Treatment of Helicobacter pylori infections: Mitigating factors and prospective natural remedies

Helicobacter pylori is a Gram-negative, microaerophilic spiral or motile rod that infects about half the world’s population with a very high prevalence in the developing world. It is an important aetiological factor in the development of gastritis, peptic ulcer disease, gastric atrophy and B cell mucosa associated lymphoid tissue (MALT) lymphoma. H. pylori infection is responsible for a significant cause of morbidity and mortality imposing a major burden on health care systems world wide. The high prevalence of infection in the developing countries has been attributed to poor socioeconomic status and sanitation as well as an increased trend of antibiotic resistance. Antimicrobial chemotherapy (two antibiotics and a proton pump inhibitor) employed for the treatment of H. pylori infections has emerged as the most important means to resolve these infections. However, antimicrobial therapy is fraught with a number of inherent limitations such as resistance, cost of treatment, unavailability of drugs in rural areas and undesirable side effects necessitating the need to search for alternative approaches from natural sources including vegetables, honey and probiotics amongst others. These could form the basis of novel low cost, efficient, large-scale and alternative/complementary solutions with minimal side effects to decrease or eradicate H. pylori infections in the future

Some solutions to the multivariate Behrens-Fisher problem for dissimilarity-based analyses

The essence of the generalised multivariate Behrens–Fisher problem (BFP) is how to test the null hypothesis of equality of mean vectors for two or more populations when their dispersion matrices differ. Solutions to the BFP usually assume variables are multivariate normal and do not handle high‐dimensional data. In ecology, species' count data are often high‐dimensional, non‐normal and heterogeneous. Also, interest lies in analysing compositional dissimilarities among whole communities in non‐Euclidean (semi‐metric or non‐metric) multivariate space. Hence, dissimilarity‐based tests by permutation (e.g., PERMANOVA, ANOSIM) are used to detect differences among groups of multivariate samples. Such tests are not robust, however, to heterogeneity of dispersions in the space of the chosen dissimilarity measure, most conspicuously for unbalanced designs. Here, we propose a modification to the PERMANOVA test statistic, coupled with either permutation or bootstrap resampling methods, as a solution to the BFP for dissimilarity‐based tests. Empirical simulations demonstrate that the type I error remains close to nominal significance levels under classical scenarios known to cause problems for the un‐modified test. Furthermore, the permutation approach is found to be more powerful than the (more conservative) bootstrap for detecting changes in community structure for real ecological datasets. The utility of the approach is shown through analysis of 809 species of benthic soft‐sediment invertebrates from 101 sites in five areas spanning 1960 km along the Norwegian continental shelf, based on the Jaccard dissimilarity measure

Helicobacter pylori infection and transmission in Africa: Household hygiene and water sources are plausible factors exacerbating spread

Helicobacter pylori (H. pylori) is a microaerophilic motile curve rod that inhabits the gastric mucosa of the human stomach. The organism chronically infects billions of people worldwide and is one of themost genetically diverse of bacterial species. Infection with the bacterium which leads to chronic gastritis, peptic ulceration, gastric cancers and gastric malt lymphoma has been reported to follow a pattern linked to geographic and socio-demographic factors. Studies have documented a higherprevalence in Africa than elsewhere although the pathological outcomes do not correlate with infection. H. pylori transmission pathways are still vague, but the risks of transmission include precarious hygiene standards, over-crowding and contaminated environment and water sources amongst others. The possible routes of transmission include oral-oral, faecal-oral and person- to -person, either with or without transitional transmission steps during episodes of diarrhoea or gastro-oral contact in the eventof vomiting. Use of contaminated water including municipal tap water has also been suspected to have a high impact in the transmission of the organism. To generate the data presented in this paper, we conducted an internet based search on relevant literature pertaining to H. pylori epidemiology in general and Africa in particular. Sites such as Pubmed, AJOL, Scopus and Goggle scholar were mainly used. This paper therefore attempts to appraise the role of household hygiene and water sources in the transmission of this organism in the developing world context

A generalised analysis of similarities (ANOSIM) statistic for designs with ordered factors

In the study of multivariate data, for example of change in ecological communities, ANOSIM is a robust non-parametric hypothesis-testing framework for differences in resemblances among groups of samples. RELATE is a non-parametric Mantel test of the hypothesis of no relationship between two resemblance matrices. Details are given of the explicit link between the RELATE statistic, a Spearman rank correlation (ρ) between corresponding elements in the two resemblance matrices, and the ANOSIM statistic R, a scaled contrast between the among- and within-group ranks. It is seen that R can equivalently be defined as the slope of the linear regression of ranked resem�blances from observations against ranked distances among samples, the latter from a simple model matrix assigning the values 1 and 0 to between- and within-group distances, respectively. Re-defining this model matrix to represent ordered distances among groups leads naturally to a generalised ANOSIM statistic, RO, suitable for testing, for example, ordered factor levels in space or time, or an environmental or pollution gradient. Two variants of the generalised ANOSIM statistic are described, namely ROc where there are replicates within groups, and ROs where there are only single samples (no replicates) within groups, for which an ANOSIM test was not previously available. Three marine ecological examples using ANOSIM to analyse an ordered factor in one-way designs are provided. These are: (1) changes in macrofaunal composition with increasing distance from an oil rig; (2) differences in phytal meiofaunal community composition with increasing macroalgal complexity; and (3) changes in average community composition of free-living nematodes along a long-term heavy metal gradient. Incorporating knowledge of an ordering structure is seen to provide more focussed, and thus stronger, ANOSIM tests, but inevitably risks losing power if that prior knowledge is incorrect or inappropriat

Analysis of similarities (ANOSIM) for 2‐way layouts using a generalised ANOSIM statistic, with comparative notes on Permutational Multivariate Analysis of Variance (PERMANOVA)

In the study of multivariate data, for example of change in ecological communities, ANOSIM is a robust non-parametric hypothesis-testing framework for differences in resemblances among groups of samples. RELATE is a non-parametric Mantel test of the hypothesis of no relationship between two resemblance matrices. Details are given of the explicit link between the RELATE statistic, a Spearman rank correlation (ρ) between corresponding elements in the two resemblance matrices, and the ANOSIM statistic R, a scaled contrast between the among- and within-group ranks. It is seen that R can equivalently be defined as the slope of the linear regression of ranked resemblances from observations against ranked distances among samples, the latter from a simple model matrix assigning the values 1 and 0 to between- and within-group distances, respectively. Re-defining this model matrix to represent ordered distances among groups leads naturally to a generalised ANOSIM statistic, RO, suitable for testing, for example, ordered factor levels in space or time, or an environmental or pollution gradient. Two variants of the generalised ANOSIM statistic are described, namely ROc where there are replicates within groups, and ROs where there are only single samples (no replicates) within groups, for which an ANOSIM test was not previously available. Three marine ecological examples using ANOSIM to analyse an ordered factor in one-way designs are provided. These are: (1) changes in macrofaunal composition with increasing distance from an oil rig; (2) differences in phytal meiofaunal community composition with increasing macroalgal complexity; and (3) changes in average community composition of free-living nematodes along a long-term heavy metal gradient. Incorporating knowledge of an ordering structure is seen to provide more focussed, and thus stronger, ANOSIM tests, but inevitably risks losing power if that prior knowledge is incorrect or inappropriate

Analysis of similarities (ANOSIM) for 3‐way designs

Analysis of similarities (ANOSIM) is a robust non-parametric hypothesis-testing framework for differences in resemblances among groups of samples. To date, the generalisation and use of ANOSIM to analyse various 2-way nested and crossed designs with unordered or ordered factors has been described. This paper describes how the 2-way tests may be extended and modified for the analysis of 3-way designs, including the introduction of a different type of constrained permutation procedure for a design in which one factor is nested in another and crossed with a third. The construction of 3-way tests using the generalised statistic in various nested and crossed designs, with or without ordered factors, and with or without replication, is described. Applications of the new tests to ecological data are demonstrated using three marine examples. They are as follows: a study of changes in fish diet for fish of increasing size sampled in different locations at different times (a 3-way fully crossed design with ordered factors); a hierarchical spatial study of the fauna inhabiting kelp holdfasts (a 3- way fully nested design with unordered factors); and a study of infaunal macrobenthos in which sites within areas were resampled over a long time series (a design in which sites are nested in areas but crossed with years, both latter factors potentially being ordered). The magnitudes of the ANOSIM statistics provide information about relative effect sizes (accounting for other factors), which is often a focus for multifactorial designs. Though the described ANOSIM tests do not provide parallels for all the range of 3-way mixed-factor designs possible in ANOVA (and its multivariate semi-parametric counterpart PERMANOVA), it is seen that for nested factors these ANOSIM tests parallel the matching PERMANOVA random-effects models, and not their fixed-effects counterparts, thus allowing the same broader inference about the space from which these random factor levels are drawn

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach

49 Marked susceptibility of South African Helicobacter pylori strains to ciprofloxacin and amoxicillin: Clinical implications

Objectives. Helicobacter pylori-associated infection is commonin South Africa, as in other developing countries. Antibioticresistance is recognised as a major cause of treatment failure.We studied the susceptibility and resistance patterns of H.pylori to guide empiric treatment and prevent the emergenceof resistance.Methods. Two hundred H. pylori strains obtained from gastricbiopsies of patients presenting with gastric-related morbiditiesattending Livingstone Hospital, Port Elizabeth, were evaluatedfor their susceptibility to seven antibiotics – metronidazole,clarithromycin, tetracycline, amoxicillin, gentamicin, ciprofloxacin and erythromycin. H. pylori was isolated following standard microbiology procedures, and susceptibility determined using the Kirby-Bauer disc diffusion and agar dilution methods. Comparisons of antimicrobial resistance rates with sex of the patients were determined using the chisquare test; a p-value o

Helicobacter pylori prevalence in dyspeptic patients in the Eastern Cape province – race and disease status

Objectives. We examined Helicobacter pylori infection in patients with gastric-related morbidities at Livingstone Hospital, Port Elizabeth, to determine the prevalence and risk factors for infection according to race, endoscopic diagnosis, age and sex. Methods. Gastric biopsies were collected from 254 consecutive patients and H. pylori was isolated on Columbia agar base supplemented with 7% sheep’s blood and Skirrow’s supplement containing trimethoprim (2.5 mg), vancomycin (5 mg) and cefsulodin (2.5 mg). Amphotericin (2.5 mg) was added to the medium. Recovered isolates were identified following standard microbiology and biochemical techniques. Presumptive isolates were further confirmed by polymerase chain reaction (PCR) targeting the glmM gene. Fisher’s exact test was used to assess the univariate association between H. pylori infection and the possible risk factors. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated to measure the strength of association, using EPI INFO 3.41 software. p-value

Remote physiological monitoring: Clinical, financial, and behavioral outcomes in a heart failure population

This article reports on the outcomes associated with remote physiological monitoring (RPM) conducted as part of a heart failure disease management program. Claims data, medical records, data transmission records, and survey results for 91 individuals ages 50–92 (mean 74 years) successfully completing a heart failure RPM program were analyzed for time periods before, during, and after the monitoring intervention. The program was associated with significant reductions in per member per month costs and emergency room and hospital utilization. More detailed analyses were performed for specific gender and age subgroups. Participant surveys indicated high levels of satisfaction, and improvements in self-perceived health status, self-efficacy, and self-management behaviors. This study is the first to assess the impact of a RPM program following removal of the monitoring equipment. The results indicate that RPM, as a component of a traditional disease management program, has a sustained, beneficial effect on participants’ lifestyles after the monitoring period has ended