A CNN-SVR model for NO2 profile prediction based on MAX-DOAS observations: The influence of Chinese New Year overlapping the 2020 COVID-19 lockdown on vertical distributions of tropospheric NO2 in Nanjing, China.

In this study, a hybrid model, the convolutional neural network-support vector regression model, was adopted to achieve prediction of the NO2 profile in Nanjing from January 2019 to March 2021. Given the sudden decline in NO2 in February 2020, the contribution of the Coronavirus Disease-19 (COVID-19) lockdown, Chinese New Year (CNY), and meteorological conditions to the reduction of NO2 was evaluated. NO2 vertical column densities (VCDs) from January to March 2020 decreased by 59.05% and 32.81%, relative to the same period in 2019 and 2021, respectively. During the period of 2020 COVID-19, the average NO2 VCDs were 50.50% and 29.96% lower than those during the pre-lockdown and post-lockdown periods, respectively. The NO2 volume mixing ratios (VMRs) during the 2020 COVID-19 lockdown significantly decreased below 400 m. The NO2 VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period. This phenomenon could be attributed to the 2020 COVID-19 lockdown. The NO2 VMRs before and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period, which further proves that the decrease in NO2 in February 2020 was attributed to the COVID-19 lockdown. Pollution source analysis of an NO2 pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was transported southwards under the action of the north wind, and the subsequent unfavorable meteorological conditions (local wind speed of < 2.0 m/sec) resulted in the accumulation of pollutants.

Pharmacokinetic study of five components of Fuzheng Huayu tablets in healthy human plasma.

Natural medicines play a crucial role in clinical drug applications, serving as a primary traditional Chinese medicine for the clinical treatment of liver fibrosis. Understanding the in vivo metabolic process of the Fuzheng Huayu (FZHY) formula is essential for delving into its material basis and mechanism. In recent years, there has been a growing body of research focused on the mechanisms and component analysis of FZHY. This study aimed to examine the pharmacokinetics of FZHY in healthy volunteers following oral administration. Blood samples were collected at designated time intervals after the oral intake of 9.6-g FZHY tablets. A UHPLC-Q/Exactive method was developed to assess the plasma concentrations of five components post-FZHY ingestion. The peak time for all components occurred within 10 min. The peak concentration (Cmax ) values for amygdalin, schisandrin, and schisandrin A ranged from 3.47 to 28.80 ng/mL, with corresponding AUC(0-t) values ranging from 10.63 to 103.20 ng h/mL. For schisandrin B and prunasin, Cmax values were in the range of 86.52 to 229.10 ng/mL, and their AUC(0-t) values ranged from 375.26 to 1875.54 ng h/mL, indicating significant exposure within the body. These findings demonstrate that the developed method enables rapid and accurate detection and quantification of the five components in FZHY, offering a valuable reference for its clinical study.

Construction of a predictive model based on MIV-SVR for prognosis and length of stay in patients with traumatic brain injury: Retrospective cohort study.

Objective: To investigate the mean impact value (MIV) method for discerning the most efficacious input variables for the machine learning (ML) model. Subsequently, various ML algorithms are harnessed to formulate a more accurate predictive model that can forecast both the prognosis and the length of hospital stay for patients suffering from traumatic brain injury (TBI). Design: Retrospective cohort study. Participants: The study retrospectively accrued data from 1128 cases of patients who sought medical intervention at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University, within the timeframe spanning from May 2017 to May 2022. Methods: We performed a retrospective analysis of patient data obtained from the Neurosurgery Center of the Second Hospital of Anhui Medical University, covering the period from May 2017 to May 2022. Following meticulous data filtration and partitioning, 70% of the data were allocated for model training, while the remaining 30% served for model evaluation. During the construction phase of the ML models, a gamut of 11 independent variables-including, but not limited to, in-hospital complications and patient age-were utilized as input variables. Conversely, the length of stay (LOS) and the Glasgow Outcome Scale (GOS) scores were designated as output variables. The model architecture was initially refined through the MIV methodology to identify optimal input variables, whereupon five distinct predictive models were constructed, encompassing support vector regression (SVR), convolutional neural networks (CNN), backpropagation (BP) neural networks, artificial neural networks (ANN) and logistic regression (LR). Ultimately, SVR emerged as the most proficient predictive model and was further authenticated through an external dataset obtained from the First Hospital of Anhui Medical University. Results: Upon incorporating the optimal input variables as ascertained through MIV, it was observed that the SVR model exhibited remarkable predictive prowess. Specifically, the Mean Absolute Percentage Error (MAPE) of the SVR model in predicting the GOS score in the test dataset is only 6.30%, and the MAPE in the external validation set is only 7.61%. In terms of predicting hospitalization time, the accuracy of the test and external validation sets were 9.28% and 7.91%, respectively. This error indicator is significantly lower than the error of other prediction models, thus proving the excellent efficacy and clinical reliability of the MIV-optimized SVR model. Conclusion: This study unequivocally substantiates that the incorporation of MIV for selecting optimal input variables can substantially augment the predictive accuracy of machine learning models. Among the models examined, the MIV-SVR model emerged as the most accurate and clinically applicable, thereby rendering it highly conducive for future clinical decision-making processes.

Conditional Goal-Oriented Trajectory Prediction for Interacting Vehicles.

Predicting future trajectories of pairwise traffic agents in highly interactive scenarios, such as cut-in, yielding, and merging, is challenging for autonomous driving. The existing works either treat such a problem as a marginal prediction task or perform single-axis factorized joint prediction, where the former strategy produces individual predictions without considering future interaction, while the latter strategy conducts conditional trajectory-oriented prediction via agentwise interaction or achieves conditional rollout-oriented prediction via timewise interaction. In this article, we propose a novel double-axis factorized joint prediction pipeline, namely, conditional goal-oriented trajectory prediction (CGTP) framework, which models future interaction both along the agent and time axes to achieve goal and trajectory interactive prediction. First, a goals-of-interest network (GoINet) is designed to extract fine-grained features of goal candidates via hierarchical vectorized representation. Furthermore, we propose a conditional goal prediction network (CGPNet) to produce multimodal goal pairs in an agentwise conditional manner, along with a newly designed goal interactive loss to better learn the joint distribution of the intermediate interpretable modes. Explicitly guided by the goal-pair predictions, we propose a goal-oriented trajectory rollout network (GTRNet) to predict scene-compliant trajectory pairs via timewise interactive rollouts. Extensive experimental results confirm that the proposed CGTP outperforms the state-of-the-art (SOTA) prediction models on the Waymo open motion dataset (WOMD), Argoverse motion forecasting dataset, and In-house cut-in dataset. Code is available at https://github.com/LiDinga/CGTP/.

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study.

BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and significantly reduce societal health care burden. Applying novel machine learning methods to the field of TBI may be valuable for determining the prognosis and cost-effectiveness of clinical treatment. OBJECTIVE: We aimed to combine multiple machine learning approaches to build hybrid models for predicting the prognosis and length of hospital stay for adults and children with TBI. METHODS: We collected relevant clinical information from patients treated at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University between May 2017 and May 2022, of which 80% was used for training the model and 20% for testing via screening and data splitting. We trained and tested the machine learning models using 5 cross-validations to avoid overfitting. In the machine learning models, 11 types of independent variables were used as input variables and Glasgow Outcome Scale score, used to evaluate patients' prognosis, and patient length of stay were used as output variables. Once the models were trained, we obtained and compared the errors of each machine learning model from 5 rounds of cross-validation to select the best predictive model. The model was then externally tested using clinical data of patients treated at the First Affiliated Hospital of Anhui Medical University from June 2021 to February 2022. RESULTS: The final convolutional neural network-support vector machine (CNN-SVM) model predicted Glasgow Outcome Scale score with an accuracy of 93% and 93.69% in the test and external validation sets, respectively, and an area under the curve of 94.68% and 94.32% in the test and external validation sets, respectively. The mean absolute percentage error of the final built convolutional neural network-support vector regression (CNN-SVR) model predicting inpatient time in the test set and external validation set was 10.72% and 10.44%, respectively. The coefficient of determination (R2) was 0.93 and 0.92 in the test set and external validation set, respectively. Compared with back-propagation neural network, CNN, and SVM models built separately, our hybrid model was identified to be optimal and had high confidence. CONCLUSIONS: This study demonstrates the clinical utility of 2 hybrid models built by combining multiple machine learning approaches to accurately predict the prognosis and length of stay in hospital for adults and children with TBI. Application of these models may reduce the burden on physicians when assessing TBI and assist clinicians in the medical decision-making process.

Antiliver Fibrosis Formula of Fuzheng Huayu Alleviates Inflammatory Response.

Fuzheng Huayu's (FZHY) formula ameliorated liver fibrosis in clinical and experimental practice. Based on the close link between fibrosis and inflammation, its anti-inflammatory effect and related mechanisms were explored in this present study. With the aid of the inflammatory macrophage model, FZHY significantly blocked nitrite accumulation without observable cytotoxicity due to its suppression of inducible nitric oxide synthase (iNOS) gene and protein expressions in a concentration-depended manner. Proinflammatory mediators including IL-6, CD86, and CD40 were also restrained by FZHY. Interestingly, FZHY induced anti-inflammatory mediators heme oxygenase 1 (HO-1) and peroxisome proliferator-activated receptor γ (PPAR-γ) expressions simultaneously. Downregulation of iNOS and miR-155 and upregulation of PPAR-γ were also observed in CCl4-induced liver fibrosis mice upon FZHY administration. Mechanically, FZHY strikingly eliminated the phosphorylation of STAT1 and MAPK. Taken together, FZYH regulated the balance of proinflammatory and anti-inflammatory mediators partially via modulating STAT1/MAPK pathways and the miR-155/PPAR-γ axis.

Wireless Flexible Magnetic Tactile Sensor with Super-Resolution in Large-Areas.

Tactile recognition is among the basic survival skills of human beings, and advances in tactile sensor technology have been adopted in various fields, bringing benefits such as outstanding performance in manipulating objects and general human-robot interactions. However, promoting enhanced perception of the existing tactile sensors is limited by their sensor array arrangement and wire-connected design. Here we present a wireless flexible magnetic tactile sensor (FMTS) consisting of a multidirection magnetized flexible film (perception module) and a contactless Hall sensor (signal receiving module). The flexible magnetic film is composed of NdFeB microparticles and soft silicone elastomer microparticles, and it transfers the unambiguous transduction of external force position and magnitude into magnetic signals. Benefiting from the specific magnetization arrangement and clustering algorithm, only one Hall sensor is needed in FMTS to perceive the magnitude and position of the contact spot simultaneously with super-resolution (2.1 mm average error) on a large area (3600 mm2), and the effective working distance is also greatly extended (∼30 mm), allowing for the full softness and adaptability to diverse conditions. We anticipate that this design will promote the development of soft tactile sensors and their integration into human-robot interaction and humanoid robot perception.

Lucidenic acid A inhibits the binding of hACE2 receptor with spike protein to prevent SARS-CoV-2 invasion.

High infection caused by mutations of SARS-CoV-2 calls for new prevention strategy. Ganoderma lucidum known as a superior immunoenhancer exhibits various antiviral effects, whether it can resist SARS-CoV-2 remains unclear. Herein, virtual screening combined with in vitro hACE2 inhibition assays were used to investigate its anti SARS-CoV-2 effect. Potential 54 active components, 80 core targets and 20 crucial pathways were identified by the component-target-pathway network. The binding characters of these components to hACE2 and its complexes with spike protein including omicron variant was analyzed by molecular docking. Lucidenic acid A was selected as the top molecule with high affinity to all receptors by forming hydrogen bonds. Molecular dynamics simulation showed it had good binding stability with the receptor proteins. Finally, in vitro FRET test demonstrated it inhibited the hACE2 activity with IC50 2 µmol/mL. Therefore, lucidenic acid A can prevent the virus invasion by blocking hACE2 binding with SARS-CoV-2.

The vertical distribution and potential sources of aerosols in the Yangtze River Delta region of China during open straw burning.

To explore the impact of open straw burning on air quality in the Yangtze River Delta (YRD) and surrounding areas, three key cities in the YRD, namely Hefei, Nanjing, and Shanghai, were selected to observe changes in aerosol characteristics. Based on Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations from May to June 2021, the spatial-temporal distribution and potential sources of aerosol were studied. During the observation period, aerosol optical depth (AOD) in Shanghai was 55.15 % and 29.50 % higher than that in Hefei and Nanjing, respectively. For Shanghai, aerosols accumulated at night, and the aerosol extinction could reach 1.3 km-1 in the morning. The aerosol variations in Hefei and Nanjing were consistent due to the relative conformity of the surrounding environmental conditions (R = 0.84). The vertical distribution of aerosol in all three cities had the same Gaussian shape. The aerosol lifted layers in Nanjing and Shanghai were higher than that in Hefei, with heights of 0.2-0.8 km and 0.2-0.6 km, respectively. The averaged aerosol extinctions for these two cities were 0.34 km-1 and 0.49 km-1, respectively. Pollution source analysis was conducted based on wind field trajectory, satellite observation, and model simulation, taking Hefei as the recipient. The results showed that western Shandong Province, northern Anhui Province, northern Jiangxi Province, central Jiangsu Province, and the central YRD were the most important aerosols sources for Hefei. The contributions of central and southern Jiangsu Province were significantly higher than those of other potential sources, with a WCWTAOD (Meteoinfo concentration weight trajectory) between 1.2 and 3.0. The influence of fine particles produced by open biomass burning inside the YRD was significantly higher than that outside the region (outside contribution: 36.6 %). Regarding the influence between YRD cities, more aerosols were transported from Shanghai to Hefei and Nanjing, with similar transport contributions between Nanjing and Hefei.

Two Myricetin-Derived Flavonols from Morella rubra Leaves as Potent α-Glucosidase Inhibitors and Structure-Activity Relationship Study by Computational Chemistry.

Diabetes mellitus (DM) is a chronic disease characterized by hyperglycemia, and oxidative stress is an important cause and therapeutic target of DM. Phytochemicals such as flavonols are important natural antioxidants that can be used for prevention and treatment of DM. In the present study, six flavonols were precisely prepared and structurally elucidated from Morella rubra leaves, which were screened based on antioxidant assays and α-glucosidase inhibitory activities of different plant tissues. Myricetin-3-O-(2″-O-galloyl)-α-L-rhamnoside (2) and myricetin-3-O-(4″-O-galloyl)-α-L-rhamnoside (3) showed excellent α-glucosidase inhibitory effects with IC50 values of 1.32 and 1.77 µM, respectively, which were hundredfold higher than those of positive control acarbose. Molecular docking simulation illustrated that the presence of galloyl group altered the binding orientation of flavonols, where it occupied the opening of the cavity pocket of α-glucosidase along with Pi-anion interaction with Glu304 and Pi-Pi stacked with His279. Pi-conjugations generated between galloyl moiety and key residues at the active site of α-glucosidase reinforced the flavonol-enzyme binding, which might explain the greatly increased activity of compounds 2 and 3. In addition, 26 flavonols were evaluated for systematic analysis of structure-activity relationship (SAR) between flavonols and α-glucosidase inhibitory activity. By using their pIC50 (-log IC50) values, three-dimensional quantitative SAR (3D-QSAR) models were developed via comparative molecular field analysis (CoMFA) and comparative similarity index analysis (CoMSIA), both of which were validated to possess high accuracy and predictive power as indicated by the reasonable cross-validated coefficient (q 2) and non-cross-validated coefficient (r 2) values. Through analyzing 3D contour maps of both CoMFA and CoMSIA models, QSAR results were in agreement with in vitro experimental data. Therefore, such results showed that the galloyl group in compounds 2 and 3 is crucial for interacting with key residues of α-glucosidase and the established 3D-QSAR models could provide valuable information for the prediction of flavonols with great antidiabetic potential.

Systematic review and meta-analysis of current evidence in endograft therapy vs medical treatment for uncomplicated type B aortic dissection.

OBJECTIVE: Best medical therapy (BMT) should be recommended for treating uncomplicated Stanford type B aortic dissection (uSTBAD), whereas thoracic aortic endovascular repair (TEVAR) has been controversial for uSTBAD. METHODS: In this paper, a meta-analysis was conducted on all available randomized controlled trials and observational studies that evaluated the relative benefits and harms of TEVAR and BMT for the management of patients suffering from uSTBAD. Primary endpoints consisted of early adverse events, long-term adverse events, and aortic remodeling. In addition, risk differences (RDs) or odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. The random-effects model or the fixed-effects model was used in accordance with the 50% heterogeneity threshold. RESULTS: Seven observational studies and two randomized controlled studies from 11 articles that contained 15,066 patients with uSTBAD (1518 TEVARs) met the inclusion criteria. For early outcomes, no significant differences were found between the TEVAR group and the BMT group in aortic rupture, retrograde dissection, paraplegia/paraparesis, reintervention, aorta-related death, and all-cause death. In the long run, the TEVAR group was found to have a significantly lower incidence of adverse events, which included aortic rupture (OR, 0.26; 95% CI, 0.16-0.42; P < .05; heterogeneity: P = .90, I2 = 0%), reintervention (OR, 0.45; 95% CI, 0.26-0.75; P < .05; heterogeneity: P = .17, I2 = 41%), aorta-related death (OR, 0.27; 95% CI, 0.18-0.42; P < .05; heterogeneity: P = .61, I2 = 0%), and all-cause death (OR, 0.52; 95% CI, 0.42-0.66; P < .05; heterogeneity: P = .05, I2 = 53%) as compared with the BMT group. Moreover, in compared with BMT, TEVAR was found to significantly contribute to the complete thrombosis of thoracic false lumen (OR, 55.34; 95% CI, 34.32-89.21; P < .05; heterogeneity: P = .97, I2 = 0%), and aortic regression (true lumen expansion and false lumen shrinkage). CONCLUSIONS: Although early endovascular repair of uSTBAD does not outperform BMT, its implementation is found to be necessary to facilitate the long-term prognosis. Accordingly, if early TEVAR is to be deferred, close follow-up is critical to allow for timely reintervention.

Simultaneous determination of eight analytes of Fuzheng Huayu recipe in beagle dog plasma by UHPLC-Q/exactive Orbitrap HRMS and its application to toxicokinetics.

Fuzheng Huayu recipe (FZHY) is a Chinese patent medicine for the treatment of liver fibrosis. This study aimed to investigate the toxicokinetics of FZHY in beagle dogs after oral administration. Blood samples were collected on days 1, 15 and 28 after oral gavage of FZHY dosages of 400 or 1,200 mg/kg body weight once a day. A UHPLC-Q-Orbitrap method was developed and validated to simultaneously determine and quantify eight components of FZHY in beagle dog plasma. The times to peak concentration for eight components were18-120 min. The peak concentrations (Cmax ) of amygdalin, genistein, daidzein and 3,4-dihydroxybenzaldehyde were 1.43-43.50 ng/ml, the areas under the concentration-time curve (AUC(0-t) ) were 2.45-6,098.25 ng min/ml, and the apparent volumes of distribution (Vd ) were 0.05-131.23 × 104 ml/kg. The values of Cmax of prunasin, schisantherin A, schisandrin A and schisandrin were 7.35-1,450.73 ng/ml, the values of AUC(0-t) were 3,642.30-330,388.65 ng min/ml, and the values of Vd were 11.15-1,087.18 × 104 ml/kg. No obvious accumulation of the eight compounds was observed in beagle dogs. The results showed that the method is rapid, accurate and sensitive, and is suitable for detecting the eight analytes of FZHY. This study provides an important basis for the assessment of FZHY safety.

Comparison of Success Rate and Complications of Totally Percutaneous Decannulation in Patients With Veno-Arterial Extracorporeal Membrane Oxygenation and Endovascular Aneurysm Repair.

Background: Total percutaneous closure for the site of femoral arterial puncture using Perclose ProGlide (PP) has become prevalent post-percutaneous endovascular aortic repair (EVAR) and veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Objective: To evaluate the safety and efficacy of total percutaneous closure of the femoral artery access site post-EVAR compared with VA-ECMO. Methods: This was a retrospective observational study conducted over 4 years, including 88 patients who underwent EVAR (64 patients) and VA-ECMO (24 patients). Perclose ProGlide devices were used in the femoral artery puncture sites closed percutaneously. In this study, technical success was defined as successful arterial closure of the common femoral artery (CFA) without additional surgical or endovascular procedures to prevent vessel leaking. Access site complications, including overt bleeding requiring transfusion or surgical intervention, minor bleeding, tinea cruris, pseudoaneurysm, and lymphocele, were recorded 24 h and 30 days after arterial closure. Results: Each group's technical success rates were 95.8% (VA-ECMO) and 92.2% EVAR, respectively. There were no differences in the periprocedural complications of major bleeding, pseudoaneurysm, minor bleeding, acute limb ischemia, and groin infection. Furthermore, we did not observe any complications such as arterial thrombosis, dissection, stenosis, arteriovenous fistula, hematoma, groin infection, or lymphocele at the access site by following-up an ultrasound examination. There was no significant difference in the technical success rate of percutaneous closure by the PP device in the EVAR and VA-ECMO oxygenation groups. Also, no periprocedural or 30-day complications were observed at the access site of the EVAR and VA-ECMO patients.

Multiple Spontaneous Visceral Arterial Dissections in a Patient With Tolosa-Hunt Syndrome on Corticosteroid Therapy.

Multiple spontaneous visceral arterial dissections are an infrequent occurrence. The etiology, risk factors and natural history of these dissections have not been elucidated, and the optimal therapeutic strategy has not been established. We report a rare case of multiple spontaneous visceral arterial dissections involving the celiac artery, splenic artery, superior mesenteric artery, and right renal artery in a patient with Tolosa-Hunt syndrome on short-term corticosteroid therapy. The patient was subjected to conservative treatment and endovascular repair, achieving good clinical and radiological outcomes during the long-term follow-up period.

Synergistic Antimicrobial Effectiveness of Plant Essential Oil and Its Application in Seafood Preservation: A Review.

The synergistic potential of plant essential oils (EOs) with other conventional and non-conventional antimicrobial agents is a promising strategy for increasing antimicrobial efficacy and controlling foodborne pathogens. Spoilage microorganisms are one of main concerns of seafood products, while the prevention of seafood spoilage principally requires exclusion or inactivation of microbial activity. This review provides a comprehensive overview of recent studies on the synergistic antimicrobial effect of EOs combined with other available chemicals (such as antibiotics, organic acids, and plant extracts) or physical methods (such as high hydrostatic pressure, irradiation, and vacuum-packaging) utilized to reduce the growth of foodborne pathogens and/or to extend the shelf-life of seafood products. This review highlights the synergistic ability of EOs when used as a seafood preservative, discovering the possible routes of the combined techniques for the development of a novel seafood preservation strategy.

Protective and therapeutic effects of nanoliposomal quercetin on acute liver injury in rats.

BACKGROUND: Quercetin, a pigment (flavonoid) found in many plants and foods, has good effects on protecting liver function but poor solubility and bioavailability in vivo. A drug delivery system can improve the accumulation and bioavailability of quercetin in liver. In this study, we used liposomal nanoparticles to entrap quercetin and evaluated its protective and therapeutic effects on drug-induced liver injury in rats. METHODS: The nanoliposomal quercetin was prepared by a thin film evaporation-high pressure homogenization method and characterized by morphology, particle size and drug content. Acute liver injury was induced in rats by composite factors, including carbon tetrachloride injection, high-fat corn powder intake and ethanol drinking. After pure quercetin or nanoliposomal quercetin treatment, liver function was evaluated by detecting serum levels of glutamic-pyruvic transaminase (GPT), glutamic-oxal acetic transaminase (GOT) and direct bilirubin (DBIL). Histology of injured liver tissues was evaluated by hematoxylin and eosin staining. RESULTS: On histology, liposomal nanoparticles loading quercetin were evenly distributed spherical particles. The nanoliposomal quercetin showed high bioactivity and bioavailability in rat liver and markedly attenuated the liver index and pathologic changes in injured liver tissue. With nanoliposomal quercetin treatment, the serum levels of GPT, GOT and DBIL were significantly better than treated with pure quercetin. Using liposomal nanoparticles to entrap quercetin might be an effective strategy to reduce hepatic injury and protect hepatocytes against damage. CONCLUSION: Liposomal nanoparticles may improve the solubility and bioavailability of quercetin in liver. Furthermore, nanoliposomal quercetin could effectively protect rats against acute liver injury and may be a new hepatoprotective and therapeutic agent for patients with liver diseases.

Treatment of Superior Mesenteric Vein Thrombus by Catheter-Directed Thrombolysis.

Contrast-enhanced computed tomography (CT) greatly improves the diagnosis of superior mesenteric vein (SMV) thrombosis, which presents as the unspecific symptom of abdominal pain. Prothrombotic states or thrombophilia and local intra-abdominal infections are major causes of SMV thrombosis. A 37-year-old Chinese woman was diagnosed with SMV and portal vein thrombosis. The patient was initially given 40 mg of heparin sodium every 12 hr and 80,0000 U/day of urokinase using superior mesenteric artery angiography. The abdominal pain was not relieved after treatment. The patient then underwent open surgery, where an ileal branch of the SMV was punctured, a 4F sheath was introduced into the vein toward the portal vein, and a 20-cm Unifuse catheter was placed inside the thrombus for further thrombolysis. Both heparin sodium and urokinase were infused through catheter-directed thrombolysis. The patient's symptoms then gradually resolved.

Total Flavonoids from Radix Glycyrrhiza Exert Anti-Inflammatory and Antitumorigenic Effects by Inactivating iNOS Signaling Pathways.

Inducible nitric oxide synthase (iNOS) plays an important role in inflammation, which has also been considered as a major driver of breast cancer disease progression. Radix Glycyrrhiza (RG) has been broadly used for its anti-inflammatory and antitumorigenic effects. However, the mechanisms of regulation of iNOS in inflammation and cancer have not been fully explored. Total flavonoids isolated from RG (TFRG) exhibited anti-inflammatory activity through the regulation of ERK/NF-κB/miR-155 signaling and suppression of iNOS expression in LPS/IFN-γ stimulated RAW264.7 macrophages without cytotoxicity. TFRG also markedly reduced tumor mass of breast cancer cell MDA-MB-231 xenografts with suppression of iNOS expression, formation of 3-nitrotyrosine (3-NT), and inactivation of protumorigenic JAK2/STAT3 signaling pathway. These results suggested that TFRG limited the development of breast cancer and inflammation due to its property of iNOS inhibition.

Galangin (GG) combined with cisplatin (DDP) to suppress human lung cancer by inhibition of STAT3-regulated NF-κB and Bcl-2/Bax signaling pathways.

Lung cancer represents a significant problem for public health worldwide. Galangin (GG), a natural active compound 3, 5, 7-trihydroxyflavone, is a type of bioflavonoid, which is isolated from the Alpinia galangal root and suggested to induce apoptosis in various cancers. We investigated the ability of Galangin (GG) to attenuate the drug resistance of human lung cancer cells, resistant to treatment of cisplatin (DDP). DDP is a pyrimidine analog, widely used in cancer treatment. Galangin and DDP co-treatment resulted in a dose-dependent suppression of the cell proliferation. Decreasing of p-STAT3 was included in p65 suppression by GG with DDP in combination. Additionally, the presence of GG potentiated the effects of DDP on apoptosis induction through suppressing Bcl-2 in DDP-resistant lung cancer cells. The pro-apoptotic proteins of Bax and Bid were up-regulated, accompanied with Caspases cleavage, leading to apoptosis. Moreover, in mice xenograft models, the combined therapy inhibited tumor growth compared to the GG or DDP treatment alone. Our data indicated a novel therapeutic strategy to potentiate DDP-induced anti-tumor effect in lung cancer cells with DDP resistance by GG through inactivating p-STAT3/p65 and Bcl-2 pathways.