215 research outputs found

    The Christian Diet: A New Perspective on Food

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    The effects of vegetation density and habitat disturbance on the spatial distribution of ixodid ticks (Acari: Ixodidae)

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    Larval, nymphal, and adult Amblyomma americanum (L.), and adult Dermacentor variabilis (Say) ticks were collected using timed dragging techniques, in an attempt to examine how different habitat variables affect models that describe the distribution of ticks in Virginia, USA. Tick count data were modeled using two approaches: (i) habitat and edge, and (ii) habitat, edge, vegetation density and levels of disturbance. Nymphs and adults tended to follow a forest edge distribution when analysed by habitat and edge. Using all variables, we detected a positive relationship with forest edges and negative associations with high-density vegetation. When larvae were modeled by habitat and edge, we failed to detect associations with the edges of habitats. When all variables were included in the larval analysis, disturbed meadow edges emerged as important in the first year, and the categories of disturbed and maturing habitat in the second year. Vegetation density and levels of disturbance were marginally important towards explaining the distribution of nymphs and adults; however, levels of disturbance were potentially more important to the distribution of larvae, than habitat types. Using the habitat and edge variables, and predicted mean encounter rates for all stages of A. americanum and adult D. variabilis, we successfully cross-validated our predictions of high, moderate and low tick densities in both years. The results for nymphs and adults were combined to develop a colour-coded threat assessment map. We estimated that the majority of ticks were located on ~ 20% of the landscape. The potential uses of geographical information system-based threat maps are discussed

    Dose Ratios between High Dose Oral Morphine or Equivalents and Oral Methadone

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    Background: Methadone is a commonly used opioid in hospice and palliative care for patients with refractory pain. Various methadone dose conversion methods utilize progressively higher morphine equivalent dose (MED) to methadone dose ratios to compensate for increased methadone potency with escalating opioid doses. Objective: The purpose of this study was to determine the dose ratio between equianalgesic doses of high dose oral morphine (daily doses \u3e1200 mg morphine or MED) and oral methadone. Methods: This study was a retrospective chart review of 324 patients who received methadone at Strong Memorial Hospital or the associated outpatient clinic during a nine-month period in 2011. Ten patients met the study inclusion and exclusion criteria. A Wilcoxon signed-rank test was used to compare the pain scale scores. The Spearman correlation coefficient was used to assess level of correlation between morphine dose and methadone dose. Results: Patients rotated to methadone from high opioid doses had a two-point improvement in median pain scale scores after conversion (p=0.039). However, there was no correlation identified for patients taking daily doses \u3e1200 mg oral morphine or MED prior to methadone rotation (p=0.19). There were no reported methadone adverse effects during the study. Conclusions: No correlation was identified between high MED doses and methadone at dose stabilization after opioid rotation. A fixed maximum methadone dose of 30 mg/day produced clinically meaningful improvements in pain scores without adverse drug effects. Caution should be exercised before considering rotation to methadone doses higher than 30 mg/day in a patient receiving \u3e1200 mg oral MED/day

    Demographic and clinical predictors of trait impulsivity in Parkinson’s disease patients

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    Background: Impulsive behaviour has become increasingly recognised as a neuropsychiatric complication of Parkinson’s disease (PD). Thought to be a product of compromised cognitive control, the spectrum of impulsive behaviours in PD ranges from cognitive disinhibition to impulse control disorders (ICDs). Objective: At present, there are no indicators for trait impulsivity in PD. The objective of the current study was to identify demographic and clinical predictors of susceptibility to trait impulsivity in a cohort of PD patients. Methods: The current study assessed impulsivity using the Barratt Impulsiveness Scale 11 (BIS-11) in a cohort of 87 PD patients. General linear models (GLMs) were used to identify clinical and demographic variables predictive of heightened BIS-11 second-order attentional and nonplanning subscale scores. Results: Male gender, no history of smoking, postsecondary education, and heightened disease severity were predictive of increased BIS-11 attentional scores (p \u3c 0.05). Similarly, male gender, after secondary education, and disease severity were predictive of increased BIS-11 nonplanning scores (p \u3c 0.05). Contrary to previous reports, dopaminergic medication use was not a significant determinant of either BIS-11 subscale scores. Conclusions: Several demographic and clinical variables including male gender, no history of past smoking, after secondary education, and elevated disease severity are associated with impulsivity in PD

    Research and implementation lessons learned from a youth-targeted digital health randomized controlled trial (the ARMADILLO Study)

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    Evidence is lacking on the efficacy of sexual and reproductive health (SRH) communication interventions for youth (aged 15-24 years), especially from low- and middle-income countries. Therefore, the World Health Organization initiated the Adolescent/Youth Reproductive Mobile Access and Delivery Initiative for Love and Life Outcomes (ARMADILLO) program, a free, menu-based, on-demand text message (SMS, short message service) platform providing validated SRH content developed in collaboration with young people. A randomized controlled trial (RCT) assessing the effect of the ARMADILLO intervention on SRH-related outcomes was implemented in Kwale County, Kenya.; This paper describes the implementation challenges related to the RCT, observed during enrollment and the intervention period, and their implications for digital health researchers and program implementers.; This was an open, three-armed RCT. Following completion of a baseline survey, participants were randomized into the ARMADILLO intervention (arm 1), a once-a-week contact SMS text message (arm 2), or usual care (arm 3, no intervention). The intervention period lasted seven weeks, after which participants completed an endline survey.; Two study team decisions had significant implications for the success of the trial's enrollment and intervention implementation: a hands-off participant recruitment process and a design flaw in an initial language selection menu. As a result, three weeks after recruitment began, 660 participants had been randomized; however, 107 (53%) participants in arm 1 and 136 (62%) in arm 2 were "stuck" at the language menu. The research team called 231 of these nonengaging participants and successfully reached 136 to learn reasons for nonengagement. Thirty-two phone numbers were found to be either not linked to our participants (a wrong number) or not in their primary possession (a shared phone). Among eligible participants, 30 participants indicated that they had assumed the introductory message was a scam or spam. Twenty-seven participants were confused by some aspect of the system. Eleven were apathetic about engaging. Twenty-four nonengagers experienced some sort of technical issue. All participants eventually started their seven-week study period.; The ARMADILLO study's implementation challenges provide several lessons related to both researching and implementing client-side digital health interventions, including (1) have meticulous phone data collection protocols to reduce wrong numbers, (2) train participants on the digital intervention in efficacy assessments, and (3) recognize that client-side digital health interventions have analog discontinuation challenges. Implementation lessons were (1) determine whether an intervention requires phone ownership or phone access, (2) digital health campaigns need to establish a credible presence in a busy digital space, and (3) interest in a service can be sporadic or fleeting.; International Standard Randomized Controlled Trial Number (ISRCTN): 85156148; http://www.isrctn. com/ISRCTN85156148

    Age, sex, and socioeconomic differences in multimorbidity measured in four ways:UK primary care cross-sectional analysis

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    Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised. Aim: To examine variation in prevalence using different definitions of multimorbidity. Design and setting: Cross-sectional study of 1 168 620 people in England. Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental–physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions. Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental–physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental–physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental–physical MM at 40–45 years younger, followed by MM2+ at 15–20 years younger, and MM3+ and MM3+ from 3+ at 10–15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental–physical MM. Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies

    The impact of varying the number and selection of conditions on estimated multimorbidity prevalence::a cross-sectional study using a large, primary care population dataset

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    Background: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. Methods and findings: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of “comorbidity.” Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. Conclusions: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence

    Elevated serum homocysteine levels have differential gender-specific associations with motor and cognitive states in Parkinson’s disease

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    Background: Studies attempting to elucidate an association between homocysteine and symptom progression in Parkinson’s disease (PD) have had largely discrepant findings. This study aimed to investigate elevated serum homocysteine levels and symptom progression in a cohort of PD patients. Methods: Serum homocysteine, folate, and vitamin B12 levels were measured in 205 people with PD and 78 age-matched healthy controls. People with Parkinson’s disease underwent a battery of clinical assessments to evaluate symptom severity, including motor (MDS-UPDRS) and cognitive (ACE-R) assessments. Multivariate generalized linear models were created, controlling for confounding variables, and were used to determine whether serum markers are associated with various symptom outcome measures. Results; People with Parkinson’s disease displayed significantly elevated homocysteine levels (p\u3c0.001), but not folate or vitamin B12 levels, when compared to healthy controls. A significant positive correlation between homocysteine and MDS-UPDRS III score was identified in males with Parkinson’s disease (rs=0.319, p\u3c0.001), but not in females, whereas a significant negative correlation between homocysteine levels and total ACE-R score was observed in females with Parkinson’s disease (rs=−0.449, p\u3c0.001), but not in males. Multivariate general linear models confirmed that homocysteine was significantly predictive of MDS-UPDRSIII score in male patients (p = 0.004) and predictive of total ACE-R score in female patients (p = 0.021). Conclusion: Elevated serum homocysteine levels are associated with a greater motor impairment in males with Parkinson’s disease and poorer cognitive performance in females with Parkinson’s disease. Our gender specific findings may help to explain previous discrepancies in the literature surrounding the utility of homocysteine as a biomarker in PD

    IGG3 Subclass Antibodies Recognize Antigenically Drifted Influenza Viruses and SARS-CoV-2 Variants Through Efficient Bivalent Binding

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    The constant domains of antibodies are important for effector functions, but less is known about how they can affect binding and neutralization of viruses. Here, we evaluated a panel of human influenza virus monoclonal antibodies (mAbs) expressed as IgG1, IgG2, or IgG3. We found that many influenza virus-specific mAbs have altered binding and neutralization capacity depending on the IgG subclass encoded and that these differences result from unique bivalency capacities of the subclasses. Importantly, subclass differences in antibody binding and neutralization were greatest when the affinity for the target antigen was reduced through antigenic mismatch. We found that antibodies expressed as IgG3 bound and neutralized antigenically drifted influenza viruses more effectively. We obtained similar results using a panel of SARS-CoV-2-specific mAbs and the antigenically advanced B.1.351 and BA.1 strains of SARS-CoV-2. We found that a licensed therapeutic mAb retained neutralization breadth against SARS-CoV-2 variants when expressed as IgG3, but not IgG1. These data highlight that IgG subclasses are not only important for fine-tuning effector functionality but also for binding and neutralization of antigenically drifted viruses
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