Overwhelming postsplenectomy infection due to Mycoplasma pneumoniae in an asplenic cirrhotic patient: Case report

<p>Abstract</p> <p>Background</p> <p><it>Mycoplasma </it><it>pneumoniae </it>infection is usually self-limited, but some fulminant cases are fatal, even when occurring in previously healthy individuals. It can also be the cause of overwhelming postsplenectomy infection (OPSI).</p> <p>Case presentation</p> <p>We report a case of OPSI in a 41-year-old woman with hypersplenism associated with hepatitis B cirrhosis. We detected a significant <it>Mycoplasma pneumoniae </it>agglutination titer, but no evidence of infection with <it>Chlamydia pneumoniae, Legionnella spp</it>., or any other bacterial or fungal pathogens. She eventually died despite aggressive therapy.</p> <p>Conclusions</p> <p><it>M. pneumoniae </it>could be an underestimated cause of OPSI, and should be suspected in fulminant infectious cases in asplenic patients.</p

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. 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Hybrid multicriteria fuzzy classification of network traffic patterns, anomalies, and protocols

© 2017, Springer-Verlag London Ltd., part of Springer Nature. Traffic classification in computer networks has very significant roles in network operation, management, and security. Examples include controlling the flow of information, allocating resources effectively, provisioning quality of service, detecting intrusions, and blocking malicious and unauthorized access. This problem has attracted a growing attention over years and a number of techniques have been proposed ranging from traditional port-based and payload inspection of TCP/IP packets to supervised, unsupervised, and semi-supervised machine learning paradigms. With the increasing complexity of network environments and support for emerging mobility services and applications, more robust and accurate techniques need to be investigated. In this paper, we propose a new supervised hybrid machine-learning approach for ubiquitous traffic classification based on multicriteria fuzzy decision trees with attribute selection. Moreover, our approach can handle well the imbalanced datasets and zero-day applications (i.e., those without previously known traffic patterns). Evaluating the proposed methodology on several benchmark real-world traffic datasets of different nature demonstrated its capability to effectively discriminate a variety of traffic patterns, anomalies, and protocols for unencrypted and encrypted traffic flows. Comparing with other methods, the performance of the proposed methodology showed remarkably better classification accuracy

Parallel assessment of male reproductive function in workers and wild rats exposed to pesticides in banana plantations in Guadeloupe

<p>Abstract</p> <p>Background</p> <p>There is increasing evidence that reproductive abnormalities are increasing in frequency in both human population and among wild fauna. This increase is probably related to exposure to toxic contaminants in the environment. The use of sentinel species to raise alarms relating to human reproductive health has been strongly recommended. However, no simultaneous studies at the same site have been carried out in recent decades to evaluate the utility of wild animals for monitoring human reproductive disorders. We carried out a joint study in Guadeloupe assessing the reproductive function of workers exposed to pesticides in banana plantations and of male wild rats living in these plantations.</p> <p>Methods</p> <p>A cross-sectional study was performed to assess semen quality and reproductive hormones in banana workers and in men working in non-agricultural sectors. These reproductive parameters were also assessed in wild rats captured in the plantations and were compared with those in rats from areas not directly polluted by humans.</p> <p>Results</p> <p>No significant difference in sperm characteristics and/or hormones was found between workers exposed and not exposed to pesticide. By contrast, rats captured in the banana plantations had lower testosterone levels and gonadosomatic indices than control rats.</p> <p>Conclusion</p> <p>Wild rats seem to be more sensitive than humans to the effects of pesticide exposure on reproductive health. We conclude that the concept of sentinel species must be carefully validated as the actual nature of exposure may varies between human and wild species as well as the vulnerable time period of exposure and various ecological factors.</p

Combining machine learning and metaheuristics algorithms for classification method PROAFTN

© Crown 2019. The supervised learning classification algorithms are one of the most well known successful techniques for ambient assisted living environments. However the usual supervised learning classification approaches face issues that limit their application especially in dealing with the knowledge interpretation and with very large unbalanced labeled data set. To address these issues fuzzy classification method PROAFTN was proposed. PROAFTN is part of learning algorithms and enables to determine the fuzzy resemblance measures by generalizing the concordance and discordance indexes used in outranking methods. The main goal of this chapter is to show how the combined meta-heuristics with inductive learning techniques can improve performances of the PROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems

Distinct Neurobehavioural Effects of Cannabidiol in Transmembrane Domain Neuregulin 1 Mutant Mice

The cannabis constituent cannabidiol (CBD) possesses anxiolytic and antipsychotic properties. We have previously shown that transmembrane domain neuregulin 1 mutant (Nrg1 TM HET) mice display altered neurobehavioural responses to the main psychoactive constituent of cannabis, Δ9-tetrahydrocannabinol. Here we investigated whether Nrg1 TM HET mice respond differently to CBD and whether CBD reverses schizophrenia-related phenotypes expressed by these mice. Adult male Nrg1 TM HET and wild type-like littermates (WT) received vehicle or CBD (1, 50 or 100 mg/kg i.p.) for 21 days. During treatment and 48 h after withdrawal we measured behaviour, whole blood CBD concentrations and autoradiographic receptor binding. Nrg1 HET mice displayed locomotor hyperactivity, PPI deficits and reduced 5-HT2A receptor binding density in the substantia nigra, but these phenotypes were not reversed by CBD. However, long-term CBD (50 and 100 mg/kg) selectively enhanced social interaction in Nrg1 TM HET mice. Furthermore, acute CBD (100 mg/kg) selectively increased PPI in Nrg1 TM HET mice, although tolerance to this effect was manifest upon repeated CBD administration. Long-term CBD (50 mg/kg) also selectively increased GABAA receptor binding in the granular retrosplenial cortex in Nrg1 TM HET mice and reduced 5-HT2A binding in the substantia nigra in WT mice. Nrg1 appears necessary for CBD-induced anxiolysis since only WT mice developed decreased anxiety-related behaviour with repeated CBD treatment. Altered pharmacokinetics in mutant mice could not explain our findings since no genotype differences existed in CBD blood concentrations. Here we demonstrate that Nrg1 modulates acute and long-term neurobehavioural effects of CBD, which does not reverse the schizophrenia-relevant phenotypes

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

Soil quality and health risk assessment of heavy metals in agricultural areas irrigated with wastewater from Kitchener Drain, Nile Delta, Egypt

Kitchener drain is one of the largest drains in Nile Delta. It discharges water directly into Mediterranean Sea water affecting on the marine environment. Local population uses its water in irrigation and agriculture field along this drain. So it’s important to determine heavy metal content of agricultural soils used this water in irrigation process and assess the hazard and cancer risk on human health living in these areas. Six metals (Fe, Cd, Pb, Ni, Cr and Co) in total and available form were determined in eight geo-referenced soil samples. The order of these metals in soil was as follow; Ni &gt; Cr &gt; Fe &gt; Pb &gt; Cd &gt; Co. The order of these metals in the available form take the sequence of; Fe &gt; Ni &gt; Pb &gt; Cr &gt; Cd &gt; Co.&nbsp; All mean concentrations of metals were exceeding the standard limits of EU, CSQG and AUEC except for cobalt. Mean values of enrichment factors of metals give an indication that the sources of these metals in the environment were from anthropogenic activities. PLI and DC showed considerable degree of contamination in sites 4 &amp; 5. While it showed high degree of contamination in other sites. Hazard quotient from different exposure pathways namely; chemical daily intake (CDI), Dermal contact (DAD) and inhalation (ECinh) and hazard index calculations from metals within different sites were more than one, indicated that there is a chance of non-carcinogenic effects to occur. Also from these pathways, cancer risk (CR) was calculated, which exceed from dermal contact, followed by ingestion and finally from inhalation. Only CR of cobalt showed no risk in the study area when compared with other metal