Prevalence of Mycoplasma pneumoniae: A cause for community‑acquired infection among pediatric populaztion

Background: Atypical pneumonia caused by Mycoplasma pneumoniae is a leading cause of mortality among the pediatric age group.Objectives: Our study was designed to know the prevalence of M. pneumoniae in children with community‑acquired pneumonia and the involvement in the cytoadherence to the respiratory epithelium by M. pneumoniae using electron microscopy and immuno‑gold labeling technique.Materials and Methods: A total of 152 children of 1 month to 12 years of age of both sexes attending Hebei Provincial People’s Hospital, Shijiazhuang, Hebei with diagnosed pneumonia were included in the study.Results: Out of 152 children 84 (55.3%) were males, and 68 (44.7%) were females. The mean age of the patients in the control group (50 patients) was 18.5 ± 3 months with 31 (62%) males and 19 (38%) females. IgM antibodies against M. pneumoniae were positive in 84 (55.3%) males and 68 (44.7%) females. Out of 50 patients 9 (18%) were found to positive for IgM M. pneumoniae antibodies of which four (44.4%) males and 5 (55.5%) females were positive. Our study observed that the gold particles were clustered on the filamentous extension of the tip of the cells. Out of 152 serum samples subjected to particle agglutination assay 138 (90.7%) were positive 1:320 titer, 9 were >1:80 and 3 showed titer was >1:40.Conclusion: We suggest that clinicians should consider empirical therapy of broad spectrum antibiotics therapy to cover these atypical pathogens to reduce the severity before obtaining the serological results. From our study, we also suggest electron microscopic and biochemical studies for better diagnosis of these pathogens.Key words: Atypical, community‑acquired pneumonia, electron microscope, gold labelin

The effect of glutamine supplement on small intestinal morphology and xylose absorptive ability of weaned piglets

The purpose of this study is to demonstrate the effects of glutamine (Gln) supplement on small intestinal  morphology, xylose absorptive and growth performance of weaned piglets. Forty eight piglets weaned at 28 ± 2 days of age were randomly allotted to three treatment groups. A basal corn-soybean diet was formulated to contain 20.3% protein and 3450 kcal DE/kg diet. Glutamine was supplemented to the basal diet at 0% (control), 1% (Gln 1%) and 2% (Gln 2%). Pigs were fed experimental diets for three weeks. The results  showed that the villous height of the Gln groups tended higher than the control group in duodenum and jejunum (P < 0.1). Glutamine supplementation increased plasma net xylose absorptive concentration from 0.78 to 1.20 and 0.95 to 1.23 in Gln 1% and Gln 2% group, respectively, which were better than the control group (0.86 to 0.97) in day 7 to 14 after weaning. Growth performance was not significantly affected by Gln supplement;  however, average daily gain was approximately improved from 21 to 28% by Gln supplement compared to the control group during 21 days of experimental period. In summary, the results suggested that dietary  supplementation of Gln could be beneficial in small intestinal villous morphology and xylose absorptive  capacity, and could have a slight contribution to the average daily gain of weaned piglets.Key words: Glutamine, growth performance, intestinal morphology, weaned piglets

Learning Shape Priors for Single-View 3D Completion and Reconstruction

The problem of single-view 3D shape completion or reconstruction is challenging, because among the many possible shapes that explain an observation, most are implausible and do not correspond to natural objects. Recent research in the field has tackled this problem by exploiting the expressiveness of deep convolutional networks. In fact, there is another level of ambiguity that is often overlooked: among plausible shapes, there are still multiple shapes that fit the 2D image equally well; i.e., the ground truth shape is non-deterministic given a single-view input. Existing fully supervised approaches fail to address this issue, and often produce blurry mean shapes with smooth surfaces but no fine details. In this paper, we propose ShapeHD, pushing the limit of single-view shape completion and reconstruction by integrating deep generative models with adversarially learned shape priors. The learned priors serve as a regularizer, penalizing the model only if its output is unrealistic, not if it deviates from the ground truth. Our design thus overcomes both levels of ambiguity aforementioned. Experiments demonstrate that ShapeHD outperforms state of the art by a large margin in both shape completion and shape reconstruction on multiple real datasets.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://shapehd.csail.mit.edu

AA--Dependence of ΛΛ\Lambda\Lambda Bond Energies in Double---Λ\Lambda Hypernuclei

The $A$-dependence of the bond energy $\Delta B_{\Lambda\Lambda}$ of the ${\Lambda\Lambda}$ hypernuclear ground states is calculated in a three-body ${\Lambda + \Lambda + {^{A}Z}}$ model and in the Skyrme-Hartree-Fock approach. Various ${\Lambda\Lambda}$ and $\Lambda$-nucleus or ${\Lambda N}$ potentials are used and the sensitivity of $\Delta B_{\Lambda\Lambda}$ to the interactions is discussed. It is shown that in medium and heavy ${\Lambda\Lambda}$ hypernuclei, $\Delta B_{\Lambda\Lambda}$ is a linear function of $r_{\Lambda}^{-3}$, where $r_\Lambda$ is rms radius of the hyperon orbital. It looks unlikely that it will be possible to extract ${\Lambda\Lambda}$ interaction from the double-$\Lambda$ hypernuclear energies only, the additional information about the $\Lambda$-core interaction, in particular, on $r_{\Lambda}$ is needed.Comment: 11 pages, LaTex, 3 figure

Genetically modified "obligate" anaerobic Salmonella typhimurium as a therapeutic strategy for neuroblastoma

published_or_final_versio

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment

Dementia has a large negative impact on the global healthcare and society. Diagnosis is rather challenging as there is no standardised test. The purpose of this paper is to conduct an analysis on ADNI data and determine its effectiveness for building classification models to differentiate the categories Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Dementia (DEM), based on tuning three Deep Learning models: two Multi-Layer Perceptron (MLP1 and MLP2) models and a Convolutional Bidirectional Long Short-Term Memory (ConvBLSTM) model. The results show that the MLP1 and MLP2 models accurately distinguish the DEM, MCI and CN classes, with accuracies as high as 0.86 (SD 0.01). The ConvBLSTM model was slightly less accurate but was explored in view of comparisons with the MLP models, and for future extensions of this work that will take advantage of time-related information. Although the performance of ConvBLSTM model was negatively impacted by a lack of visit code data, opportunities were identified for improvement, particularly in terms of pre-processing

Accreting Neutron Stars in Low-Mass X-Ray Binary Systems

Using the Rossi X-ray Timing Explorer (RossiXTE), astronomers have discovered that disk-accreting neutron stars with weak magnetic fields produce three distinct types of high-frequency X-ray oscillations. These oscillations are powered by release of the binding energy of matter falling into the strong gravitational field of the star or by the sudden nuclear burning of matter that has accumulated in the outermost layers of the star. The frequencies of the oscillations reflect the orbital frequencies of gas deep in the gravitational field of the star and/or the spin frequency of the star. These oscillations can therefore be used to explore fundamental physics, such as strong-field gravity and the properties of matter under extreme conditions, and important astrophysical questions, such as the formation and evolution of millisecond pulsars. Observations using RossiXTE have shown that some two dozen neutron stars in low-mass X-ray binary systems have the spin rates and magnetic fields required to become millisecond radio-emitting pulsars when accretion ceases, but that few have spin rates above about 600 Hz. The properties of these stars show that the paucity of spin rates greater than 600 Hz is due in part to the magnetic braking component of the accretion torque and to the limited amount of angular momentum that can be accreted in such systems. Further study will show whether braking by gravitational radiation is also a factor. Analysis of the kilohertz oscillations has provided the first evidence for the existence of the innermost stable circular orbit around dense relativistic stars that is predicted by strong-field general relativity. It has also greatly narrowed the possible descriptions of ultradense matter.Comment: 22 pages, 7 figures, updated list of sources and references, to appear in "Short-period Binary Stars: Observation, Analyses, and Results", eds. E.F. Milone, D.A. Leahy, and D. Hobill (Dordrecht: Springer, http://www.springerlink.com

Bond-length dependence of charge-transfer excitations and stretch phonon modes in perovskite ruthenates: Evidence of strong p – d hybridization effects

We reported the optical conductivity spectra of the Ruddlesden-Popper series ruthenates, i.e., Srn+1RunO3n+1 and Can+1RunO3n+1, where n=1, 2, and `. Among various optical transitions, we investigated two Ru-O related modes, i.e., the charge-transfer excitation and the transverse stretching phonon. We found that their frequency shifts are not much affected by a structural dimensionality, but are closely related to the Ru-O bond length. Through the quantitative analysis of the charge-transfer excitation energy, we could demonstrate that the p–d hybridization should play an important role in determining their electronic structure. In addition, we discussed how the electronic excitation could contribute the lattice dynamics in the metallic ruthenate

Rapid Processing of Both Reward Probability and Reward Uncertainty in the Human Anterior Cingulate Cortex

Reward probability and uncertainty are two fundamental parameters of decision making. Whereas reward probability indicates the prospect of winning, reward uncertainty, measured as the variance of probability, indicates the degree of risk. Several lines of evidence have suggested that the anterior cingulate cortex (ACC) plays an important role in reward processing. What is lacking is a quantitative analysis of the encoding of reward probability and uncertainty in the human ACC. In this study, we addressed this issue by analyzing the feedback-related negativity (FRN), an event-related potential (ERP) component that reflects the ACC activity, in a simple gambling task in which reward probability and uncertainty were parametrically manipulated through predicting cues. Results showed that at the outcome evaluation phase, while both win and loss-related FRN amplitudes increased as the probability of win or loss decreased, only the win-related FRN was modulated by reward uncertainty. This study demonstrates the rapid encoding of reward probability and uncertainty in the human ACC and offers new insights into the functions of the ACC