4,695 research outputs found
Accurate Reproduction of 161 Small-Molecule Complex Crystal Structures using the EUDOC Program: Expanding the Use of EUDOC to Supramolecular Chemistry
EUDOC is a docking program that has successfully predicted small-molecule-bound protein complexes and identified drug leads from chemical databases. To expand the application of the EUDOC program to supramolecular chemistry, we tested its ability to reproduce crystal structures of small-molecule complexes. Of 161 selected crystal structures of small-molecule guest-host complexes, EUDOC reproduced all these crystal structures with guest structure mass-weighted root mean square deviations (mwRMSDs) of <1.0 Å relative to the corresponding crystal structures. In addition, the average interaction energy of these 161 guest-host complexes (−50.1 kcal/mol) was found to be nearly half of that of 153 previously tested small-molecule-bound protein complexes (−108.5 kcal/mol), according to the interaction energies calculated by EUDOC. 31 of the 161 complexes could not be reproduced with mwRMSDs of <1.0 Å if neighboring hosts in the crystal structure of a guest-host complex were not included as part of the multimeric host system, whereas two of the 161 complexes could not be reproduced with mwRMSDs of <1.0 Å if water molecules were excluded from the host system. These results demonstrate the significant influence of crystal packing on small molecule complexation and suggest that EUDOC is able to predict small-molecule complexes and that it is useful for the design of new materials, molecular sensors, and multimeric inhibitors of protein-protein interactions
Assessment of depression in medical patients: A systematic review of the utility of the Beck Depression Inventory-II
To perform a systematic review of the utility of the Beck Depression Inventory for detecting depression in medical settings, this article focuses on the revised version of the scale (Beck Depression Inventory-II), which was reformulated according to the DSM-IV criteria for major depression. We examined relevant investigations with the Beck Depression Inventory-II for measuring depression in medical settings to provide guidelines for practicing clinicians. Considering the inclusion and exclusion criteria seventy articles were retained. Validation studies of the Beck Depression Inventory-II, in both primary care and hospital settings, were found for clinics of cardiology, neurology, obstetrics, brain injury, nephrology, chronic pain, chronic fatigue, oncology, and infectious disease. The Beck Depression Inventory-II showed high reliability and good correlation with measures of depression and anxiety. Its threshold for detecting depression varied according to the type of patients, suggesting the need for adjusted cut-off points. The somatic and cognitive-affective dimension described the latent structure of the instrument. The Beck Depression Inventory-II can be easily adapted in most clinical conditions for detecting major depression and recommending an appropriate intervention. Although this scale represents a sound path for detecting depression in patients with medical conditions, the clinician should seek evidence for how to interpret the score before using the Beck Depression Inventory-II to make clinical decisions
Comparação de caracterÃsticas demográficas e clÃnicas entre crianças e adolescentes com transtorno depressivo maior
OBJECTIVE: To compare clinical characteristics of major depressive disorder symptoms between children and adolescents. METHOD: The subjects were 58 patients of a Child and Adolescent Affective Disorder Clinic consecutively admitted during a six-month period. Children aged 5-9 years old and adolescents from 10-17 years old currently meeting DSM-IV criteria diagnosis of major depressive disorder were chosen. Current MDD diagnosis and depressive psychopathology were assessed by a clinical interview and the Diagnostic Interview for Children and Adolescents-DSM-IV version. The Children’s Depression Rating Scale-Revised Version and the Children Global Assessment Scale rated the severity and global functioning of major depressive disorder. RESULTS: The most common depressive symptoms were: anhedonia (72.4%), depressed mood (72.4%), decreased concentration (62.1%), and irritability (58.6%). The intensity of depressive episodes of this sample ranged from mild to moderate. Fifty percent reported thoughts of death, and 29.3% presented a variety of psychotic symptoms. When compared with children, adolescents reported a significantly more depressed mood (p = 0.043), lower self-esteem (p = 0.002), and had more difficulty concentrating (p = 0.020). Female adolescents had lower self-esteem (p = 0.003), and male adolescents showed more decreased concentration (p = 0.016). CONCLUSION: This study suggests that age and gender differences might influence the clinical presentation of major depressive disorder in children and adolescents. Further studies with larger samples are needed.OBJETIVO: Comparar as caracterÃsticas clÃnicas de transtorno depressivo maior entre crianças e adolescentes. MÉTODO: Amostra constituÃda de 58 sujeitos admitidos consecutivamente em um serviço especializado em transtornos do humor na infância e adolescência durante um perÃodo de 6 meses. Foram considerados crianças sujeitos com idade entre 5 e 9 anos, e adolescentes aqueles com idade entre 10 e 17 anos. Todos os participantes preenchiam diagnóstico de transtorno depressivo maior seguindo os critérios de DSM-IV. O diagnóstico de transtorno depressivo maior e avaliação de aspectos psicopatológicos foram realizados por entrevista clÃnica direta e aplicação de entrevista de apoio ao diagnóstico. O funcionamento global e a gravidade dos sintomas depressivos foram mensurados através de versões adaptadas de Children’s Depression Rating Scale-Revised Version e Children Global Assessment Scale. RESULTADOS: Os sintomas depressivos mais freqüentes foram: anedonia (72,4%), humor depressivo (72,4%), diminuição de concentração (62,1%) e irritabilidade (58,6%). A intensidade do episódio depressivo dessa amostra variou de leve a moderada. Cinqüenta por cento relataram pensamentos mórbidos e 29,3% apresentaram sintomas psicóticos variados. Quando comparados com crianças, adolescentes apresentaram significativamente mais humor depressivo (p = 0,043), baixa auto-estima (p = 0,002) e mais dificuldade de concentração (p = 0,020). As adolescentes femininas tinham mais baixa auto-estima (p = 0,003) e os masculinos mostraram mais diminuição de concentração (p = 0,016). CONCLUSÃO: Esse estudo sugere que idade e gênero poderiam influenciar na apresentação clÃnica de transtorno depressivo maior em crianças e adolescentes. Estudos com amostra mais representativa serão necessários
Enhancing Deep Neural Networks Testing by Traversing Data Manifold
We develop DEEPTRAVERSAL, a feedback-driven framework to test DNNs.
DEEPTRAVERSAL first launches an offline phase to map media data of various
forms to manifolds. Then, in its online testing phase, DEEPTRAVERSAL traverses
the prepared manifold space to maximize DNN coverage criteria and trigger
prediction errors. In our evaluation, DNNs executing various tasks (e.g.,
classification, self-driving, machine translation) and media data of different
types (image, audio, text) were used. DEEPTRAVERSAL exhibits better performance
than prior methods with respect to popular DNN coverage criteria and it can
discover a larger number and higher quality of error-triggering inputs. The
tested DNN models, after being repaired with findings of DEEPTRAVERSAL, achieve
better accurac
MDPFuzz: Testing Models Solving Markov Decision Processes
The Markov decision process (MDP) provides a mathematical framework for
modeling sequential decision-making problems, many of which are crucial to
security and safety, such as autonomous driving and robot control. The rapid
development of artificial intelligence research has created efficient methods
for solving MDPs, such as deep neural networks (DNNs), reinforcement learning
(RL), and imitation learning (IL). However, these popular models for solving
MDPs are neither thoroughly tested nor rigorously reliable.
We present MDPFuzzer, the first blackbox fuzz testing framework for models
solving MDPs. MDPFuzzer forms testing oracles by checking whether the target
model enters abnormal and dangerous states. During fuzzing, MDPFuzzer decides
which mutated state to retain by measuring if it can reduce cumulative rewards
or form a new state sequence. We design efficient techniques to quantify the
"freshness" of a state sequence using Gaussian mixture models (GMMs) and
dynamic expectation-maximization (DynEM). We also prioritize states with high
potential of revealing crashes by estimating the local sensitivity of target
models over states.
MDPFuzzer is evaluated on five state-of-the-art models for solving MDPs,
including supervised DNN, RL, IL, and multi-agent RL. Our evaluation includes
scenarios of autonomous driving, aircraft collision avoidance, and two games
that are often used to benchmark RL. During a 12-hour run, we find over 80
crash-triggering state sequences on each model. We show inspiring findings that
crash-triggering states, though look normal, induce distinct neuron activation
patterns compared with normal states. We further develop an abnormal behavior
detector to harden all the evaluated models and repair them with the findings
of MDPFuzzer to significantly enhance their robustness without sacrificing
accuracy
Learning probabilistic models for model checking: an evolutionary approach and an empirical study
Learning probabilistic models for model checking: an evolutionary approach and an empirical study
spectroscopy using the modified Rovibrational model
Mass spectra of quarkonium systems can be described by different
phenomenological potentials. In the present work, the {\color{black}resonance}
states of heavy quarkonium like ( and ) are considered as
the rovibrational states. We study a parameterized rovibrational model derived
from the empirical solution of the nonrelativistic Schr\"{o}dinger equation
with Morse potential, the corrections are composed of colour hyperfine
interaction and spin-orbit interaction of mesons. We {\color{black}obtain} the
high excited state mass spectra of charmonium and bottomonium comparing the
results in reasonable agreement with the present experimental data.Comment: 6 pages, 4 figure
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