Impact of routine cryptococcal antigen screening and targeted pre-emptive fluconazole therapy in antiretroviral naive HIV-infected adults with less than 100 CD4 cells/μL: a systematic review and meta-analysis.

Cryptococcal antigen (CrAg) screening and targeted pre-emptive fluconazole in antiretroviral naive HIV-infected adults with less than 100 CD4 cells/μL seems promising to reduce the burden of cryptococcal meningitis (CM). We searched MEDLINE, EMBASE, and Web of Science and used random-effect meta-analysis to assess the prevalence of blood CrAg-positivity (31 studies; 35,644 participants) and asymptomatic CM in CrAg-positives, incidence of CM and all-cause mortality in screened participants. Pooled prevalence of blood CrAg-positivity was 6% (95%CI: 5 - 7) and asymptomatic CM in CrAg-positives was 33% (95%CI: 21 - 45). Incidence of CM without pre-emptive fluconazole was 21.4% (95%CI: 11.6 - 34.4) and 5.7% (95%CI: 3.0 - 9.7) with pre-emptive fluconazole initiated at 800 mg/day. In CrAg-positives, post-screening lumbar puncture prior to initiating pre-emptive fluconazole at 800 mg/day further reduced incidence of CM to null and showed some survival benefits. However, all-cause mortality remained significantly higher in CrAg-positives than CrAg-negatives: RR: 2.2 (95%CI: 1.7 - 2.9, p<0.001)

A Framework to Estimate the Nutritional Value of Food in Real Time Using Deep Learning Techniques

There has been a rapid increase in dietary ailments during last few decades, caused by unhealthy food routine. Mobile-based dietary assessment systems that can record real time images of meal and analyze it for nutritional content can be very handy and improve the dietary habits, and therefore, result in healthy life. This paper proposes a novel system to automatically estimate food attributes such as ingredients and nutritional value by classifying the input image of food. Our method employs different deep learning models for accurate food identification. In addition to image analysis, attributes and ingredients are estimated by extracting semantically related words from a huge corpus of text, collected over the Internet. We performed experiments with a dataset comprising 100 classes, averaging 1000 images for each class to acquire top 1 classification rate of up to 85 percent. An extension of a benchmark dataset Food-101 is also created to include sub-continental foods. Results show that our proposed system is equally efficient on basic Food- 101 dataset and its extension for sub-continental foods. The proposed system is implemented as a mobile app that has its application in healthcare sector

Scoring Protein Relationships in Functional Interaction Networks Predicted from Sequence Data

The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins

The future of hybrid imaging—part 1: hybrid imaging technologies and SPECT/CT

Since the 1990s, hybrid imaging by means of software and hardware image fusion alike allows the intrinsic combination of functional and anatomical image information. This review summarises in three parts the state-of-the-art of dual-technique imaging, with a focus on clinical applications. We will attempt to highlight selected areas of potential improvement of combined imaging technologies and new applications. In this first part, we briefly review the origins of hybrid imaging and comment on the status and future development of single photon emission tomography (SPECT)/computed tomography (CT). In short, we could predict that, within 10 years, we may see all existing dual-technique imaging systems, including SPECT/CT, in clinical routine use worldwide. SPECT/CT, in particular, may evolve into a whole-body imaging technique with supplementary use in dosimetry applications

Measurement of the Negative Muon Anomalous Magnetic Moment to 0.7 ppm

The anomalous magnetic moment of the negative muon has been measured to a precision of 0.7 parts per million (ppm) at the Brookhaven Alternating Gradient Synchrotron. This result is based on data collected in 2001, and is over an order of magnitude more precise than the previous measurement of the negative muon. The result a_mu= 11 659 214(8)(3) \times 10^{-10} (0.7 ppm), where the first uncertainty is statistical and the second is sytematic, is consistend with previous measurements of the anomaly for the positive and negative muon. The average for the muon anomaly a_{mu}(exp) = 11 659 208(6) \times 10^{-10} (0.5ppm).Comment: 4 pages, 4 figures, submitted to Physical Review Letters, revised to reflect referee comments. Text further revised to reflect additional referee comments and a corrected Fig. 3 replaces the older versio

Seagrass can mitigate negative ocean acidification effects on calcifying algae

The ultimate effect that ocean acidification (OA) and warming will have on the physiology of calcifying algae is still largely uncertain. Responses depend on the complex interactions between seawater chemistry, global/local stressors and species-specific physiologies. There is a significant gap regarding the effect that metabolic interactions between coexisting species may have on local seawater chemistry and the concurrent effect of OA. Here, we manipulated CO2 and temperature to evaluate the physiological responses of two common photoautotrophs from shallow tropical marine coastal ecosystems in Brazil: the calcifying alga Halimeda cuneata, and the seagrass Halodule wrightii. We tested whether or not seagrass presence can influence the calcification rate of a widespread and abundant species of Halimeda under OA and warming. Our results demonstrate that under elevated CO2, the high photosynthetic rates of H. wrightii contribute to raise H. cuneata calcification more than two-fold and thus we suggest that H. cuneata populations coexisting with H. wrightii may have a higher resilience to OA conditions. This conclusion supports the more general hypothesis that, in coastal and shallow reef environments, the metabolic interactions between calcifying and non-calcifying organisms are instrumental in providing refuge against OA effects and increasing the resilience of the more OA-susceptible species.E.B. would like to thank the Coordenação de Aperfeiçoamento de Pessoas de Nível Superior (CAPES) for Masters funding. Funding for this project came from the Synergism grant (CNPq 407365/2013-3). We extend our thanks to the Brazil-based Projeto Coral Vivo and its sponsor PetroBras Ambiental for providing the Marine Mesocosm structure and experimental assistance.info:eu-repo/semantics/publishedVersio

The Functional DRD3 Ser9Gly Polymorphism (rs6280) Is Pleiotropic, Affecting Reward as Well as Movement

Abnormalities of motivation and behavior in the context of reward are a fundamental component of addiction and mood disorders. Here we test the effect of a functional missense mutation in the dopamine 3 receptor (DRD3) gene (ser9gly, rs6280) on reward-associated dopamine (DA) release in the striatum. Twenty-six healthy controls (HCs) and 10 unmedicated subjects with major depressive disorder (MDD) completed two positron emission tomography (PET) scans with [11C]raclopride using the bolus plus constant infusion method. On one occasion subjects completed a sensorimotor task (control condition) and on another occasion subjects completed a gambling task (reward condition). A linear regression analysis controlling for age, sex, diagnosis, and self-reported anhedonia indicated that during receipt of unpredictable monetary reward the glycine allele was associated with a greater reduction in D2/3 receptor binding (i.e., increased reward-related DA release) in the middle (anterior) caudate (p<0.01) and the ventral striatum (p<0.05). The possible functional effect of the ser9gly polymorphism on DA release is consistent with previous work demonstrating that the glycine allele yields D3 autoreceptors that have a higher affinity for DA and display more robust intracellular signaling. Preclinical evidence indicates that chronic stress and aversive stimulation induce activation of the DA system, raising the possibility that the glycine allele, by virtue of its facilitatory effect on striatal DA release, increases susceptibility to hyperdopaminergic responses that have previously been associated with stress, addiction, and psychosis

Sexual Size Dimorphism and Body Condition in the Australasian Gannet

Funding: The research was financially supported by the Holsworth Wildlife Research Endowment. Acknowledgments We thank the Victorian Marine Science Consortium, Sea All Dolphin Swim, Parks Victoria, and the Point Danger Management Committee for logistical support. We are grateful for the assistance of the many field volunteers involved in the study.Peer reviewedPublisher PD