Molecular characterization, toxin detection and resistance testing of human clinical Clostridium difficile isolates from Lebanon

Clostridium (Clostridioides) difficile is the main cause for nosocomial diarrhoea in industrialised nations. Epidemiologic data on the pathogen’s occurrence in other world regions are still scarce. In this context we characterized with phenotypic and molecular genetic methods C. difficile isolates stemming from hospitalised patients with diarrhoea in Lebanon. From 129 stool samples of symptomatic patients at a tertiary care University hospital in Lebanon, a total of 107 C. difficile strains were cultivated and underwent ribotyping, toxin gene detection and antibiotic resistance testing. Ribotype 014 (RT014, 16.8%) predominated, followed by RT002 (9.3%), RT106 (8.4%) and RT070 (6.5%). Binary toxin gene-positive isolates (RT023, RT078 and RT126) were rarely detected and RT027 was absent. Interestingly, within one isolate only the toxin A gene (tcdA) was detected. Multiple-locus variable-number tandem repeat analysis (MLVA) revealed strong strain diversity in most RTs. The isolates were sensitive to metronidazole and vancomycin, and only a small proportion of strains displayed resistance against moxifloxacin, rifampicin, and clarithromycin (5.6%, 1.9%, and 2.8%), respectively. The data indicate that the genetic strain composition of Lebanese strains differs markedly from the situation seen in Europe and North America. Especially the epidemic RTs seen in the latter regions were almost absent in Lebanon. Interestingly, most strains showed almost no resistance to commonly used antibiotics that are suspected to play a major role in the development of C. difficile infection, despite frequent use of these antibiotics in Lebanon. Thus, the role of antimicrobial resistance as a major driving force for infection development remains uncertain in this area

Recent results on multiplicative noise

Recent developments in the analysis of Langevin equations with multiplicative noise (MN) are reported. In particular, we: (i) present numerical simulations in three dimensions showing that the MN equation exhibits, like the Kardar-Parisi-Zhang (KPZ) equation both a weak coupling fixed point and a strong coupling phase, supporting the proposed relation between MN and KPZ; (ii) present dimensional, and mean field analysis of the MN equation to compute critical exponents; (iii) show that the phenomenon of the noise induced ordering transition associated with the MN equation appears only in the Stratonovich representation and not in the Ito one, and (iv) report the presence of a new first-order like phase transition at zero spatial coupling, supporting the fact that this is the minimum model for noise induced ordering transitions.Comment: Some improvements respect to the first versio

An algorithm for network-based gene prioritization that encodes knowledge both in nodes and in links

Background: Candidate gene prioritization aims to identify promising new genes associated with a disease or a biological process from a larger set of candidate genes. In recent years, network-based methods - which utilize a knowledge network derived from biological knowledge - have been utilized for gene prioritization. Biological knowledge can be encoded either through the network's links or nodes. Current network-based methods can only encode knowledge through links. This paper describes a new network-based method that can encode knowledge in links as well as in nodes. Results: We developed a new network inference algorithm called the Knowledge Network Gene Prioritization (KNGP) algorithm which can incorporate both link and node knowledge. The performance of the KNGP algorithm was evaluated on both synthetic networks and on networks incorporating biological knowledge. The results showed that the combination of link knowledge and node knowledge provided a significant benefit across 19 experimental diseases over using link knowledge alone or node knowledge alone. Conclusions: The KNGP algorithm provides an advance over current network-based algorithms, because the algorithm can encode both link and node knowledge. We hope the algorithm will aid researchers with gene prioritization. © 2013 Kimmel, Visweswaran

Non-medical prescribing versus medical prescribing for acute and chronic disease management in primary and secondary care.

The aim of this Cochrane review was to find out if prescribing by health professionals other than doctors delivers comparable outcomes to prescribing by doctors. Cochrane researchers collected and analysed all relevant studies to answer this question and found 46 studies. Key messages With appropriate training and support, nurses and pharmacists are able to prescribe medicines as part of managing a range of conditions to achieve comparable health management outcomes to doctors. The majority of studies focus on chronic disease management in higher-income counties where there is generally a moderate-certainty of evidence supporting similar outcomes for the markers of disease in high blood pressure, diabetes, and high cholesterol. Further high-quality studies are needed in poorer countries and to better quantify differences in prescribing outcomes for adverse events, and to determine health economic outcomes. Further studies could also focus more specifically on the prescribing component of care. What was studied in the review? A number of countries allow health professionals other than doctors to prescribe medicines. This shift in roles is thought to provide improved and timely access to medicines for consumers where there are shortages of doctors or the health system is facing pressures in coping with the burden of disease. In addition, this task shift has been supported by a number of governments as a way to more appropriately use the skills of health professionals, such as nurses and pharmacists, in the care of patients. We compared the outcomes of any healthcare workers who were prescribing with a high degree of autonomy with medical prescribers in the hospital or community setting in low-, middle- and high-income countries. What are the main results of the review? This review found 45 studies where nurses and pharmacists with high levels of prescribing autonomy were compared with usual care medical prescribers. A further study compared nurse prescribing with guideline support with usual nurse prescribing care. No studies were found with other health professionals or lay prescribers. Four nurse prescribing studies were undertaken in the low- and middle-income settings of Colombia, South Africa, Uganda, and Thailand. The remainder of studies were undertaken in high-income Western countries. Forty-two studies were based in a community setting, two studies were located in hospitals, one study in the workplace, and one study in an aged care facility. Prescribing was but one part of many health-related interventions, particularly in the management of chronic disease. The review found that the outcomes for non-medical prescribers were comparable to medical prescribers for: high blood pressure (moderate-certainty of evidence); diabetes control (high-certainty of evidence); high cholesterol (moderate-certainty of evidence); adverse events (low-certainty of evidence); patients adhering to their medication regimeans (moderate-certainty of evidence); patient satisfaction with care (moderate-certainty of evidence); and health-related quality of life (moderate-certainty of evidence). Pharmacists and nurses with varying levels of undergraduate, postgraduate, and specific on-the-job training related to the disease or condition were able to deliver comparable prescribing outcomes to doctors. Non-medical prescribers frequently had medical support available to facilitate a collaborative practice model

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density.

The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease

Human matrix metalloproteinases: An ubiquitarian class of enzymes involved in several pathological processes

Human matrix metalloproteinases (MMPs) belong to the M10 family of the MA clan of endopeptidases. They are ubiquitarian enzymes, structurally characterized by an active site where a Zn(2+) atom, coordinated by three histidines, plays the catalytic role, assisted by a glutamic acid as a general base. Various MMPs display different domain composition, which is very important for macromolecular substrates recognition. Substrate specificity is very different among MMPs, being often associated to their cellular compartmentalization and/or cellular type where they are expressed. An extensive review of the different MMPs structural and functional features is integrated with their pathological role in several types of diseases, spanning from cancer to cardiovascular diseases and to neurodegeneration. It emerges a very complex and crucial role played by these enzymes in many physiological and pathological processes

Causal effect of plasminogen activator inhibitor type 1 on coronary heart disease

Background--Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. Methods and Results--To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. Conclusions--Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction