Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

BACKGROUND: Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. METHODS: The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. RESULTS: It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. CONCLUSION: The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources

Assessment of pain during rest and during activities in the postoperative period of cardiac surgery

OBJECTIVE: to assess the intensity and site of pain after Cardiac Surgery through sternotomy during rest and while performing five activities. METHOD: descriptive study with a prospective cohort design. A total of 48 individuals participated in the study. A Multidimensional Scale for Pain Assessment was used. RESULTS: postoperative pain from cardiac surgery was moderate during rest and decreased over time. Pain was also moderate during activities performed on the 1st and 2nd postoperative days and decreased from the 3rd postoperative day, with the exception of coughing, which diminished only on the 6th postoperative day. Coughing, turning over, deep breathing and rest are presented in decreased order of intensity. The region of the sternum was the most frequently reported site of pain. CONCLUSION: the assessment of pain in the individuals who underwent cardiac surgery during rest and during activities is extremely important to adapt management and avoid postoperative complications and delayed surgical recovery

Lessons from giant gravitons on AdS5×T1,1AdS_{5}\times T^{1,1}

We implement Mikhailov's holomorphic curve construction to explore various properties of giant gravitons in type IIB string theory on $AdS_{5}\times T^{1,1}$. By coloring the D-brane worldvolume, we are able to show how, in the string theory, the giant graviton factorizes at its maximal size into two dibaryons - topologically stable D-branes wrapping non-contractible cycles in the $T^{1,1}$. This is related to the structure of the symmetry group of the emergent Klebanov-Witten gauge theory being a product - $SU(N) \times SU(N)$ instead of the canonical $SU(N)$. Finally, we complete this study with a systematic and detailed construction of the spectrum of small fluctuations about the giant graviton configuration. Curiously, we find that the fluctuation spectrum depends on the size of the giant. The similarity of the operator structures in the Klebanov-Witten and ABJM theories leads us to believe that the D4-brane giant graviton in type IIA string theory on $AdS_{4}\times \mathbb{CP}^{3}$ factorizes into two $\mathbb{CP}^{2}$ dibaryons in a qualitatively similar way.Comment: 39 pages; abstract reworded slightly; additional comments included in subsection 3.3; section 5 revised with the addition of subsection 5.3; added reference

Predicting olfactory receptor neuron responses from odorant structure

Background Olfactory receptors work at the interface between the chemical world of volatile molecules and the perception of scent in the brain. Their main purpose is to translate chemical space into information that can be processed by neural circuits. Assuming that these receptors have evolved to cope with this task, the analysis of their coding strategy promises to yield valuable insight in how to encode chemical information in an efficient way. Results We mimicked olfactory coding by modeling responses of primary olfactory neurons to small molecules using a large set of physicochemical molecular descriptors and artificial neural networks. We then tested these models by recording in vivo receptor neuron responses to a new set of odorants and successfully predicted the responses of five out of seven receptor neurons. Correlation coefficients ranged from 0.66 to 0.85, demonstrating the applicability of our approach for the analysis of olfactory receptor activation data. The molecular descriptors that are best-suited for response prediction vary for different receptor neurons, implying that each receptor neuron detects a different aspect of chemical space. Finally, we demonstrate that receptor responses themselves can be used as descriptors in a predictive model of neuron activation. Conclusions The chemical meaning of molecular descriptors helps understand structure-response relationships for olfactory receptors and their 'receptive fields'. Moreover, it is possible to predict receptor neuron activation from chemical structure using machine-learning techniques, although this is still complicated by a lack of training data