Improvised Peritoneal Dialysis in an 18-month-old Child with Severe Acute Malnutrition (kwashiorkor) and Acute kidney Injury: A Case Report.

Severe acute malnutrition is common in developing countries. Children with severe acute malnutrition are prone to complications, including electrolyte imbalance and infections. Our patient was an 18-month-old boy who had severe acute malnutrition (kwashiorkor) and developed acute kidney injury, which was managed with peritoneal dialysis using improvised equipment. This case report illustrates the importance of improvisation in resource-limited settings in providing lifesaving treatment. To the best of our knowledge, this is the first case report on peritoneal dialysis in a child with severe acute malnutrition (kwashiorkor). We report a case of an 18-month-old Bantu-African Tanzanian boy who had severe malnutrition and developed anuric acute kidney injury. He had severe renal dysfunction and was managed with peritoneal dialysis using an improvised catheter and bedside constituted fluids (from intravenous fluids) and was diuretic after 7 days of peritoneal dialysis, with complete recovery of renal functions after 2 weeks. Children with severe acute malnutrition who develop acute kidney injury should be offered peritoneal dialysis, which may be provided using improvised equipment in resource-limited settings, as illustrated in this case report

Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells

<p>Abstract</p> <p>Background</p> <p>The ability to predict the spatial frequency of relapses in multiple sclerosis (MS) would enable physicians to decide when to intervene more aggressively and to plan clinical trials more accurately.</p> <p>Methods</p> <p>In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS). The dataset included the expression levels of 10,594 genes and annotated sequences corresponding to 22,215 gene-transcripts that appear in the microarray.</p> <p>Results</p> <p>We designed a two stage predictor. The first stage predictor was based on the expression level of 10 genes, and predicted the time to next relapse with a resolution of 500 days (error rate 0.079, p < 0.001). If the predicted relapse was to occur in less than 500 days, a second stage predictor based on an additional different set of 9 genes was used to give a more accurate estimation of the time till the next relapse (in resolution of 50 days). The error rate of the second stage predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p < 0.001). The predictors were further evaluated and found effective both for untreated MS patients and for MS patients that subsequently received immunomodulatory treatments after the initial testing (the error rate of the first level predictor was < 0.18 with p < 0.001 for all the patient groups).</p> <p>Conclusion</p> <p>We conclude that gene expression analysis is a valuable tool that can be used in clinical practice to predict future MS disease activity. Similar approach can be also useful for dealing with other autoimmune diseases that characterized by relapsing-remitting nature.</p

The rate of facultative sex governs the number of expected mating types in isogamous species

It is unclear why sexually reproducing isogamous species frequently contain just two self-incompatible mating types. Deterministic theory suggests that since rare novel mating types experience a selective advantage (by virtue of their many potential partners), the number of mating types should consistently grow. However, in nature, species with thousands of mating types are exceedingly rare. Several competing theories for the predominance of species with two mating types exist, yet they lack an explanation for how many are possible and in which species to expect high numbers. Here, we present a theoretical null model that explains the distribution of mating type numbers using just three biological parameters: mutation rate, population size and the rate of sex. If the number of mating types results from a mutation–extinction balance, the rate of sexual reproduction plays a crucial role. If sex is facultative and rare (a very common combination in isogamous species), mating type diversity will remain low. In this rare sex regime, small fitness differences between the mating types lead to more frequent extinctions, further lowering mating type diversity. We also show that the empirical literature supports the role of drift and facultativeness of sex as a determinant of mating type dynamics

The rate of facultative sex governs the number of expected mating types in isogamous species

It is unclear why sexually reproducing isogamous species frequently contain just two self-incompatible mating types. Deterministic theory suggests that since rare novel mating types experience a selective advantage (by virtue of their many potential partners), the number of mating types should consistently grow. However, in nature, species with thousands of mating types are exceedingly rare. Several competing theories for the predominance of species with two mating types exist, yet they lack an explanation for how many are possible and in which species to expect high numbers. Here, we present a theoretical null model that explains the distribution of mating type numbers using just three biological parameters: mutation rate, population size and the rate of sex. If the number of mating types results from a mutation–extinction balance, the rate of sexual reproduction plays a crucial role. If sex is facultative and rare (a very common combination in isogamous species), mating type diversity will remain low. In this rare sex regime, small fitness differences between the mating types lead to more frequent extinctions, further lowering mating type diversity. We also show that the empirical literature supports the role of drift and facultativeness of sex as a determinant of mating type dynamics

Fungal G-protein-coupled receptors::mediators of pathogenesis and targets for disease control

G-protein signalling pathways are involved in sensing the environment, enabling fungi to coordinate cell function, metabolism and development with their surroundings, thereby promoting their survival, propagation and virulence. G-protein-coupled receptors (GPCRs) are the largest class of cell surface receptors in fungi. Despite the apparent importance of GPCR signalling to fungal biology and virulence, relatively few GPCR–G-protein interactions, and even fewer receptor-binding ligands, have been identified. Approximately 40% of current pharmaceuticals target human GPCRs, due to their cell surface location and central role in cell signalling. Fungal GPCRs do not belong to any of the mammalian receptor classes, making them druggable targets for antifungal development. This Review Article evaluates developments in our understanding of fungal GPCR-mediated signalling, while substantiating the rationale for considering these receptors as potential antifungal targets. The need for insights into the structure–function relationship of receptor–ligand interactions is highlighted, which could facilitate the development of receptor-interfering compounds that could be used in disease control