Evaluation of a text supported weight maintenance programme ‘Lighten Up Plus’ following a weight reduction programme: randomised controlled trial

Background Many overweight people find it difficult to maintain weight loss after attending a weight reduction programme. Self-weighing and telephone support are known to be useful methods for self-monitoring for weight loss. We examined the effectiveness of an SMS-text messaging based weight maintenance programme to encourage regular self-weighing in adults who had completed a 12 week commercial weight loss programme. Methods Randomised controlled trial of 380 obese or overweight men and women. The intervention group (n=190) received a single maintenance support phone call and SMS-text based weight maintenance messages over 12 weeks to encourage regular self-weighing after completing their weight loss programme. The primary outcome was change in weight at nine months follow up. Results Our sample (N=380) had a mean age of 47.4 years (SD 13.4), mean baseline weight and BMI of 93.1kg (16.1) and 34.4 kg/m2 (5.0) respectively, as well as majority female (87.3%) and White British (80.0%). Using intention to treat analysis both groups regained weight at nine months follow up; the intervention group regained an average of 1.36 kg while the control group regained 1.81 kg. Adjusting for covariates resulted in a mean difference of 0.45 kg (95% CI -0.78, 1.67) favouring the intervention group at nine month follow up. Conclusions We found no evidence that an SMS based weight maintenance intervention encouraging adults to weigh themselves weekly prevented weight regain at three or nine months after completing a commercial weight loss programme. <br/

The Efficiency of the Human CD8+ T Cell Response: How Should We Quantify It, What Determines It, and Does It Matter?

Multidisciplinary techniques, in particular the combination of theoretical and experimental immunology, can address questions about human immunity that cannot be answered by other means. From the turnover of virus-infected cells in vivo, to rates of thymic production and HLA class I epitope prediction, theoretical techniques provide a unique insight to supplement experimental approaches. Here we present our opinion, with examples, of some of the ways in which mathematics has contributed in our field of interest: the efficiency of the human CD8+ T cell response to persistent viruses

Causal Modeling Using Network Ensemble Simulations of Genetic and Gene Expression Data Predicts Genes Involved in Rheumatoid Arthritis

Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. In silico simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86 - a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28

Targeting of a CD8 T cell env epitope presented by HLA-B*5802 is associated with markers of HIV disease progression and lack of selection pressure.

In HIV-infected persons, certain HLA class I alleles are associated with effective control of viremia, while others are associated with rapid disease progression. Among the most divergent clinical outcomes are the relatively good prognosis in HLA-B*5801 expressing persons and poor prognosis with HLA-B*5802. These two alleles differ by only three amino acids in regions involved in HLA-peptide recognition. This study evaluated a cohort of over 1000 persons with chronic HIV clade C virus infection to determine whether clinical outcome differences associated with B*5801 (n = 93) and B*5802 ( n = 259) expression are associated with differences in HIV-1-specific CD8 (+) T cell responses. The overall breadth and magnitude of HIV-1-specific CD8(+) T cell responses were lower in persons expressing B*5802, and epitope presentation by B*5802 contributed significantly less to the overall response as compared to B*5801-restricted CD8 (+) T cells. Moreover, viral load in B*5802-positive persons was higher and CD4 cell counts lower when this allele contributed to the overall CD8 (+) T cell response, which was detected exclusively through a single epitope in Env. In addition, persons heterozygous for B*5802 compared to persons homozygous for other HLA-B alleles had significantly higher viral loads. Viral sequencing revealed strong selection pressure mediated through B*5801-restricted responses but not through B*5802. These data indicate that minor differences in HLA sequence can have a major impact on epitope recognition, and that selective targeting of Env through HLA-B*5802 is at least ineffectual if not actively adverse in the containment of viremia. These results provide experimental evidence that not all epitope-specific responses contribute to immune containment, a better understanding of which is essential to shed light on mechanisms involved in HIV disease progression

Knowledge Reuse Mechanisms for Categorizing Related Image Sets

. This chapter introduces the concept of classier knowledge reuse as a means of exploiting domain knowledge taken from old, previously created, relevant classiers to assist in a new classication task. Knowledge reuse helps in constructing better generalizing classiers given few training examples and for evaluating images for search in an image database. In particular, we discuss a knowledge reuse framework in which a supra-classier improves the performance of the target classi er using information from existing support classiers. Soft computing methods can be used for all three types of classiers involved. We explore supra-classier design issues and introduce several types of supra-classiers, comparing their relative strengths and weaknesses. Empirical examples on real world image data sets are used to demonstrate the eectiveness of the supra-classier framework for classi- cation and retrieval/search in image databases. Keywords: knowledge reuse, image classication, image database, curse of dimensionality, soft classiers

A survey on statistical methods for health care fraud detection

Fraud detection, Health care, Statistical methods,