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1.
J Colloid Interface Sci ; 565: 483-493, 2020 Jan 09.
Artigo em Inglês | MEDLINE | ID: mdl-31982715

RESUMO

The complex biology of glioma compromises therapeutic efficacy and results in poor prognosis. Photodynamic therapy (PDT) has emerged as a promising modality for localized tumor ablation with limited damage to healthy brain tissues. However, low photosensitizer concentration and hypoxic microenvironment in glioma tissue hamper the practical applications of PDT. To address the challenges, biocompatible periodic mesoporous organosilica coated Prussian blue nanoparticles (PB@PMOs) are constructed to load a biosafe prodrug 5-aminolevulinic acid (5-ALA), which is pronouncedly converted to protoporphyrin IX (PpIX) in malignant cells. PB@PMO-5-ALA induces a higher accumulation of PpIX in glioma cells compared to free 5-ALA. Meanwhile, the PB@PMOs, with a mean edge length of 81 nm and good biocompatibility, effectively decompose hydrogen peroxide to oxygen in a temperature-responsive manner. Oxygen supply further contributes to the promotion of 5-ALA-PDT. Thus, the photodynamic effect of PB@PMO-5-ALA is significantly improved, imposing augmented cytotoxicity to glioma U87MG cells. Furthermore, ex vivo fluorescence imaging elucidates the tumor PpIX increases by 75% in PB@PMO-5-ALA treated mice than that in 5-ALA treated ones post 12 h injection. Magnetic resonance imaging (MRI) and iron staining strongly demonstrate the accumulation of PB@PMO-5-ALA in glioma tissues with negative contrast enhancement and blue staining deposits, respectively. The nanoparticle accumulation and high PpIX level collaboratively enhance PDT efficacy through PB@PMO-5-ALA, which efficiently suppresses tumor growth, providing a promising option with safety for local glioma ablation.

2.
Nanoscale ; 12(3): 1801-1810, 2020 Jan 23.
Artigo em Inglês | MEDLINE | ID: mdl-31898712

RESUMO

Black titanium dioxide (TiO2) nanoparticles have attracted great attention due to their application in photothermal therapy (PTT). However, single-mode phototherapy has the risk of recurrence, and the high-dose laser usually imposed to improve the PTT performance can bring a potential threat to security. Here, polydopamine (PDA)-coated black TiO2 (b-P25@PDA) nanoparticles with a core-shell structure were synthesized for enhanced PTT; then, synergistic phototherapy nanoprobes (b-P25@PDA-Ce6 (Mn)) were constructed by coupling chlorin e6 (Ce6) and chelating Mn2+ for simultaneous photodynamic therapy (PDT)/PTT and magnetic resonance (MR) imaging, in which a low-dose laser was used and imaging-guided phototherapy with high efficiency and high safety was achieved. The prepared nanoprobes showed high photothermal conversion efficiency (32.12%), high reactive oxygen generation and excellent MR imaging. In the 4T1 tumor-bearing nude mouse model, the tumors completely disappeared under the combination of PDT/PTT with a low-dose laser but were only partially inhibited by single PDT and single PTT. The current work developed a multifunctional black TiO2-based nanoprobe for enhanced synergistic PDT/PTT and MR imaging, which will be important for the safe and efficient visualized theranostics of cancers.

3.
Artigo em Inglês | MEDLINE | ID: mdl-31976915

RESUMO

Existing multi-label medical image learning tasks generally contain rich relationship information among pathologies such as label co-occurrence and interdependency, which is of great importance for assisting in clinical diagnosis and can be represented as the graph-structured data. However, most state-of-the-art works only focus on regression from the input to the binary labels, failing to make full use of such valuable graph-structured information due to the complexity of graph data. In this paper, we propose a novel label co-occurrence learning framework based on Graph Convolution Networks (GCNs) to explicitly explore the dependencies between pathologies for the multi-label chest X-ray (CXR) image classification task, which we term the "CheXGCN". Specifically, the proposed CheXGCN consists of two modules, i.e., the image feature embedding (IFE) module and label co-occurrence learning (LCL) module. Thanks to the LCL model, the relationship between pathologies is generalized into a set of classifier scores by introducing the word embedding of pathologies and multi-layer graph information propagation. During end-to-end training, it can be flexibly integrated into the IFE module and then adaptively recalibrate multi-label outputs with these scores. Extensive experiments on the ChestX-ray14 and CheXpert datasets have demonstrated the effectiveness of CheXGCN as compared with the state-of-the-art baselines.

4.
Biomaterials ; 232: 119677, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31865193

RESUMO

Conventional radiotherapy has a pivotal role in the treatment of glioblastoma; nevertheless, its clinical utility has been limited by radiation resistance. There is emerging evidence that upregulated heat shock protein A5 (HSPA5) in cancer cells maintains or restores the homeostasis of a cellular microenvironment and results in cancer resistance in various treatments. Therefore, we describe a bioresponsive nanoplatform that can deliver a HSPA5 inhibitor (pifithrin-µ, PES) and radiosensitizer (gold nanosphere, AuNS), to expand the synergistic photothermal therapy and radiotherapy, as well as to monitor the progression of cancer therapy using computer tomography/magnetic resonance imaging. The nanoplatform (PES-Au@PDA, 63.3 ± 3.1 nm) comprises AuNS coated with the photothermal conversion agent polydopamine (PDA) for enhanced radiotherapy and photothermal therapy, as well as PES (loading efficiency of PES approximately 40%), a small molecular inhibitor against HSPA5 to amplify the pro-apoptotic unfolded protein response (UPR). The reported nanoplatform enables hyperthermia-responsive release of PES. Results from in vitro and in vivo studies demonstrate that PES-Au@PDA can specially activate pro-apoptotic UPR cascades, leading to remarkably improved radiotherapy and photothermal therapy efficiencies. Considered together, a versatile theranostic nanosystem is reported for promoting the synergistic radiophotothermal therapy by selectively activating pro-apoptotic UPR cascade pathways.

5.
Front Neurol ; 10: 1201, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31798523

RESUMO

Objectives: To investigate the performance of substate classification of children with benign epilepsy with centrotemporal spikes (BECTS) by granger causality density (GCD) based support vector machine (SVM) model. Methods: Forty-two children with BECTS (21 females, 21 males; mean age, 8.6 ± 1.96 years) were classified into interictal epileptic discharges (IEDs; 11 females, 10 males) and non-IEDs (10 females, 11 males) substates depending on presence of central-temporal spikes or not. GCD was calculated on four metrics, including inflow, outflow, total-flow (inflow + outflow) and int-flow (inflow - outflow) connectivity. SVM classifier was applied to discriminate the two substates. Results: The Rolandic area, caudate, dorsal attention network, visual cortex, language networks, and cerebellum had discriminative effect on distinguishing the two substates. Relative to each of the four GCD metrics, using combined metrics could reach up the classification performance (best value; AUC, 0.928; accuracy rate, 90.83%; sensitivity, 90%; specificity, 95%), especially for the combinations with more than three GCD metrics. Specially, combined the inflow, outflow and int-flow metric received the best classification performance with the highest AUC value, classification accuracy and specificity. Furthermore, the GCD-SVM model received good and stable classification performance across 14 dimension reduced data sets. Conclusions: The GCD-SVM model could be used for BECTS substate classification, which might have the potential to provide a promising model for IEDs detection. This may help assist clinicians for administer drugs and prognosis evaluation.

6.
Transl Androl Urol ; 8(5): 421-431, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31807419

RESUMO

Background: Adherent perinephric fat (APF) is evaluated preoperatively with the Mayo adhesive probability (MAP) scoring system using conventional single-form computed tomography (CT) images. An objective or quantitative indicator for predicting APF is urgently needed for clinical application. Methods: A total of 150 patients with renal tumours who underwent laparoscopic partial nephrectomy (LPN) were retrospectively enrolled and divided into the APF group (n=100) and the non-APF group (n=50) according to surgical results. All patients underwent a renal contrast-enhanced dual-energy CT (DECT) scan. The obtained CT DICOM data were transmitted to the DECT post-processing workstation and adopted virtual non-contrast (VNC), Rho/Z Maps, and Monoenergetic Plus (mono+) modes separately to undergo a multi-parameter analysis. A logistic stepwise investigation was utilized to analyse the related risk factors. The cutoff value was determined by the Youden index. Fifty patients were prospectively enrolled to validate the constructed model. The area under the curve (AUC), sensitivity, specificity and accuracy of the model were calculated. Results: The study demonstrated that age, sex, body mass index (BMI), smoking status, tumour diameter, exophytic status, degree of malignancy and posterior perinephric fat thickness were related to the occurrence of APF (P<0.05). Model 1 was selected with the contrast material (CM) parameter (cutoff point 0.5), model 2 was selected with the effective atomic number (Zeff) parameter (cutoff point 6.5), and model 3 was selected with the slope K (K) parameter (cutoff point -0.95). The AUC, sensitivity, specificity and accuracy of model 1 were 0.94, 0.94, 0.93 and 0.94, respectively; for model 2, they were 0.94, 0.93, 0.93 and 0.96, respectively; and for model 3, they were 0.92, 0.92, 0.93 and 0.92, respectively. Conclusions: Multi-mode and multi-parameter models of DECT can effectively be used to predict the occurrence of APF.

7.
ACS Appl Mater Interfaces ; 11(50): 46626-46636, 2019 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-31751121

RESUMO

Programmed cell death ligand 1 (PD-L1) blockade has achieved great success in cancer immunotherapy; however, the response of triple-negative breast cancer (TNBC) to PD-L1 antibodies is limited. To address this challenge, we use the bromodomain and extra-terminal inhibitor JQ1 to down-regulate the expression of PD-L1 and thus elicit the immune response to TNBC instead of using antibodies to block PD-L1. JQ1 also inhibits the growth of TNBC as a targeted therapeutic agent by inhibiting the BRD4-c-MYC axis. The polydopamine nanoparticles (PDMNs) are introduced as a biodegradable and adaptable platform to load JQ1 and induce photothermal therapy (PTT) as another synergistic therapeutic modality. Because the JQ1-loaded PDMNs (PDMN-JQ1) are self-degradable and release JQ1 continuously, this synergistic treatment can lead to remarkable activation of cytotoxic T lymphocytes and induce a strong immune-memory effect to protect mice from tumor re-challenge. Taken together, our study demonstrates a compact and simple nanoplatform for triple therapy, including targeted therapy, PTT, and immunotherapy, for TNBC treatment.

8.
Sci Rep ; 9(1): 15834, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31676819

RESUMO

Electric switching of non-polar bulk crystals is shown to occur when domain walls are polar in ferroelastic materials and when rough surfaces with steps on an atomic scale promote domain switching. All domains emerging from surface nuclei possess polar domain walls. The progression of domains is then driven by the interaction of the electric field with the polarity of domain boundaries. In contrast, smooth surfaces with higher activation barriers prohibit effective domain nucleation. We demonstrate the existence of an electrically driven ferroelectric hysteresis loop in a non-ferroelectric, ferroelastic bulk material.

9.
Cancer Manag Res ; 11: 7825-7834, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31695487

RESUMO

Purpose: We aimed to assess the classification performance of a computed tomography (CT)-based radiomic signature for discriminating invasive and non-invasive lung adenocarcinoma. Patients and Methods: A total of 192 patients (training cohort, n=116; validation cohort, n=76) with pathologically confirmed lung adenocarcinoma were retrospectively enrolled in the present study. Radiomic features were extracted from preoperative unenhanced chest CT images to build a radiomic signature. Predictive performance of the radiomic signature were evaluated using an intra-cross validation cohort. Diagnostic performance of the radiomic signature was assessed via receiver operating characteristic (ROC) analysis. Results: The radiomic signature consisted of 14 selected features and demonstrated good discrimination performance between invasive and non-invasive adenocarcinoma. The area under the ROC curve (AUC) for the training cohort was 0.83 (sensitivity, 0.84 ; specificity, 0.78; accuracy, 0.82), while that for the validation cohort was 0.77 (sensitivity, 0.94; specificity, 0.52 ; accuracy, 0.82). Conclusion: The CT-based radiomic signature exhibited good classification performance for discriminating invasive and non-invasive lung adenocarcinoma, and may represent a valuable biomarker for determining therapeutic strategies in this patient population.

10.
Artigo em Inglês | MEDLINE | ID: mdl-31715576

RESUMO

Traditional clinical experiences have shown the benefit of lesion location attention for improving clinical diagnosis tasks. Inspired by this point of interest, in this paper we propose a novel lesion location attention guided network named LLAGnet to focus on the discriminative features from lesion locations for multi-label thoracic disease classification in chest X-rays (CXRs). By revealing the equivalence of the region-level attention (RLA) and channel-level attention (CLA), we find that the RLA is available as priors for object localization while the CLA implicitly provides high weights to the attractive channels, which both enable lesion location attention excitation. To integrate the advantages from both mechanisms, the proposed LLAGnet is structured with two corresponding attention modules, i.e., the RLA and CLA modules. Specifically, the RLA module consists of the global and local branches. And the weakly supervised attention mechanism embedded in the global branch can obtain visual regions of lesion locations by back-propagating gradients. Then the optimal attention region is amplified and applied to the local branch to provide more fine-grained features for the image classification. Finally, the CLA module adaptively enhances the weights of channel-wise features from the lesion locations by modeling interdependencies among channels. Extensive experiments on the ChestX-ray14 dataset clearly substantiate the effectiveness of LLAGnet as compared with the state-of-the-art baselines.

11.
Front Oncol ; 9: 908, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31620365

RESUMO

Purpose: To investigate the correlation between 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters and clinicopathological factors in pathological subtypes of invasive lung adenocarcinoma and prognosis. Patients and Methods: Metabolic parameters and clinicopathological factors from 176 consecutive patients with invasive lung adenocarcinoma between August 2008 and August 2016 who underwent 18F-FDG PET/CT examination were retrospectively analyzed. Invasive lung adenocarcinoma was divided into five pathological subtypes:lepidic predominant adenocarcinoma (LPA), acinar predominant adenocarcinoma (APA), papillary predominant adenocarcinoma (PPA), solid predominant adenocarcinoma (SPA), and micropapillary predominant adenocarcinoma (MPA). The differences in metabolic parameters [maximal standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), and metabolic tumor volume (MTV)] and tumor diameter for different pathological subtypes were analyzed. Patients were divided into two groups according to their prognosis: good prognosis group (LPA, APA, PPA) and poor prognosis group (SPA, MPA). Logistic regression was used to filter predictors and construct a predictive model, and areas under the receiver operating curve (AUC) were calculated. Cox regression analysis was performed on prognostic factors. Results: 82 (46.6%) females and 94 (53.4%) males of patients with invasive lung adenocarcinoma were enrolled in this study. Metabolic parameters and tumor diameter of different pathological subtype had statistically significant (P < 0.05). The predictive model constructed using independent predictors (Distant metastasis, Ki-67, and SUVmax) had good classification performance for both groups. The AUC for SUVmax was 0.694 and combined with clinicopathological factors were 0.745. Cox regression analysis revealed that Stage, TTF-1, MTV, and pathological subtype were independent risk factors for patient prognosis. The hazard ratio (HR) of the poor prognosis group was 1.948 (95% CI 1.042-3.641) times the good prognosis group. The mean survival times of good and poor prognosis group were 50.2621 (95% CI 47.818-52.706) and 35.8214 (95% CI 27.483-44.159) months, respectively, while the median survival time was 47.00 (95% CI 45.000-50.000) and 31.50 (95% CI 23.000-49.000) months, respectively. Conclusion: PET/CT metabolic parameters combined with clinicopathological factors had good classification performance for the different pathological subtypes, which may provide a reference for treatment strategies and prognosis evaluation of patients.

12.
Biomater Sci ; 7(11): 4790-4799, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31524909

RESUMO

The size effect of mesoporous organosilica nanoparticles (MONs) on tumor penetration and accumulation remains poorly understood, which strongly affects the tumor therapeutic efficacy. Herein, four different-sized thioether-bridged MONs (20, 40, 60, and 100 nm) are synthesized; all the MONs have a spherical morphology, excellent dispersity, similar surface charge, uniform mesopores (3.2-3.5 nm), and large surface areas (709-1353 m2·g-1). Hematology and histopathology analyses demonstrate that the four MONs do not cause pathological changes in mice even at a dose of 20 mg kg-1 for 30 d. The penetration depth of the MONs for multicellular spheroids (MCSs) decreases with increasing particle sizes, and the 20 nm MONs are uniformly distributed in the MCSs at a depth of 60 µm, while the larger MONs are mainly restricted to peripheral areas. In vivo experiments show that the 40 nm MONs possess the longest mean residence times, leading to their highest accumulation in blood and tumors. However, the 20 nm MONs reach the deepest penetration depth of 1230 µm for xenograft tumors. In contrast, the penetration depths of 40, 60, and 100 nm MONs are 783, 105, and 40 µm, respectively. Overall, this work provides an important guideline for the rational design of nanoplatforms for tumor treatment.

13.
Wideochir Inne Tech Maloinwazyjne ; 14(3): 401-407, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31534570

RESUMO

Introduction: Severe acute pancreatitis (SAP) has a high mortality rate of 20% to 30%, with death often resulting from hemorrhage. Aim: To investigate the role of digital subtraction angiography (DSA) and endovascular embolization in the management of arterial bleeding in SAP patients. Material and methods: Seventy-six patients with SAP admitted to our hospital between January 2010 and May 2016 underwent DSA. DSA revealed arterial bleeding in 22 of these patients, who were treated with transcatheter endovascular embolization with coils and/or gelfoam particles. Patient demographics, angiographic features of vascular abnormalities, and outcomes of embolization were assessed. Results: Arterial bleeding was the most common vascular abnormality (22/76 patients; 28.9%). DSA enabled the identification of 27 bleeding arteries in 22 patients. The splenic artery was the most commonly affected vessel (11/27; 40.7%). Among the 27 arteries treated with endovascular embolization, successful hemostasis was achieved in 96.3% (26/27). Two patients developed major complications (hepatic and splenic abscess). These patients were treated with abdominal catheter drainage and anti-infection measures and ultimately recovered. The mean interval between initial onset of SAP and angiographic diagnosis of arterial bleeding was 56 days. Rebleeding was diagnosed in 5 patients (5/22; 22.7%) during repeat angiography, with bleeding from new sites in four of these patients. The mean interval between successive angiography treatments was 38 days. Conclusions: Endovascular embolization is a safe and effective method to localize bleeding arteries and achieve complete hemostasis in patients with SAP-related arterial bleeding.

14.
Quant Imaging Med Surg ; 9(8): 1421-1428, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31559171

RESUMO

Background: Adherent perinephric fat (APF) is evaluated preoperatively with the Mayo adhesive probability (MAP) scoring system using conventional single form computed tomography (CT) images. An objective or quantitative indicator for predicting APF is urgently needed for clinical application. Methods: Data obtained from 150 renal tumor patients with partial nephrectomy (PN) were used in the present study. Patients were divided into two groups based on the surgical results: an APF group (n=100) and a non-APF group (n=50). All patients had renal contrast-enhanced dual-energy CT (DECT) scan, and the data were brought into a post-processing workstation. Monoenergetic plus mode was adopted to analyze the spectrum curve of the region of interest (ROI). Logistic stepwise relapse investigation was utilized to analyze the related risk factors. The maximum Youden index was taken as the cut-off value. The sensitivity, specificity, accuracy, and 95% CI of the model were calculated. Results: APF is related to patients' clinical characteristics of age, gender, BMI, smoking, tumor diameter, exophytic, and benign or malignant nature of the renal masses (P<0.05). The shape of the curve of ROI1 in the APF group was different from that of the ROI4 in the non-APF group, and the curve slope of K1 (-0.21±0.47) was different from that of K4 (-1.30±0.14) (P<0.001). Statistical analysis showed that the slope K was solely retained in the model index. The best cut-off point for the K value was -0.95. The AUC of the cut-off point was 0.97 (95% CI: 0.96-0.99). Conclusions: The DECT spectrum curve performed well in predicting APF, and the curve slope K can be used as an objective quantitative indicator.

15.
Artigo em Inglês | MEDLINE | ID: mdl-31502989

RESUMO

Group convolution is widely used in many mobile networks to remove the filter's redundancy from the channel extent. In order to further reduce the redundancy of group convolution, this article proposes a novel repeated group convolutional (RGC) kernel, which has M primary groups, and each primary group includes N tiny groups. In every primary group, the same convolutional kernel is repeated in all the tiny groups. The RGC filter is the first kernel to remove the redundancy from group extent. Based on RGC, a sparse RGC (SRGC) kernel is also introduced in this article, and its corresponding network is called SRGC neural networks (SRGC-Net). The SRGC kernel is the summation of RGC kernel and pointwise group convolutional (PGC) kernel. The number of PGC's groups is M. Accordingly, in each primary group, besides the center locations in all channels, the values of parameters located in other N-1 tiny groups are all zero. Therefore, SRGC can significantly reduce the parameters. Moreover, it can also effectively retrieve spatial and channel-difference features by utilizing RGC and PGC to preserve the richness of produced features. Comparative experiments were performed on the benchmark classification data sets. Compared with the traditional popular networks, SRGC-Nets can perform better with timely reducing the model size and computational complexity. Furthermore, it can also achieve better performances than other latest state-of-the-art mobile networks on most of the databases and effectively decrease the test and training runtime.

16.
Front Oncol ; 9: 589, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31380265

RESUMO

Purpose: This study assessed the ability of metabolic parameters from 18Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and clinicopathological data to predict epidermal growth factor receptor (EGFR) expression/mutation status in patients with lung adenocarcinoma and to develop a prognostic model based on differences in EGFR expression status, to enable individualized targeted molecular therapy. Patients and Methods: Metabolic parameters and clinicopathological data from 200 patients diagnosed with lung adenocarcinoma between July 2009 and November 2016, who underwent 18F-FDG PET/CT and EGFR mutation testing, were retrospectively evaluated. Multivariate logistic regression was applied to significant variables to establish a prediction model for EGFR mutation status. Overall survival for both mutant and wild-type EGFR was analyzed to establish a multifactor Cox regression model. Results: Of the 200 patients, 115 (58%) exhibited EGFR mutations and 85 (42%) were wild-type. Among selected metabolic parameters, metabolic tumor volume (MTV) demonstrated a significant difference between wild-type and mutant EGFR mutation status, with an area under the receiver operating characteristic curve (AUC) of 0.60, which increased to 0.70 after clinical data (smoking status) were combined. Survival analysis of wild-type and mutant EGFR yielded mean survival times of 34.451 (95% CI 28.654-40.249) and 53.714 (95% CI 44.331-63.098) months, respectively. Multivariate Cox regression revealed that mutation type, tumor stage, and thyroid transcription factor-1 (TTF-1) expression status were the main factors influencing patient prognosis. The hazard ratio for mutant EGFR was 0.511 (95% CI 0.303-0.862) times that of wild-type, and the risk of death was lower for mutant EGFR than for wild-type. The risk of death was lower in TTF-1-positive than in TTF-1-negative patients. Conclusion: 18F-FDG PET/CT metabolic parameters combined with clinicopathological data demonstrated moderate diagnostic efficacy in predicting EGFR mutation status and were associated with prognosis in mutant and wild-type EGFR non-small-cell lung cancer (NSCLC), thus providing a reference for individualized targeted molecular therapy.

17.
Eur J Med Chem ; 180: 648-655, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31352245

RESUMO

Herein, synthesis and biological evaluation of fourteen moxifloxacin-acetyl-1,2,3-1H-triazole-methylene-isatin hybrids as potential anti-tubercular agents against both drug-susceptible (MTB H37Rv), rifampicin-resistant and multidrug-resistant Mycobacterium tuberculosis strains were reported, and cytotoxicity towards VERO cells as well as inhibitory activity against MTB DNA gyrase were also discussed in this paper. The structure-activity relationship and structure-cytotoxicity relationship demonstrated that substituents on the C-3 and C-5/C-7 positions of isatin framework were closely related with the anti-mycobacterial activity and cytotoxicity. The most active hybrids 8h and 8l (MIC: 0.12-0.5 µg/mL) showed excellent activity which was no inferior to the parent moxifloxacin against the tested drug-susceptible, rifampicin-resistant and multidrug-resistant Mycobacterium tuberculosis strains, demonstrating their potential application as novel anti-tubercular candidates.


Assuntos
Antituberculosos/farmacologia , Farmacorresistência Bacteriana/efeitos dos fármacos , Isatina/farmacologia , Moxifloxacina/farmacologia , Mycobacterium tuberculosis/efeitos dos fármacos , Triazóis/farmacologia , Animais , Antituberculosos/síntese química , Antituberculosos/química , Células CHO , Sobrevivência Celular/efeitos dos fármacos , Cricetulus , Relação Dose-Resposta a Droga , Feminino , Isatina/química , Camundongos , Camundongos Endogâmicos ICR , Testes de Sensibilidade Microbiana , Estrutura Molecular , Moxifloxacina/química , Relação Estrutura-Atividade , Triazóis/química , Células Vero
18.
Brain Behav ; 9(8): e01361, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31313505

RESUMO

PURPOSE: To analyze magnetic resonance imaging (MRI) findings and clinical diagnosis and treatment data relating to Angiostrongylus cantonensis infection to gain insight into the disease. MATERIALS AND METHODS: We retrospectively analyzed the epidemiology, clinical manifestations, diagnosis and treatment data, imaging manifestations, and outcomes of 27 patients who were clinically diagnosed with angiostrongyliasis and who underwent contrast-enhanced brain MRI. RESULTS: Patients with A. cantonensis infection had a history of eating raw mollusks in the endemic area, and they mainly presented with dizziness and headache of varying degrees and vomiting (n = 7). Laboratory examinations revealed increased peripheral blood and cerebrospinal fluid (CSF) eosinophils, as well as increased CSF protein levels. Brain MRI findings mainly included eosinophilic meningitis, whereas linear or nodular enhancement of the pia mater was observed in enhanced T1-weighted and fluid-attenuated inversion recovery images, accompanied by encephalitis or vasculitis. Meningitis manifested as multiple, thickened flow voids around the meninges, and contrast-enhanced scans showed substantial enhancement in intracranial dilated and hyperplastic blood vessels. CONCLUSION: The possibility of A. cantonensis infection should be considered in the effective use of albendazole or mebendazole as a treatment. Combining clinical history with laboratory examination is helpful in diagnosing A. cantonensis infection. A final definite diagnosis can be confirmed by detecting larvae in the CSF. The administration of corticosteroids during pathogen therapy can substantially reduce the therapeutic response.

19.
J Affect Disord ; 257: 632-639, 2019 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-31357160

RESUMO

BACKGROUND: Post-traumatic stress disorder (PTSD) is associated with disruption of the brain network topology; however, little is known about the topological changes and sex effects in PTSD patients following a unique trauma, the loss of an only child, in China. METHODS: Fifty-one lost-only-child parents with PTSD, 93 lost-only-child non-PTSD parents (NPTSD), and 50 healthy subjects underwent resting-state functional MRI. The whole-brain functional network was constructed by thresholding partial correlation matrices of 90 brain regions. Group differences in the topological properties, the diagnosis-by-sex interaction, and the relationships between topological metrics and clinical variables were investigated. RESULTS: Compared with healthy subjects, PTSD and NPTSD groups exhibited significantly shorter path lengths and higher nodal centralities in many brain regions across sexes; however, no significant difference was found between the PTSD and NPTSD groups. Additionally, the global topological metrics did not show any sex difference, whereas the nodal centralities in the left insula, right inferior frontal gyrus, and right posterior cingulate cortex differed significantly only in women, and the nodal centralities in the bilateral anterior cingulate cortices and left hippocampus were significantly different only in men. Furthermore, the nodal centralities of the right parahippocampus demonstrated significant diagnosis-by-sex interaction. LIMITATION: Cross-sectional design of this study could not demonstrate the causality. CONCLUSIONS: The parents who lost their only child exhibited a shift toward randomization and significant nodal topological alterations independent of PTSD effects. Additionally, sex differences were observed primarily in the topological properties at the nodal level, which may indicate a neurobiological contribution to the greater incidence of PTSD in females.

20.
IEEE Trans Cybern ; 2019 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-31170087

RESUMO

Multiview learning has been widely studied in various fields and achieved outstanding performances in comparison to many single-view-based approaches. In this paper, a novel multiview learning method based on the Gaussian process latent variable model (GPLVM) is proposed. In contrast to existing GPLVM methods which only assume that there are transformations from the latent variable to the multiple observed inputs, our proposed method simultaneously takes a back constraint into account, encoding multiple observations to the latent variable by enjoying the Gaussian process (GP) prior. Particularly, to overcome the difficulty of the covariance matrix calculation in the encoder, a linear projection is designed to map different observations to a consistent subspace first. The obtained variable in this subspace is then projected to the latent variable in the manifold space with the GP prior. Furthermore, different from most GPLVM methods which strongly assume that the covariance matrices follow a certain kernel function, for example, radial basis function (RBF), we introduce a multikernel strategy to design the covariance matrix, being more reasonable and adaptive for the data representation. In order to apply the presented approach to the classification, a discriminative prior is also embedded to the learned latent variables to encourage samples belonging to the same category to be close and those belonging to different categories to be far. Experimental results on three real-world databases substantiate the effectiveness and superiority of the proposed method compared with state-of-the-art approaches.

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