Asthma Prevalence, Knowledge, and Perceptions among Secondary School Pupils in Rural and Urban Costal Districts in Tanzania.

Asthma is a common chronic disease of childhood that is associated with significant morbidity and mortality. We aimed to estimate the prevalence of asthma among secondary school pupils in urban and rural areas of coast districts of Tanzania. The study also aimed to describe pupils' perception towards asthma, and to assess their knowledge on symptoms, triggers, and treatment of asthma. A total of 610 pupils from Ilala district and 619 pupils from Bagamoyo district formed the urban and rural groups, respectively. Using a modified International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire, a history of "diagnosed" asthma or the presence of a wheeze in the previous 12 months was obtained from all the studied pupils, along with documentation of their perceptions regarding asthma. Pupils without asthma or wheeze in the prior 12 months were subsequently selected and underwent a free running exercise testing. A >= 20% decrease in the post-exercise Peak Expiratory Flow Rate (PEFR) values was the criterion for diagnosing exercise-induced asthma. The mean age of participants was 16.8 (+/-1.8) years. The prevalence of wheeze in the past 12 months was 12.1% in Bagamoyo district and 23.1% in Ilala district (p < 0.001). Self-reported asthma was found in 17.6% and 6.4% of pupils in Ilala and Bagamoyo districts, respectively (p < 0.001). The prevalence of exercise-induced asthma was 2.4% in Bagamoyo, and 26.3% in Ilala (P < 0.002). In both districts, most information on asthma came from parents, and there was variation in symptoms and triggers of asthma reported by the pupils. Non-asthmatic pupils feared sleeping, playing, and eating with their asthmatic peers. The prevalence rates of self-reported asthma, wheezing in the past 12 months, and exercise-induced asthma were significantly higher among urban than rural pupils. Although bronchial asthma is a common disease, pupils' perceptions about asthma were associated with fear of contact with their asthmatic peers in both rural and urban schools

Preoperative systemic inflammation predicts postoperative infectious complications in patients undergoing curative resection for colorectal cancer

The presence of systemic inflammation before surgery, as evidenced by the glasgow prognostic score (mGPS), predicts poor long-term survival in colorectal cancer. The aim was to examine the relationship between the preoperative mGPS and the development of postoperative complications in patients undergoing potentially curative resection for colorectal cancer. Patients (n=455) who underwent potentially curative resections between 2003 and 2007 were assessed consecutively, and details were recorded in a database. The majority of patients presented for elective surgery (85%) were over the age of 65 years (70%), were male (58%), were deprived (53%), and had TNM stage I/II disease (61%), had preoperative haemoglobin (56%), white cell count (87%) and mGPS 0 (58%) in the normal range. After surgery, 86 (19%) patients developed a postoperative complication; 70 (81%) of which were infectious complications. On multivariate analysis, peritoneal soiling (P&#60;0.01), elevated preoperative white cell count (P&#60;0.05) and mGPS (P&#60;0.01) were independently associated with increased risk of developing a postoperative infection. In elective patients, only the mGPS (OR=1.75, 95% CI=1.17-2.63, P=0.007) was significantly associated with increased risk of developing a postoperative infection. Preoperative elevated mGPS predicts increased postoperative infectious complications in patients undergoing potentially curative resection for colorectal cancer

Is Gly16Arg β₂ Receptor Polymorphism Related to Impulse Oscillometry in a Real-Life Asthma Clinic Setting?

PURPOSE: We evaluated whether Gly16Arg beta2-receptor genotype relates to impulse oscillometry (IOS) in a real-life clinic setting. METHODS: Patients with persistent asthma taking inhaled corticosteroid ± long-acting beta-agonist (ICS ± LABA) were evaluated. We compared genotype groups comprising either no Arg copies (i.e. GlyGly) versus one or two Arg copies (i.e. ArgArg or ArgGly). IOS outcomes included total airway resistance at 5 Hz (R5), central airway resistance at 20 Hz (R20), peripheral airway resistance (R5–R20), reactance at 5 Hz, area under reactance curve (AX) and resonant frequency (RF). In addition, we recorded ACQ-5 and salbutamol use. RESULTS: One hundred and twelve ICS-treated asthmatic patients (mean ICS dose 1238 µg/day), mean age 43 years, ACQ 2.34, FEV1 82 %, R5 177 % were identified—89 were also taking LABA. 61 patients were GlyGly, while 14 were ArgArg and 37 were ArgGly. There were no significant differences in IOS outcomes, ACQ or salbutamol use between the genotypes. The allelic risk (as odds ratio) for less well-controlled asthma (as ACQ > 1.5) was 1.1 (95 % CI 0.72–1.68) in relation to each Arg copy with a corresponding odds ratio for abnormal R5–R20 > 0.07kPA/l.s being 0.91 (95 % CI 0.57–1.44). 71 % of patients had an ACQ > 1.5 in the GlyGly group, versus 67 % in GlyArg/ArgArg group, with corresponding figures for abnormal R5–R20 > 0.07 kPa/l.s being 69 versus 73 %. CONCLUSION: In a real-life clinic setting for patients with poorly controlled persistent asthma taking ICS ± LABA, we found no evidence of any relationship of Gly16Arg to IOS, ACQ or salbutamol use

Design and feasibility testing of a novel group intervention for young women who binge drink in groups

BackgroundYoung women frequently drink alcohol in groups and binge drinking within these natural drinking groups is common. This study describes the design of a theoretically and empirically based group intervention to reduce binge drinking among young women. It also evaluates their engagement with the intervention and the acceptability of the study methods.MethodsFriendship groups of women aged 18–35 years, who had two or more episodes of binge drinking (>6 UK units on one occasion; 48g of alcohol) in the previous 30 days, were recruited from the community. A face-to-face group intervention, based on the Health Action Process Approach, was delivered over three sessions. Components of the intervention were woven around fun activities, such as making alcohol free cocktails. Women were followed up four months after the intervention was delivered. Results The target of 24 groups (comprising 97 women) was recruited. The common pattern of drinking was infrequent, heavy drinking (mean consumption on the heaviest drinking day was UK 18.1 units). Process evaluation revealed that the intervention was delivered with high fidelity and acceptability of the study methods was high. The women engaged positively with intervention components and made group decisions about cutting down. Twenty two groups set goals to reduce their drinking, and these were translated into action plans. Retention of individuals at follow up was 87%.ConclusionsThis study successfully recruited groups of young women whose patterns of drinking place them at high risk of acute harm. This novel approach to delivering an alcohol intervention has potential to reduce binge drinking among young women. The high levels of engagement with key steps in the behavior change process suggests that the group intervention should be tested in a full randomised controlled trial

Dynamic modeling of mean-reverting spreads for statistical arbitrage

Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean-reverting spreads enjoying a certain degree of predictability. Gaussian linear state-space processes have recently been proposed as a model for such spreads under the assumption that the observed process is a noisy realization of some hidden states. Real-time estimation of the unobserved spread process can reveal temporary market inefficiencies which can then be exploited to generate excess returns. Building on previous work, we embrace the state-space framework for modeling spread processes and extend this methodology along three different directions. First, we introduce time-dependency in the model parameters, which allows for quick adaptation to changes in the data generating process. Second, we provide an on-line estimation algorithm that can be constantly run in real-time. Being computationally fast, the algorithm is particularly suitable for building aggressive trading strategies based on high-frequency data and may be used as a monitoring device for mean-reversion. Finally, our framework naturally provides informative uncertainty measures of all the estimated parameters. Experimental results based on Monte Carlo simulations and historical equity data are discussed, including a co-integration relationship involving two exchange-traded funds.Comment: 34 pages, 6 figures. Submitte

Male breast cancer

Male breast cancer (MBC) is a rare disease representing less than 1% of all breast cancers (BC) and less than 1% of cancers in men. Age at presentation is mostly in the late 60s. MBC is recognized as an estrogen-driven disease, specifically related to hyperestrogenism. About 20% of MBC patients have family history for BC. Mutations in BRCA1 and, predominantly, BRCA2, account for approximately 10% of MBC cases. Because of its rarity, MBC is often compared with female BC (FBC). Based on age-frequency distribution, age-specific incidence rate patterns and prognostic factors profiles, MBC is considered similar to late-onset, postmenopausal estrogen/progesterone receptor positive (ER+/PR+) FBC. However, clinical and pathological characteristics of MBC do not exactly overlap FBC. Compared with FBC, MBC has been reported to occur later in life, present at a higher stage, and display lower histologic grade, with a higher proportion of ER+ and PR+ tumors. Although rare, MBC remains a substantial cause for morbidity and mortality in men, probably because of its occurrence in advanced age and delayed diagnosis. Diagnosis and treatment of MBC generally is similar to that of FBC. Men tend to be treated with mastectomy rather than breast-conserving surgery. The backbone of adjuvant therapy or palliative treatment for advanced disease is endocrine, mostly tamoxifen. Use of FBC-based therapy led to the observation that treatment outcomes for MBC are worse and that survival rates for MBC do not improve like FBC. These different outcomes may suggest a non-appropriate utilization of treatments and that different underlying pathogenetic mechanisms may exist between male and female BC

Forgetting having denied: The "amnesic" consequences of denial

The concept of denial has its roots in psychoanalysis. Denial has been assumed to be effective in blocking unwanted memories. In two experiments, we report that denial has unique consequences for remembering. In two experiments, participants viewed a video of a theft and half of the participants had to deny seeing certain details in the video whereas the other half had to tell the truth. One day later, all participants were given a source monitoring recognition or recall task. In these tasks, they were instructed to indicate (1) whether they could remember talking about certain details and (2) whether they could recollect seeing those details in the video. In both experiments, we found that denial made participants forget that they talked about these details while leaving memory for the video unaffected. This denial-induced forgetting was evident for both the source monitoring recognition and recall tests. Furthermore, when we asked participants after the experiment whether they could still not remember talking about these details, participants who had to deny were most likely to report that they forgot this. In contrast to a widely held belief, we show that denial does not impair memory for the experienced stimuli, but that it has a unique ability to undermine memory for what was talked about

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitud