on the predicted risk of PPCs using the Assess Respiratory Risk in Surgical Patients in Catalonia risk index and the time interval between infection and surgery.The primary outcome of the study will be the presence of PPCs within the first 7 days following surgery, including respiratory infection, respiratory failure, pleural effusion, atelectasis, pneumothorax, bronchospasm and aspiration pneumonitis. The primary outcome will be reported as counts (percentage) and will be compared using a two-proportion χ2 test. The common effect across all primary components will be estimated using a multiple generalised linear model. ETHICS AND DISSEMINATION: The trial is approved by the Institutional Review Board of Xijing Hospital (KY20232058-F1). The findings, including positive, negative and inconclusive results, will be published in scientific journals with peer-review processes. TRIAL REGISTRATION NUMBER: NCT05721144.

MetDIT: Transforming and Analyzing Clinical Metabolomics Data with Convolutional Neural Networks.

Clinical metabolomics is growing as an essential tool for precision medicine. However, classical machine learning algorithms struggle to comprehensively encode and analyze the metabolomics data due to their high dimensionality and complex intercorrelations. This article introduces a new method called MetDIT, designed to analyze intricate metabolomics data effectively using deep convolutional neural networks (CNN). MetDIT comprises two components: TransOmics and NetOmics. Since CNN models have difficulty in processing one-dimensional (1D) sequence data efficiently, we developed TransOmics, a framework that transforms sequence data into two-dimensional (2D) images while maintaining a one-to-one correspondence between the sequences and images. NetOmics, the second component, leverages a CNN architecture to extract more discriminative representations from the transformed samples. To overcome the overfitting due to the small sample size and class imbalance, we introduced a feature augmentation module (FAM) and a loss function to improve the model performance. Furthermore, we systematically optimized the model backbone and image resolution to balance the model parameters and computational costs. To demonstrate the performance of the proposed MetDIT, we conducted extensive experiments using three different clinical metabolomics data sets and achieved better classification performance than classical machine learning methods used in metabolomics, including Random Forest, SVM, XGBoost, and LightGBM. The source code is available at the GitHub repository at https://github.com/Li-OmicsLab/MetDIT, and the WebApp can be found at http://metdit.bioinformatics.vip/.

The impact of intraarterial, intravenous, and combined tirofiban on endovascular treatment for acute intracranial atherosclerotic occlusion.

Background and purpose: Adjunctive tirofiban administration in patients undergoing endovascular treatment (EVT) for acute large vessel occlusion (LVO) has been investigated in several studies. However, the findings are conflict. This study aimed to compare the effect of different administration pathways of tirofiban on patients undergoing EVT for acute LVO with intracranial atherosclerotic disease (ICAD). Methods: Patients were selected from the ANGEL-ACT Registry (Endovascular Treatment Key Technique and Emergency Workflow Improvement of Acute Ischemic Stroke: A Prospective Multicenter Registry Study) and divided into four groups: intra-arterial (IA), intravenous (IV), and intra-arterial plus intravenous (IA+IV) and non-tirofiban. The primary outcome was 90-day ordinal modified Rankin Scale (mRS) score, and the secondary outcomes included the rates of mRS 0-1, 0-2, and 0-3 at 90-day, successful recanalization. The safety outcomes were symptomatic intracranial hemorrhage (sICH) and other safety endpoints. The multivariable logistic regression models adjusting for potential baseline confounders were performed to compare the outcomes. A propensity score matching (PSM) with a 1:1:1:1 ratio was conducted among four groups, and the outcomes were then compared in the post-matched population. Results: A total of 502 patients were included, 80 of which were in the IA-tirofiban group, 73 in IV-tirofiban, 181 in (IA+IV)-tirofiban group, and 168 in the non-tirofiban group. The median (IQR) 90-day mRS score in the four groups of IA, IV, IA+IV, and non-tirofiban was, respectively 3(0-5) vs. 1(0-4) vs. 1(0-4) vs. 3(0-5). The adjusted common odds ratio (OR) for 90-day ordinal modified Rankin Scale distribution with IA-tirofiban vs. non-tirofiban was 0.77 (95% CI, 0.45-1.30, P = 0.330), with IV-tirofiban vs. non-tirofiban was 1.36 (95% CI, 0.78-2.36, P = 0.276), and with (IA+IV)-tirofiban vs. non-tirofiban was 1.03 (95% CI, 0.64-1.64, P = 0.912). The adjusted OR for mRS 0-1 and mRS 0-2 at 90-day with IA-tirofiban vs. non-tirofiban was, respectively 0.51 (95% CI, 0.27-0.98, P = 0.042) and 0.50 (95% CI, 0.26-0.94, P = 0.033). The other outcomes of each group were similar with non-tirofiban group, all P was >0.05. After PSM, the common odds ratio (OR) for 90-day ordinal modified Rankin Scale distribution with IA-tirofiban vs. non-tirofiban was 0.41 (95% CI, 0.18-0.94, P = 0.036), and the OR for mRS 0-1 and mRS 0-2 at 90-day with IA-tirofiban vs. non-tirofiban was, respectively 0.28 (95% CI, 0.11-0.74, P = 0.011) and 0.25 (95% CI, 0.09-0.67, P = 0.006). Conclusions: Intra-arterial administration of tirofiban was associated with worse outcome than non-tirofiban, which suggested that intra-arterial tirofiban had a harmful effect on patients undergoing EVT for ICAD-LVO. Clinical trial registration: http://www.clinicaltrials.gov, Unique identifier: NCT03370939.

Metagenomic analysis towards understanding the effects of ammonia on chain elongation process for medium chain fatty acids production.

The production of medium chain fatty acids (MCFAs) through chain elongation (CE) from organic wastes/wastewater has attracted much attention, while the effects of a common inhibitor-ammonia has not been elucidated. The mechanism of ammonia affecting CE was studied by metagenomic. The lag phase duration of caproate production was increased, and the maximum caproate production rate was decreased by 43.4 % at 4 g-N/L, as compared to 0 g-N/L. And hydrochar (HC) alleviated the inhibition of ammonia at 4 g-N/L. Metagenomic analysis indicated that ammonia induced UBA4085 sp.FDU78 as the dominant microorganism, and metabolic reconstruction revealed its potential CE ability. Furthermore, ammonia inhibited the reverse ß oxidation pathway and Acetyl-CoA production pathway. The tolerance of UBA4085 sp.FDU78 to ammonia was associated with the uptake of inorganic ions, energy conservation, and synthesis of osmoprotectants. The present study provided a deep-insight on the ammonia tolerance mechanism on the CE process.

Explanatory deep learning to predict elevated pulmonary artery pressure in children with ventricular septal defects using standard chest x-rays: a novel approach.

Objective: Early risk assessment of pulmonary arterial hypertension (PAH) in patients with congenital heart disease (CHD) is crucial to ensure timely treatment. We hypothesize that applying artificial intelligence (AI) to chest x-rays (CXRs) could identify the future risk of PAH in patients with ventricular septal defect (VSD). Methods: A total of 831 VSD patients (161 PAH-VSD, 670 nonPAH-VSD) was retrospectively included. A residual neural networks (ResNet) was trained for classify VSD patients with different outcomes based on chest radiographs. The endpoint of this study was the occurrence of PAH in VSD children before or after surgery. Results: In the validation set, the AI algorithm achieved an area under the curve (AUC) of 0.82. In an independent test set, the AI algorithm significantly outperformed human observers in terms of AUC (0.81 vs. 0.65). Class Activation Mapping (CAM) images demonstrated the model's attention focused on the pulmonary artery segment. Conclusion: The preliminary findings of this study suggest that the application of artificial intelligence to chest x-rays in VSD patients can effectively identify the risk of PAH.

Field Evaluation of a Mobile App for Assisting Blind and Visually Impaired Travelers to Find Bus Stops.

Purpose: GPS location-based navigation apps are insufficient to aid blind and visually impaired (BVI) travelers for micro-navigation tasks, such as finding the exact location of bus stops. The resulting large gaps could lead to BVI travelers missing their bus. We evaluated the ability of a signage detection mobile app, All_Aboard, to guide BVI travelers precisely to the bus stops compared to Google Maps alone. Methods: The All_Aboard app detected bus stop signs in real-time via smartphone camera using a deep neural network model, and provided distance coded audio feedback to help localize the detected sign. BVI individuals used the All_Aboard and Google Maps app to localize 10 bus stops each in downtown and suburban Boston, Massachusetts. For each bus stop, the subjects used both apps to navigate as close as possible to the physical bus stop sign, starting from 30 to 50 meters away. The outcome measures were success rate and gap distance between the app-indicated location and the actual physical location of the bus stop. Results: The study involved 24 legally blind participants (mean age [SD] = 51 [14] years; 11 [46%] women). The success rate of the All_Aboard app (91%) was significantly higher than the Google Maps (52%, P < 0.001). The gap distance when using the All_Aboard app was significantly lower (mean = 1.8, 95% confidence interval [CI] = 1.2-2.3 meters) compared to the Google Maps alone (mean = 7, 95% CI = 6.5-7.5 meters, P < 0.001). Conclusions: All_Aboard micro-navigation app guided BVI travelers to bus stops more accurately and reliably than a location-based macro-navigation app alone. Translational Relevance: The All_Aboard app together with a macro-navigation app can potentially help BVI individuals independently access public transportation.

Hirudin inhibit the formation of NLRP3 inflammasome in cardiomyocytes via suppressing oxidative stress and activating mitophagy.

Context: Cardiomyocyte hypertrophy due to hemodynamic overload eventually leads to heart failure. Hirudin has been widely used in the treatment of cardiovascular diseases and NLRP3 inflammasome was proven to induce cardiomyocyte pyroptosis. However, the mechanism by which it inhibits cardiomyocyte hypertrophy remains unclear. Objective: To explore the mechanism of hirudin inhibiting cardiomyocyte hypertrophy based on NLRP3 inflammasome activation and mitophagy. Materials & methods: 1 µM AngII was used for cardiac hypertrophy modeling in H9C2 cells, and cell viability was quantified by CCK-8 assay to screen the appropriate action concentrations of hirudin. After that, we cultured AngII induced-H9C2 cells for 24 h with 0, 0.3, 0.6, and 1.2 mM hirudin, respectively. Next, we marked H9C2 cells with phalloidine and observed them using fluorescence microscope. IL-1ß, IL-18, IL-6, TNF-α, ANP, BNP, ß-MHC, and mtDNA were analyzed by qRT-PCR; ROS were quantified by Flow cytometry; SOD, MDA, and GSH-Px were detected by ELISA; and proteins including NLRP3, ASC, caspase-1, pro-caspase-1, IL-1ß, IL-18, PINK-1, Parkin, beclin-1, LC3-Ⅰ, LC3-Ⅱ, p62, were quantified by western blotting. Results: It was discovered that hirudin reduced the superficial area of AngII-induced H9C2 cells and inhibited the AngII-induced up-regulation of ANP, BNP, and ß-MHC. Besides, hirudin down-regulated the expressions of NLRP3 inflammasome-related cytokines, containing IL-1ß, IL-18, IL-6, TNF-α. It also down-regulated the expression of mtDNA and ROS, decreased the expression levels of NLRP3 inflammasome activation related proteins, including NLRP3, ASC, caspase-1, pro-caspase-1, IL-1ß, IL-18; and increased the expressions of PINK-1, Parkin, beclin-1, LC3-Ⅱ/LC3-Ⅰ, p62 in AngII-induced H9C2 cells. Discussion: Hirudin promoted the process of mitophagy, inhibited the development of inflammation and oxidative stress, and inhibited the activation of the NLRP3 inflammasome and the PINK-1/Parkin pathway. Conclusion: Hirudin has the activity to suppress cardiac hypertrophy may benefit from the inhibition of NLRP3 inflammasome and activating of PINK-1/Parkin related-mitophagy.