Literature mining for context-specific molecular relations using multimodal representations (COMMODAR).

Biological contextual information helps understand various phenomena occurring in the biological systems consisting of complex molecular relations. The construction of context-specific relational resources vastly relies on laborious manual extraction from unstructured literature. In this paper, we propose COMMODAR, a machine learning-based literature mining framework for context-specific molecular relations using multimodal representations. The main idea of COMMODAR is the feature augmentation by the cooperation of multimodal representations for relation extraction. We leveraged biomedical domain knowledge as well as canonical linguistic information for more comprehensive representations of textual sources. The models based on multiple modalities outperformed those solely based on the linguistic modality. We applied COMMODAR to the 14 million PubMed abstracts and extracted 9214 context-specific molecular relations. All corpora, extracted data, evaluation results, and the implementation code are downloadable at https://github.com/jae-hyun-lee/commodar . CCS CONCEPTS: • Computing methodologies~Information extraction • Computing methodologies~Neural networks • Applied computing~Biological networks.

Evaluation of the Efficacy and Safety of the Herbal Formula PM014 in a Cisplatin- and Paclitaxel-Treated Tumor-Bearing Mouse Model.

PM014 (HL301) is a standardized herbal mixture derived from a traditional Korean medicine, Chung-Sang-Bo-Ha-Tang. Previously, we reported that PM014 treatment significantly suppressed pulmonary fibrosis, one of the frequent adverse effects of anticancer therapy in lung cancer. Before the clinical application of PM014 in anticancer therapy, the safety and efficacy of PM014 in combination with conventional anticancer drugs should be addressed to determine whether PM014 can be used in lung cancer. Lewis lung cancer-bearing mice were injected with 10 mg/kg of cisplatin or paclitaxel on day 5. Starting on day 7, the mice were administered 200 mg/kg PM014 every 2 days. On day 15, all mice were assessed by biochemical and histological analyses. PM014 did not block the antitumor activity of cisplatin and paclitaxel. Coadministration of PM014 and antitumor agents did not elevate the aspartate transaminase/alanine transaminase ratio or the blood urea nitrogen/creatinine ratio. Histopathological analysis also showed that PM014 did not induce hepatic or renal injury. Moreover, PM014 had no apparent inhibitory effects on drug metabolizing enzymes, indicating that PM014 did not alter the pharmacokinetics of chemotherapeutic drugs. Overall, these data show the safety and compatibility of combination therapy of PM014 and chemotherapies for the treatment of lung cancer.

The rostroventral part of the thalamic reticular nucleus modulates fear extinction.

The thalamus has been implicated in fear extinction, yet the role of the thalamic reticular nucleus (TRN) in this process remains unclear. Here, in mice, we show that the rostroventral part of the TRN (TRNrv) is critically involved in the extinction of tone-dependent fear memory. Optogenetic excitation of TRNrv neurons during extinction learning dramatically facilitated, whereas the inhibition disrupted, the fear extinction. Single unit recordings demonstrated that TRNrv neurons selectively respond to conditioned stimuli but not to neutral stimuli. TRNrv neurons suppressed the spiking activity of the medial part of the dorsal midline thalamus (dMTm), and a blockade of this inhibitory pathway disrupted fear extinction. Finally, we found that the suppression of dMTm projections to the central amygdala promotes fear extinction, and TRNrv neurons have direct connections to this pathway. Our results uncover a previously unknown function of the TRN and delineate the neural circuit for thalamic control of fear memory.

In silico profiling of systemic effects of drugs to predict unexpected interactions.

Identifying unexpected drug interactions is an essential step in drug development. Most studies focus on predicting whether a drug pair interacts or is effective on a certain disease without considering the mechanism of action (MoA). Here, we introduce a novel method to infer effects and interactions of drug pairs with MoA based on the profiling of systemic effects of drugs. By investigating propagated drug effects from the molecular and phenotypic networks, we constructed profiles of 5,441 approved and investigational drugs for 3,833 phenotypes. Our analysis indicates that highly connected phenotypes between drug profiles represent the potential effects of drug pairs and the drug pairs with strong potential effects are more likely to interact. When applied to drug interactions with verified effects, both therapeutic and adverse effects have been successfully identified with high specificity and sensitivity. Finally, tracing drug interactions in molecular and phenotypic networks allows us to understand the MoA.

Predicting the Absorption Potential of Chemical Compounds Through a Deep Learning Approach.

The human colorectal carcinoma cell line (Caco-2) is a commonly used in-vitro test that predicts the absorption potential of orally administered drugs. In-silico prediction methods, based on the Caco-2 assay data, may increase the effectiveness of the high-throughput screening of new drug candidates. However, previously developed in-silico models that predict the Caco-2 cellular permeability of chemical compounds use handcrafted features that may be dataset-specific and induce over-fitting problems. Deep Neural Network (DNN) generates high-level features based on non-linear transformations for raw features, which provides high discriminant power and, therefore, creates a good generalized model. We present a DNN-based binary Caco-2 permeability classifier. Our model was constructed based on 663 chemical compounds with in-vitro Caco-2 apparent permeability data. Two hundred nine molecular descriptors are used for generating the high-level features during DNN model generation. Dropout regularization is applied to solve the over-fitting problem and the non-linear activation. The Rectified Linear Unit (ReLU) is adopted to reduce the vanishing gradient problem. The results demonstrate that the high-level features generated by the DNN are more robust than handcrafted features for predicting the cellular permeability of structurally diverse chemical compounds in Caco-2 cell lines.

Coupling effects on turning points of infectious diseases epidemics in scale-free networks.

BACKGROUND: Pandemic is a typical spreading phenomenon that can be observed in the human society and is dependent on the structure of the social network. The Susceptible-Infective-Recovered (SIR) model describes spreading phenomena using two spreading factors; contagiousness (ß) and recovery rate (γ). Some network models are trying to reflect the social network, but the real structure is difficult to uncover. METHODS: We have developed a spreading phenomenon simulator that can input the epidemic parameters and network parameters and performed the experiment of disease propagation. The simulation result was analyzed to construct a new marker VRTP distribution. We also induced the VRTP formula for three of the network mathematical models. RESULTS: We suggest new marker VRTP (value of recovered on turning point) to describe the coupling between the SIR spreading and the Scale-free (SF) network and observe the aspects of the coupling effects with the various of spreading and network parameters. We also derive the analytic formulation of VRTP in the fully mixed model, the configuration model, and the degree-based model respectively in the mathematical function form for the insights on the relationship between experimental simulation and theoretical consideration. CONCLUSIONS: We discover the coupling effect between SIR spreading and SF network through devising novel marker VRTP which reflects the shifting effect and relates to entropy.

Comparison of Extracorporeal Cardiopulmonary Resuscitation with Conventional Cardiopulmonary Resuscitation: Is Extracorporeal Cardiopulmonary Resuscitation Beneficial?

BACKGROUND: With improvements in cardiopulmonary resuscitation (CPR) techniques, the quality and the effectiveness of CPR have been established; nevertheless, the survival rate after cardiac arrest still remains poor. Recently, many reports have shown good outcomes in cases where extracorporeal membrane oxygenation (ECMO) was used during prolonged CPR. Accordingly, we attempted to evaluate the impact of extracorporeal cardiopulmonary resuscitation (ECPR) on the survival of patients who experienced a prolonged cardiac arrest and compared it with that of conventional CPR (CCPR). METHODS: Between March 2009 and April 2014, CPR, including both in-hospital and out-of-hospital CPR, was carried out in 955 patients. The ECPR group, counted from the start of the ECPR program in March 2010, included 81 patients in total, and the CCPR group consisted of 874 patients. All data were retrospectively collected from the patients' medical records. RESULTS: The return of spontaneous circulation (ROSC) rate was 2.24 times better in CPR of in-hospital cardiac arrest (IHCA) patients than in CPR of out-of-hospital CA (OHCA) patients (p=0.0012). For every 1-minute increase in the CPR duration, the ROSC rate decreased by 1% (p=0.0228). Further, for every 10-year decrease in the age, the rate of survival discharge increased by 31%. The CPR of IHCA patients showed a 2.49 times higher survival discharge rate than the CPR of OHCA patients (p=0.03). For every 1-minute increase in the CPR duration, the rate of survival discharge was decreased by 4%. ECPR showed superiority in terms of the survival discharge in the univariate analysis, although with no statistical significance in the multivariate analysis. CONCLUSION: The survival discharge rate of the ECPR group was comparable to that of the CCPR group. As the CPR duration increased, the survival discharge and the ROSC rate decreased. Therefore, a continuous effort to reduce the time for the decision of ECMO initiation and ECMO team activation is necessary, particularly during the CPR of relatively young patients and IHCA patients.

LFP-guided targeting of a cortical barrel column for in vivo two-photon calcium imaging.

Two-photon microscopy of bulk-loaded functional dyes is an outstanding physiological technique that enables simultaneous functional mapping of hundreds of brain cells in vivo at single-cell resolution. However, precise targeting of a specific cortical location is not easy due to its fine dimensionality. To enable precise targeting, intrinsic-signal optical imaging is often additionally performed. However, the intrinsic-signal optical imaging is not only time-consuming but also ineffective in ensuring precision. Here, we propose an alternative method for precise targeting based on local field potential (LFP) recording, a conventional electrophysiological method. The heart of this method lies in use of the same glass pipette to record LFPs and to eject calcium dye. After confirming the target area by LFP using a glass pipette, the calcium dye is ejected from the same pipette without a time delay or spatial adjustment. As a result, the calcium dye is loaded into the same ensemble of brain cells from which the LFP was obtained. As a validation of the proposed LFP-based method, we targeted and successfully loaded calcium dye into layer 2/3 of a mouse barrel column.

Right Heart Failure during Veno-Venous Extracorporeal Membrane Oxygenation for H1N1 Induced Acute Respiratory Distress Syndrome: Case Report and Literature Review.

A 38-year-old male was admitted with symptoms of upper respiratory infection. Despite medical treatment, his symptoms of dyspnea and anxiety became aggravated, and bilateral lung infiltration was noted on radiological imaging studies. His hypoxemia failed to improve even after the application of endotracheal intubation with mechanical ventilator care, and we therefore decided to initiate venovenous extracorporeal membrane oxygenation (VV ECMO) for additional pulmonary support. On his twentieth day of hospitalization, hypotension and desaturation (arterial saturated oxygen <85%) developed, and right ventricular failure was confirmed by two-dimensional echocardiography. Therefore, we changed from VV ECMO to venoarteriovenous (VAV) ECMO, and the patient ultimately recovered. In this case, right ventricular dysfunction and volume overloading were induced by long-term VV ECMO therapy, and we successfully treated these conditions by changing to VAV ECMO.

A study on group key agreement in sensor network environments using two-dimensional arrays.

These days, with the emergence of the concept of ubiquitous computing, sensor networks that collect, analyze and process all the information through the sensors have become of huge interest. However, sensor network technology fundamentally has wireless communication infrastructure as its foundation and thus has security weakness and limitations such as low computing capacity, power supply limitations and price. In this paper, and considering the characteristics of the sensor network environment, we propose a group key agreement method using a keyset pre-distribution of two-dimension arrays that should minimize the exposure of key and personal information. The key collision problems are resolved by utilizing a polygonal shape's center of gravity. The method shows that calculating a polygonal shape's center of gravity only requires a very small amount of calculations from the users. The simple calculation not only increases the group key generation efficiency, but also enhances the sense of security by protecting information between nodes.

Proteomic analysis of human small cell lung cancer tissues: up-regulation of coactosin-like protein-1.

Small cell lung cancer (SCLC) is the leading cause of cancer death, with a high propensity for aggressiveness and metastasis even in an early stage. Thus, identification of biomarkers as early diagnostics and treatment is needed. In this study, we investigated differentially regulated proteins between human SCLC tissues and normal bronchial epithelium by proteomic analysis using two-dimensional electrophoresis (2-DE) and MALDI-TOF mass spectrometry. Seven proteins and protein isoforms, including, γ-actin, tubulin α-1B, laminin B1, coactosin-like protein-1 (COTL-1), ubiquitin carboxyl-terminal esterase L1, ubiquitin-conjugating enzyme E2-25K, and carbonic anhydrase 1, were up-regulated more than 2 fold in SCLC tissues. In particular, up-regulated COTL-1 expression was validated by Western blot analysis, immunohistochemistry, and reverse transcription quantitative polymerase chain reaction (RT-qPCR). Moreover, most SCLC tissues (93%; 28/30) were COTL-1-positive in immunohistochemistry, whereas only 16% (10/64) of nonsmall cell lung cancer (NSLC) tissues were. Taken together, this SCLC proteomic data may help in establishing a human SCLC proteome database. COTL-1 may be a biomarker or a therapeutic target in SCLC patients.

Biological effects of fucoidan isolated from Fucus vesiculosus on thrombosis and vascular cells.

BACKGROUND: Fucoidan is a highly sulfated glycosaminoglycan, which has a molecular structure similar to that of heparin. The antithrombotic effects of fucoidan in vitro have been widely reported, but its antithrombotic effects in vivo as well as its other biological properties in vitro have not been well investigated. METHODS: This study investigated the effects and mechanism of fucoidan from Fucus vesiculosus on thrombosis both in vitro and in vivo. A ferric chloride-induced mouse carotid artery thrombosis model was used to determine the antithrombotic effects of fucoidan in vivo. Additionally, changes in the levels of proinflammatory cytokines and chemokines were examined in vascular cells treated with fucoidan. RESULTS: In vivo studies employing a ferric chloride-induced mouse carotid artery thrombosis model indicated that fucoidan had a stronger antithrombotic activity than heparin. Further, vascular cells treated with fucoidan demonstrated a decrease in proinflammatory cytokine and chemokine production as well as inhibition of proliferation. CONCLUSION: The major findings of this study showed that fucoidan has a stronger antithrombotic effect than heparin in vivo and that fucoidan has an inhibitory effect on proinflammatory cytokine production and proliferation of vascular cells.

The association of Alu repeats with the generation of potential AU-rich elements (ARE) at 3' untranslated regions.

BACKGROUND: A significant portion (about 8% in the human genome) of mammalian mRNA sequences contains AU (Adenine and Uracil) rich elements or AREs at their 3' untranslated regions (UTR). These mRNA sequences are usually stable. However, an increasing number of observations have been made of unstable species, possibly depending on certain elements such as Alu repeats. ARE motifs are repeats of the tetramer AUUU and a monomer A at the end of the repeats ((AUUU)nA). The importance of AREs in biology is that they make certain mRNA unstable. Proto-oncogene, such as c-fos, c-myc, and c-jun in humans, are associated with AREs. Although it has been known that the increased number of ARE motifs caused the decrease of the half-life of mRNA containing ARE repeats, the exact mechanism is as of yet unknown. We analyzed the occurrences of AREs and Alu and propose a possible mechanism for how human mRNA could acquire and keep AREs at its 3' UTR originating from Alu repeats. RESULTS: Interspersed in the human genome, Alu repeats occupy 5% of the 3' UTR of mRNA sequences. Alu has poly-adenine (poly-A) regions at its end, which lead to poly-thymine (poly-T) regions at the end of its complementary Alu. It has been found that AREs are present at the poly-T regions. From the 3' UTR of the NCBI's reference mRNA sequence database, we found nearly 40% (38.5%) of ARE (Class I) were associated with Alu sequences (Table 1) within one mismatch allowance in ARE sequences. Other ARE classes had statistically significant associations as well. This is far from a random occurrence given their limited quantity. At each ARE class, random distribution was simulated 1,000 times, and it was shown that there is a special relationship between ARE patterns and the Alu repeats. CONCLUSION: AREs are mediating sequence elements affecting the stabilization or degradation of mRNA at the 3' untranslated regions. However, AREs' mechanism and origins are unknown. We report that Alu is a source of ARE. We found that half of the longest AREs were derived from the poly-T regions of the complementary Alu.

Regression trees for regulatory element identification.

MOTIVATION: The transcription of a gene is largely determined by short sequence motifs that serve as binding sites for transcription factors. Recent findings suggest direct relationships between the motifs and gene expression levels. In this work, we present a method for identifying regulatory motifs. Our method makes use of tree-based techniques for recovering the relationships between motifs and gene expression levels. RESULTS: We treat regulatory motifs and gene expression levels as predictor variables and responses, respectively, and use a regression tree model to identify the structural relationships between them. The regression tree methodology is extended to handle responses from multiple experiments by modifying the split function. The significance of regulatory elements is determined by analyzing tree structures and using a variable importance measure. When applied to two data sets of the yeast Saccharomyces cerevisiae, the method successfully identifies most of the regulatory motifs that are known to control gene transcription under the given experimental conditions, and suggests several new putative motifs. Analysis of the tree structures also reconfirms several pairs of motifs that are known to regulate gene transcription in combination. AVAILABILITY: http://if.kaist.ac.kr/~phuong/RegTree