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1.
Artigo em Inglês | MEDLINE | ID: mdl-31944981

RESUMO

ecent studies have shown that balance performance assessment based on artificial intelligence (AI) is feasible. However, balance control is very complex and requires different subsystems to participate, which have not been evaluated individually yet. Furthermore, these studies only classified individual's balance performance across limited grades. Therefore, in this study we attempted to implement AI to precisely evaluate different types of balance control subsystems (BCSes). First, a total of 224 commonly used and newly developed features were extracted from the center of pressure (CoP) data for each participant, respectively. Then, regressors were employed in order to map these features to the evaluation scores given by physical therapists, which include the total score in Mini-Balance-Evaluation-Systems-Tests (Mini-BESTest) and its sub-scores on BCSes, namely anticipatory postural adjustments (APA), reactive postural control (RPC), sensory orientation (SO), and dynamic gait (DG). Their scoring ranges should be 0-28, 0-6, 0-6, 0-6, and 0-10, respectively. The results show that their minimum mean absolute errors from AI estimation reach up to 2.658, 0.827, 0.970, 0.642, and 0.98, respectively. In sum, our study is a preliminary study for assessing BCSes based on AI, which shows its possibility to be used in the clinics in the future.

2.
IEEE Trans Neural Syst Rehabil Eng ; 28(1): 181-190, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31751278

RESUMO

Analysis of joint motion data (AJMD) by Kinect, such as velocity, has been widely used in many research fields, many of which focused on how one joint moves with another, namely bivariate AJMD. However, these studies might not accurately reflect the motor symptoms in patients. The human body can be divided into six widely accepted parts (head, trunk and four limbs), which are interrelated and interact with each other. Therefore, in this study we attempted to investigate how the major joints of one body part move with the ones in another body part, namely multivariate AJMD. For method illustration, the motion data of sit-to-stand-to-sit for healthy participants and people with Parkinson disease (PD) were employed. Four types of multivariate AJMD were investigated by eigenspace-maximal-information-canonical-correlation-analysis, which obtained maximal- information-eigen-coefficients (MIECes), the parameters for quantifying the correlation between two sets of joints located in two different body parts. The results show that healthy participants have significantly higher MIECes than the PD patients (p-value < 0.0001). Furthermore, the area under the receiver operating characteristic curve value for the classification between healthy participants and PD patients reaches up to 1.00. In conclusion, we demonstrated the possibility of using multivariate AJMD for motion feature extraction, which may be helpful for medical research and engineering.

3.
Colloids Surf B Biointerfaces ; : 110653, 2019 Nov 21.
Artigo em Inglês | MEDLINE | ID: mdl-31787458

RESUMO

Chlorhexidine (CHX) is a widely used antiseptic in various infection control practices. In this work, we have developed biodegradable mesoporous organosilica nanoparticles (MONs) through a one-pot synthesis by employing CHX as a bifunctional agent that not any acts as a cationic template to form the structure of mesopores but also serves as a broad-spectrum antiseptic. The resulting CHX@MONs exhibit a relatively high CHX content and glutathione (GSH)-responsive release of CHX via a matrix-degradation-controlled mechanism, leading to comparable antibacterial effects with CHX on both Escherichia coli and Staphylococcus aureus. Furthermore, the effective antibacterial concentration of CHX@MONs shows less cytotoxicity toward normal cells. Our findings will help increase the use of CHX as an antiseptic agent, especially for responsive drug release upon bacterial infection.

4.
Mult Scler Relat Disord ; 36: 101395, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31521916

RESUMO

BACKGROUND: Current studies suggested discrepancies on the correlations between multiple sclerosis (MS) and blood levels of homocysteine (Hcy), vitamin B12 (VB12), and folate. We performed a case-control study and meta-analysis to help resolve the controversy of these lab values in Chinese patients with MS. METHODS: We recruited 80 Chinese MS patients, 86 age/sex matched neurological controls (patients with peripheral vertigo or sleep disorders), and 80 age- and sex-matched healthy controls. Serum Hcy levels were measured using flourimetric high-performance liquid chromatography, serum levels of VB12 and folate using immune assay. A literature search of PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure, Wanfang, and SinoMed was conducted for case-control studies with pure Chinese populations published up to March 16, 2019. The effective size was estimated by the pooled standardized mean difference (SMD) and associated 95% confidence interval (CI). RESULTS: The case-control study results suggest higher Hcy levels (mean ± SD) and frequency of hyperhomocysteinemia in the Chinese MS cases than control groups (all p < 0.001), lower for VB12 levels (mean ± SD, p = 0.043 or 0.039). No significant difference was observed for levels of folate (mean ± SD, both p > 0.05), and for frequency of folate or VB12 deficiency (all p > 0.05). Analysis of pooled SMDs and 95% CIs suggested increased Hcy levels in Chinese MS patients (SMD: 2.31, 95% CI: 1.33-3.28, p < 0.001), and in relapsing or remitting cases relative to controls (SMD: 0.94 or 0.85, 95% CI: 0.49-1.39 or 0.35-1.34, both p < 0.001). The meta-analysis results also suggested reduced VB12 levels in Chinese MS patients (SMD: -0.30, 95% CI: -0.46-0.14, p < 0.001), and in relapsing MS patients compared to controls (SMD: -0.31, 95% CI: -0.47-0.15, p < 0.001), while no statistical difference for cases in remission. No significant difference was observed for levels folate in all comparisons. CONCLUSION: Patients with MS tend to have increased blood Hcy levels compared to controls. MS patients of Chinese origin and those in relapse may have decreased levels of VB12. Hcy and VB12 may contribute to pathogenesis of the disease, and VB12 may correlate with MS relapse.

5.
Methods Mol Biol ; 1993: 217-226, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31148090

RESUMO

The success of tissue engineering hinges on the rapid and sufficient vascularization of the neotissue. For efficient vascular network formation within three-dimensional (3D) constructs, biomaterial scaffolds that can support survival of endothelial cells as well as formation and maturation of a capillary network in vivo are highly sought after. Here, we outline a method to biofabricate 3D porous collagen scaffolds that can support extrinsic and intrinsic vascularization using two different in vivo animal models-the mouse subcutaneous implant model (extrinsic vascularization, capillary growth within the scaffold originating from host tissues outside the scaffold) and the rat tissue engineering chamber model (intrinsic vascularization, capillary growth within the scaffold derived from a centrally positioned vascular pedicle). These in vivo vascular tissue engineering approaches hold a great promise for the generation of clinically viable vascularized constructs. Moreover, the 3D collagen scaffolds can also be employed for 3D cell culture and for in vivo delivery of growth factors and cells.

6.
Front Oncol ; 9: 354, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31134153

RESUMO

Background: Triple-negative breast cancer (TNBC) accounts for 12-20% of all breast cancers. Diagnosis of TNBC is sometimes quite difficult based on morphological assessment and immunohistochemistry alone, particularly in the metastatic setting with no prior history of breast cancer. Methods: Molecular profiling is a promising diagnostic approach that has the potential to provide an objective classification of metastatic tumors with unknown primary. In this study, performance of a novel 90-gene expression signature for determination of the site of tumor origin was evaluated in 115 TNBC samples. For each specimen, expression profiles of the 90 tumor-specific genes were analyzed, and similarity scores were obtained for each of the 21 tumor types on the test panel. Predicted tumor type was compared to the reference diagnosis to calculate accuracy. Furthermore, rank product analysis was performed to identify genes that were differentially expressed between TNBC and other tumor types. Results: Analysis of the 90-gene expression signature resulted in an overall 97.4% (112/115, 95% CI: 0.92-0.99) agreement with the reference diagnosis. Among all specimens, the signature correctly classified 97.6% of TNBC from the primary site (41/42) and lymph node metastasis (41/42) and 96.8% of distant metastatic tumors (30/31). Furthermore, a list of genes, including AZGP1, KRT19, and PIGR, was identified as differentially expressed between TNBC and other tumor types, suggesting their potential use as discriminatory markers. Conclusion: Our results demonstrate excellent performance of a 90-gene expression signature for identification of tumor origin in a cohort of both primary and metastatic TNBC samples. These findings show promise for use of this novel molecular assay to aid in differential diagnosis of TNBC, particularly in the metastatic setting.

7.
J Med Internet Res ; 21(3): e11990, 2019 03 11.
Artigo em Inglês | MEDLINE | ID: mdl-30855231

RESUMO

BACKGROUND: Improper dosing of medications such as insulin can cause hypoglycemic episodes, which may lead to severe morbidity or even death. Although secure messaging was designed for exchanging nonurgent messages, patients sometimes report hypoglycemia events through secure messaging. Detecting these patient-reported adverse events may help alert clinical teams and enable early corrective actions to improve patient safety. OBJECTIVE: We aimed to develop a natural language processing system, called HypoDetect (Hypoglycemia Detector), to automatically identify hypoglycemia incidents reported in patients' secure messages. METHODS: An expert in public health annotated 3000 secure message threads between patients with diabetes and US Department of Veterans Affairs clinical teams as containing patient-reported hypoglycemia incidents or not. A physician independently annotated 100 threads randomly selected from this dataset to determine interannotator agreement. We used this dataset to develop and evaluate HypoDetect. HypoDetect incorporates 3 machine learning algorithms widely used for text classification: linear support vector machines, random forest, and logistic regression. We explored different learning features, including new knowledge-driven features. Because only 114 (3.80%) messages were annotated as positive, we investigated cost-sensitive learning and oversampling methods to mitigate the challenge of imbalanced data. RESULTS: The interannotator agreement was Cohen kappa=.976. Using cross-validation, logistic regression with cost-sensitive learning achieved the best performance (area under the receiver operating characteristic curve=0.954, sensitivity=0.693, specificity 0.974, F1 score=0.590). Cost-sensitive learning and the ensembled synthetic minority oversampling technique improved the sensitivity of the baseline systems substantially (by 0.123 to 0.728 absolute gains). Our results show that a variety of features contributed to the best performance of HypoDetect. CONCLUSIONS: Despite the challenge of data imbalance, HypoDetect achieved promising results for the task of detecting hypoglycemia incidents from secure messages. The system has a great potential to facilitate early detection and treatment of hypoglycemia.

8.
Chem Biol Drug Des ; 93(3): 232-241, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30251407

RESUMO

Fifty-eight quinazoline-based compounds were designed and synthesized based on the structural optimizations from the lead compound 23bb in an attempt to search for more potent dual HDAC1 and HDAC6 inhibitors. Among them, 32c (HDAC1, IC50  = 31.10 ± 0.37 nM; HDAC6, IC50  = 16.15 ± 0.62 nM) and 32d (HDAC1, IC50  = 37.00 ± 0.24 nM; HDAC6, IC50  = 35.00 ± 0.71 nM) were not only identified as potent dual-acting HDAC1 and HDAC6 inhibitors with over 10-fold selectivity to the other HDACs, but also displayed activities in tubulin acetylation and histone H3 acetylation induction. Importantly, both of them displayed strong antiproliferative activities against various tumor cell lines in vitro with IC50 values less than 40 nM, especially for hematologic tumors cells (U266 and RPMI8226, IC50  < 1 nM), which were even better than 23bb and SAHA. Furthermore, 32c showed a significant tumor growth inhibition (antitumor rate = 63.98%, p < 0.05) in the resistant MCF-7/ADR xenograft model without any obvious body weight changes and abnormal behaviors. Our findings validate that 32c is a potent dual inhibitor of HDAC1/6 that can be an efficacious treatment for breast cancer with Adriamycin resistance.


Assuntos
Antineoplásicos/síntese química , Desenho de Drogas , Histona Desacetilase 1/antagonistas & inibidores , Desacetilase 6 de Histona/antagonistas & inibidores , Quinazolinas/química , Acetilação/efeitos dos fármacos , Animais , Antineoplásicos/química , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Histona Desacetilase 1/metabolismo , Desacetilase 6 de Histona/metabolismo , Humanos , Isoenzimas/antagonistas & inibidores , Isoenzimas/metabolismo , Camundongos , Neoplasias , Quinazolinas/metabolismo , Quinazolinas/farmacologia , Quinazolinas/uso terapêutico , Relação Estrutura-Atividade , Transplante Heterólogo , Tubulina (Proteína)/metabolismo
9.
Prog Retin Eye Res ; 68: 31-53, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-30170104

RESUMO

Many clinical trials using gene therapy have shown significant therapeutic benefits and exceptional safety records. Increasing evidence is verifying the long sought-after promise that gene therapy will genetically 'cure' some severely disabling diseases. In particular, the first gene therapy bioproduct for RPE65-associated Leber's congenital amaurosis, which was approved by the US Food and Drug Administration in 2017, has provided tremendous encouragement to the field of gene therapy. Recent developments in genome editing technologies have significantly advanced our capability to precisely engineer genomes in eukaryotic cells. Programmable nucleases, particularly the CRISPR/Cas system, have been widely adopted in studies applying genome engineering therapy to ocular diseases with the hope of managing these diseases. In this review article, we summarize the current approaches that have been developed in the area of gene therapy for ocular disease. We also discuss the challenges and opportunities facing gene therapy for ocular diseases, as well as its prospects.


Assuntos
Oftalmopatias/terapia , Terapia Genética/métodos , Transtornos da Visão/terapia , Cegueira/terapia , Oftalmopatias/genética , Edição de Genes/métodos , Vetores Genéticos , Humanos
10.
Conf Proc IEEE Eng Med Biol Soc ; 2018: 4965-4968, 2018 07.
Artigo em Inglês | MEDLINE | ID: mdl-30441456

RESUMO

Recent advancement in technology has brought about increase in the application areas of wearable electroencephalographic devices. In that, new types of electrodes take place, and particular attention is needed to ensure the required quality of obtained signals. In this study, we evaluate electrode-skin impedance and signal quality for several kinds of electrodes when used in conditions typical for wearable devices. Results suggest that active dry electrode coated with gold alloy is superior while it was challenging to obtain appropriate signal quality when using passive dry electrodes. We also demonstrate electrode-skin impedance measurement using the analog frontend ADS1299, which is suitable for implementation in wearable devices.


Assuntos
Eletroencefalografia , Dispositivos Eletrônicos Vestíveis , Impedância Elétrica , Eletrodos , Pele
11.
Int J Mol Sci ; 19(10)2018 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-30274378

RESUMO

Choroidal neovascularization (CNV) is a key pathological feature of several leading causes of vision loss including neovascular age-related macular degeneration. Here, we show that a calreticulin anti-angiogenic domain (CAD)-like peptide 27, CAD27, inhibited in vitro angiogenic activities, including tube formation, migration of endothelial cells, and vascular sprouting from rat aortic ring explants. In a rat model of laser-induced CNV, we demonstrate that intravitreal injection of CAD27 significantly attenuated the formation of CNV lesions as measured via fundus fluorescein angiography and choroid flat-mounts (19.5% and 22.4% reductions at 10 µg and 20 µg of CAD27 injected, respectively). Similarly, the reduction of CNV lesions was observed in rats that had received topical applications of CAD27 (choroid flat-mounts: 17.9% and 32.5% reductions at 10 µg/mL and 20 µg/mL of CAD27 instilled, respectively). Retinal function was unaffected, as measured using electroretinography in both groups receiving interareal injection or topical applications of CAD27 for at least fourteen days. These findings show that CAD27 can be used as a potential therapeutic alternative for targeting CNV in diseases such as neovascular age-related macular degeneration.


Assuntos
Calreticulina/química , Neovascularização de Coroide/tratamento farmacológico , Peptídeos/uso terapêutico , Administração Tópica , Sequência de Aminoácidos , Inibidores da Angiogênese/farmacologia , Inibidores da Angiogênese/uso terapêutico , Animais , Aorta/patologia , Neovascularização de Coroide/patologia , Neovascularização de Coroide/fisiopatologia , Angiofluoresceinografia , Células Endoteliais da Veia Umbilical Humana/efeitos dos fármacos , Células Endoteliais da Veia Umbilical Humana/metabolismo , Humanos , Injeções Intravítreas , Lasers , Masculino , Neovascularização Fisiológica/efeitos dos fármacos , Peptídeos/administração & dosagem , Peptídeos/química , Peptídeos/farmacologia , Domínios Proteicos , Ratos Sprague-Dawley , Retina/efeitos dos fármacos , Retina/patologia , Retina/fisiopatologia
12.
J Med Internet Res ; 20(1): e26, 2018 01 22.
Artigo em Inglês | MEDLINE | ID: mdl-29358159

RESUMO

BACKGROUND: Many health care systems now allow patients to access their electronic health record (EHR) notes online through patient portals. Medical jargon in EHR notes can confuse patients, which may interfere with potential benefits of patient access to EHR notes. OBJECTIVE: The aim of this study was to develop and evaluate the usability and content quality of NoteAid, a Web-based natural language processing system that links medical terms in EHR notes to lay definitions, that is, definitions easily understood by lay people. METHODS: NoteAid incorporates two core components: CoDeMed, a lexical resource of lay definitions for medical terms, and MedLink, a computational unit that links medical terms to lay definitions. We developed innovative computational methods, including an adapted distant supervision algorithm to prioritize medical terms important for EHR comprehension to facilitate the effort of building CoDeMed. Ten physician domain experts evaluated the user interface and content quality of NoteAid. The evaluation protocol included a cognitive walkthrough session and a postsession questionnaire. Physician feedback sessions were audio-recorded. We used standard content analysis methods to analyze qualitative data from these sessions. RESULTS: Physician feedback was mixed. Positive feedback on NoteAid included (1) Easy to use, (2) Good visual display, (3) Satisfactory system speed, and (4) Adequate lay definitions. Opportunities for improvement arising from evaluation sessions and feedback included (1) improving the display of definitions for partially matched terms, (2) including more medical terms in CoDeMed, (3) improving the handling of terms whose definitions vary depending on different contexts, and (4) standardizing the scope of definitions for medicines. On the basis of these results, we have improved NoteAid's user interface and a number of definitions, and added 4502 more definitions in CoDeMed. CONCLUSIONS: Physician evaluation yielded useful feedback for content validation and refinement of this innovative tool that has the potential to improve patient EHR comprehension and experience using patient portals. Future ongoing work will develop algorithms to handle ambiguous medical terms and test and evaluate NoteAid with patients.


Assuntos
Registros Eletrônicos de Saúde/normas , PubMed/normas , Unified Medical Language System/normas , Humanos , Processamento de Linguagem Natural , Médicos
13.
Int J Mol Med ; 41(1): 195-201, 2018 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-29115371

RESUMO

The PC12 cell line is a classical neuronal cell model due to its ability to acquire the sympathetic neurons features when deal with nerve growth factor (NGF). In the present study, the authors used a variety of different methods to induce PC12 cells, such as Opti-MEM medium containing different concentrations of fetal bovine serum (FBS) and horse serum compared with RPMI-1640 medium, and then observed the neurite length, differentiation, adhesion, cell proliferation and action potential, as well as the protein levels of axonal growth-associated protein 43 (GAP-43) and synaptic protein synapsin-1, among other differences. Compared with the conventional RPMI-1640 medium induction method, the new approach significantly improved the neurite length of induced cells (2.7 times longer), differentiation rate (30% increase), adhesion rate (21% increase) and expression of GAP-43 and synapsin-1 (three times), as well as reduced cell proliferation. The morphology of induced cells in Opti-MEM medium containing 0.5% FBS was more like that of neurons. Additionally, induced cells were also able to motivate the action potential after treatment for 6 days. Therefore, the research provided a novel, improved induction method of neural differentiation of PC12 cells using Opti-MEM medium containing 0.5% FBS, resulting in a better neuronal model cell line that can be widely used in neurobiology and neuropharmacology research.


Assuntos
Diferenciação Celular/genética , Proliferação de Células/efeitos dos fármacos , Meios de Cultura/farmacologia , Neurônios/efeitos dos fármacos , Animais , Axônios/efeitos dos fármacos , Diferenciação Celular/efeitos dos fármacos , Proteína GAP-43/genética , Regulação da Expressão Gênica no Desenvolvimento/efeitos dos fármacos , Células PC12 , Ratos , Sinapsinas/genética
14.
J Exp Clin Cancer Res ; 36(1): 176, 2017 Dec 06.
Artigo em Inglês | MEDLINE | ID: mdl-29208006

RESUMO

BACKGROUND: Renal cancers account for more than 3% of all adult malignancies and cause more than 23,400 deaths per year in China alone. The four most common types of kidney tumours include clear cell, papillary, chromophobe and benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. Some kidney tumours can be very difficult to distinguish based on the pathological assessment of morphology and immunohistochemistry. METHODS: Six renal cell carcinoma microarray data sets, including 106 clear cell, 66 papillary, 42 chromophobe, 46 oncocytoma and 35 adjacent normal tissue samples, were subjected to integrative analysis. These data were combined and used as a training set for candidate gene expression signature identification. In addition, two independent cohorts of 1020 RNA-Seq samples from The Cancer Genome Atlas database and 129 qRT-PCR samples from Fudan University Shanghai Cancer Center (FUSCC) were analysed to validate the selected gene expression signature. RESULTS: A 44-gene expression signature derived from microarray analysis was strongly associated with the histological differentiation of renal tumours and could be used for tumour subtype classification. The signature performance was further validated in 1020 RNA-Seq samples and 129 qRT-PCR samples with overall accuracies of 93.4 and 93.0%, respectively. CONCLUSIONS: A 44-gene expression signature that could accurately discriminate renal tumour subtypes was identified in this study. Our results may prompt further development of this gene expression signature into a molecular assay amenable to routine clinical practice.


Assuntos
Carcinoma de Células Renais/classificação , Perfilação da Expressão Gênica/métodos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Reação em Cadeia da Polimerase em Tempo Real/métodos , Análise Serial de Tecidos/métodos , Carcinoma de Células Renais/patologia , Feminino , Humanos , Masculino
15.
JMIR Med Inform ; 5(4): e42, 2017 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-29089288

RESUMO

BACKGROUND: Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. OBJECTIVE: We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation-that is, creating lay definitions for these terms. METHODS: Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. RESULTS: The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target-domain training examples. The 2 ADS systems both performed significantly better than the baseline systems (P<.001 for all measures and all conditions). Using a rich set of learning features contributed to ADS's performance substantially. CONCLUSIONS: ADS can effectively rank terms mined from EHRs. Transfer learning improved ADS's performance even with a small number of target-domain training examples. EHR terms prioritized by ADS were used to expand a lay language resource that supports patient EHR comprehension. The top 10,000 EHR terms ranked by ADS are available upon request.

16.
Mol Divers ; 21(3): 637-654, 2017 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-28656523

RESUMO

A series of fused-pyrimidine derivatives were prepared and evaluated for their agonistic activities against human GPR119. Compound 9i showed high potent agonistic activity against HEK293T cells over-expressing human GPR119 and improved glucose tolerance in dose-dependent manner, as well as promoted insulin secretion. In a DIO mice model, 9i also ameliorated the obese-related symptoms by decreasing the body weights without markedly changing food intake, normalized some serum biomarkers, such as ALT, AST, ALP, GLU, CHOL, HDL, and LDL, and exerted therapeutic activity on fat deposition in liver tissue. We consider 9i to have utility as a GPR119 agonists for the treatment of type 2 diabetes mellitus and obese-related symptoms.


Assuntos
Diabetes Mellitus Tipo 2/tratamento farmacológico , Obesidade/tratamento farmacológico , Pirimidinas/síntese química , Pirimidinas/uso terapêutico , Receptores Acoplados a Proteínas-G/agonistas , Animais , Biomarcadores/sangue , Peso Corporal/efeitos dos fármacos , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/metabolismo , Modelos Animais de Doenças , Regulação da Expressão Gênica/efeitos dos fármacos , Teste de Tolerância a Glucose , Células HEK293 , Humanos , Camundongos , Estrutura Molecular , Obesidade/sangue , Obesidade/metabolismo , Pirimidinas/química , Pirimidinas/farmacologia , Receptores Acoplados a Proteínas-G/genética , Relação Estrutura-Atividade
17.
Am J Transl Res ; 9(2): 692-699, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28337297

RESUMO

In addition to antibiotic therapy for treatment of peritonitis, biologics have also been found to exhibit both anti-inflammatory and inflammation-resolving properties. Here, we first developed NF-κB transgenic mice with zymosan-induced acute peritonitis to investigate the effects of a novel anti-Toll-like receptor (TLR)2 antibody (anti-T20). In this mouse model, anti-T20 treatment significantly attenuated the increase of peritoneal NF-κB activity and serum levels of inflammatory cytokines, including monocyte chemoattractant protein (MCP)-1, interleukin (IL)-6 and tumor necrosis factor (TNF)-α, in a dose-dependent manner compared to mice treated with isotype control antibody. Additionally, anti-T20 treatment significantly reduced MCP-1 levels as well as the leukocyte and total protein concentrations in the peritoneal exudates of peritonitis mice. Moreover, anti-T20 treatment significantly reduced TLR2 signal transduction in the leukocytes in peritoneal exudates from the experimental peritonitis mice. In conclusion, we developed a zymosan-induced acute peritonitis mouse model that facilitated visualization of NF-κB activity and demonstrated that anti-T20 treatment plays a protective role in this model concomitant with the inhibition of the zymosan-induced inflammatory response.

18.
J Biomed Inform ; 68: 121-131, 2017 04.
Artigo em Inglês | MEDLINE | ID: mdl-28267590

RESUMO

BACKGROUND: Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. OBJECTIVE: The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. METHODS: We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. RESULTS: FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. CONCLUSIONS: FIT can automatically identify EHR terms important to patients. It may help develop future interventions to improve quality of care. By using unsupervised learning as well as a robust and flexible framework for information fusion, FIT can be readily applied to other domains and applications.


Assuntos
Algoritmos , Registros Eletrônicos de Saúde , Registros de Saúde Pessoal , Processamento de Linguagem Natural , Compreensão , Humanos , Terminologia como Assunto
19.
Chem Biol Drug Des ; 89(5): 815-819, 2017 05.
Artigo em Inglês | MEDLINE | ID: mdl-27779815

RESUMO

A series of 1, 2, 4-oxadiazole derivatives have been designed and synthesized, and 25 compounds were evaluated their abilities by the assay of cAMP concentration in GPR119-transfected HEK293T cells. All compounds showed acceptable agonistic effects on GPR119. Among these compounds, 4p exhibited the best agonistic effects with the EC50 of 20.6 nm, which was comparable to that of positive control GPR119 agonist GSK1292263. The agonistic activity of these 1,2,4-oxadiazole derivatives led to the establishment of a structure-activity relationship.


Assuntos
Hipoglicemiantes/síntese química , Oxidiazóis/química , Receptores Acoplados a Proteínas-G/agonistas , AMP Cíclico/metabolismo , Desenho de Drogas , Avaliação Pré-Clínica de Medicamentos , Células HEK293 , Humanos , Hipoglicemiantes/química , Hipoglicemiantes/metabolismo , Mesilatos/química , Mesilatos/metabolismo , Oxidiazóis/síntese química , Oxidiazóis/metabolismo , Ligação Proteica , Receptores Acoplados a Proteínas-G/genética , Receptores Acoplados a Proteínas-G/metabolismo , Relação Estrutura-Atividade
20.
JMIR Med Inform ; 4(4): e40, 2016 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-27903489

RESUMO

BACKGROUND: Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. OBJECTIVE: We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. METHODS: First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians' agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. RESULTS: Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen's kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS's performance substantially. CONCLUSIONS: FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care.

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