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An analysis plan or strategy should be developed before any analysis is undertaken to ensure that the modelling is hypothesis-led rather than data-driven. The a priori model-fitting analysis strategy should identify:

the covariates which are to be considered for inclusion in any modelling approach to analysis

the order in which confounding variables are to be considered for inclusion in the model with the intervention variable fitted last (or an ‘intervention × phase’ interaction if pre- and post-measurements have been taken). 14

An example of a model-fitting analysis strategy which could have been used for the URGE data is displayed in Figure 1.

Multilevel modelling was undertaken for the URGE study using the software package MLWin, developed by the Institute of Education in London (Table 2). As outlined above, an a priori model-fitting analysis strategy was developed which identified the order in which covariates were to be included in the model. Only after all covariates were included in the model was the effect of the ‘intervention × phase’ interaction examined. After adjustment for the pre-identified covariates, the interaction remained significant. The effect size estimated from the multilevel model was 0.70 (95% CI: 0.55–0.91). The resulting t -ratio was t = 2.71, P = 0.01. This indicates that when all the data are used in the analysis, the waiting time was on average 30% less in the guideline group compared with the control group (Table 2).

An in-depth discussion of all the available modelling methods is beyond the scope of this article. Researchers should refer to specific texts such as Murray 2 for a general introduction to possible methods, or to Kreft and de Leeuw 15 for discussion of multilevel models. Similarly, a range of statistical software packages are available for the analysis of clustered data sets. A discussion of the more common packages can be found on the multilevel modelling web site: Mens Leather Casual Shoes Dress Autumn Personality Wedding Fashion Slip On Red Red free shipping shopping online 2014 newest sale online clearance Manchester S7bGg0Mh
. For a discussion of generalized estimating equations, readers should refer to Burton et al. 16

These modelling techniques adjust well for clustering and allow adjustment for both cluster level and patient level covariates. These types of analyses are more computationally intensive, however, and require greater statistical expertise both in the execution of the procedures and in the interpretation of the results.

With the increasing popularity of the cluster randomized trial, it is important that researchers be aware of the implications of adopting such a design. Cluster RCTs are more complex to undertake than patient randomized trials in that they require increased sample sizes, with associated recruitment issues, and the analysis of these trials is not so straightforward. Cluster trials are the gold standard design for some interventions, however, and it is important that researchers have the information to design and analyse them appropriately.

In the multicellular preparations of the myocardium isolated from the epicardial border zone of the 5-day infarcted heart, the following abnormalities have been described: a decrease in resting potential, total AP amplitude and V̇ max , a reduction in AP duration at both 50 and 90% repolarization and a loss in the plateau potentials ( Fig. 1 ) [5] . However, when the cells of the epicardial border zone are dispersed and studied as isolated myocytes in vitro [10] , the resting potential is no different than control suggesting that other factors control resting membrane potential in the multicellular preparation. One likely factor may be extracellular ion accumulation, since in single cells electrical activity is studied after it is removed from the syncytium and superfused in an environment where immediate extracellular ion accumulation and depletion are not significant.

While resting potentials of the 5-day myocytes are similar to control values, APs of these myocytes show changes in the repolarization during the terminal portion of phase 3. Net membrane currents are significantly different between cell groups but I K1 appears to differ only at hyperpolarized potentials ( Fig. 2 ).

Fig. 2
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Average ‘steady-state’ net membrane current density voltage-relations of normal (NZVM, =28, filled circles) and 5-day infarct (IZVM, =44, unfilled circles) ventricular myocytes in nisoldipine-containing Tyrode’s solution. Currents were measured at the end of a 440-ms pulse from a holding potential of −40 mV to various test potentials (). Average capacitance of cells was 123±6 pF (NZVM) and 179±7 pF (IZVM) (<0.05). Note that the isochronal – curve of NZVM had a pronounced n-shape, compared to that of IZVM. The average resting potential −87±3 mV and −83±3 mV for NZVM and IZVM, respectively. For all IZVM studied, the average – differed from NZVM at test voltages −110 to −95 mV and at −80 to −30 mV. Inset shows cesium (Cs, 20 mM)-sensitive currents in a subset of cells (NZVM, =12; IZVM, =24). Cs-sensitive currents were n-shaped in both groups, depicting the – of the underlying (zero intercepts, NZVM=−90±2 mV; IZVM=−93±1 mV, >0.05). There was a significant reduction in IZVM density in the −110 to −90 mV range. * indicates significance at <0.05.

Fig. 2
View large Download slide

Average ‘steady-state’ net membrane current density voltage-relations of normal (NZVM, =28, filled circles) and 5-day infarct (IZVM, =44, unfilled circles) ventricular myocytes in nisoldipine-containing Tyrode’s solution. Currents were measured at the end of a 440-ms pulse from a holding potential of −40 mV to various test potentials (). Average capacitance of cells was 123±6 pF (NZVM) and 179±7 pF (IZVM) (<0.05). Note that the isochronal – curve of NZVM had a pronounced n-shape, compared to that of IZVM. The average resting potential −87±3 mV and −83±3 mV for NZVM and IZVM, respectively. For all IZVM studied, the average – differed from NZVM at test voltages −110 to −95 mV and at −80 to −30 mV. Inset shows cesium (Cs, 20 mM)-sensitive currents in a subset of cells (NZVM, =12; IZVM, =24). Cs-sensitive currents were n-shaped in both groups, depicting the – of the underlying (zero intercepts, NZVM=−90±2 mV; IZVM=−93±1 mV, >0.05). There was a significant reduction in IZVM density in the −110 to −90 mV range. * indicates significance at <0.05.

Investigations of changes in the electrical function in the healing or healed infarct (weeks to months) include studies of cells overlying the infarct scar, known as the central ‘infarct zone’ cells, and those of the surrounding thin rim of cells called the lateral adjacent ‘border zone’ cells. In the feline healed infarct model, 50% of the hearts have ectopic activity [11,12] . The site of origin of these arrhythmias is not known but may be from cells within the healed border zone.

For each compartment (blood, CSF), the time of viral rebound was estimated as the midpoint between the last undetectable HIV RNA viral load (or date of ART interruption if participant interrupted ART before the first study visit), and the first detectable HIV RNA viral load in blood or CSF supernatant respectively.

Study participants ( N  = 14) were HIV-infected individuals with a median age of 41 years (interquartile range [IQR]: [37–45]), who had been receiving ART for a median of 4 years (IQR: 1.7–8.5 years) and voluntarily interrupted therapy between February 1999 and December 2005. Characteristics of the study participants are summarized in Table 1 .

Table 1.

Characteristics at baseline (14 individuals).

HIV, human immunodeficiency virus; ART, antiretroviral therapy; IQR, interquartile range; CSF, cerebrospinal fluid.

HIV RNA levels at the time of sampling for time point 1.

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Table 1.

Characteristics at baseline (14 individuals).

HIV, human immunodeficiency virus; ART, antiretroviral therapy; IQR, interquartile range; CSF, cerebrospinal fluid.

HIV RNA levels at the time of sampling for time point 1.

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Ten participants had documented undetectable HIV RNA levels for at least 2 years (prospective Group 1) or 6 months (retrospective Group 2) before ART interruption. For the remaining four participants (convenience cohort), duration of HIV RNA suppression before treatment interruption was uncertain. Rebound dynamics of HIV RNA in blood plasma and CSF supernatant for five participants belonging to Group 1 are showed in Fig. 1 .

Figure 1.
View large Download slide

Dynamics of HIV RNA rebound in CSF supernatant (blue) and blood plasma (red) for five participants belonging to group 1 (prospective cohort). Each dot represents a study visit with blood and CSF collection. Time points used for sequence analysis are indicated with arrows. X axis shows time after interruption of ART (in days), Y axis shows HIV RNA viral load (log10).

Figure 1.
View large Download slide

Dynamics of HIV RNA rebound in CSF supernatant (blue) and blood plasma (red) for five participants belonging to group 1 (prospective cohort). Each dot represents a study visit with blood and CSF collection. Time points used for sequence analysis are indicated with arrows. X axis shows time after interruption of ART (in days), Y axis shows HIV RNA viral load (log10).

The median time from ART interruption to viral rebound in blood plasma was 19 days (IQR: 8–31 days), while the median time from ART interruption to viral rebound in CSF supernatant was 30 days (IQR: 16–44 days). The median time from viral rebound to HIV RNA sampling in blood plasma (referred as Time point 1) was 24 days (IQR: 20–87 days), while the median time from viral rebound (within the CSF compartment) to HIV RNA sampling in CSF supernatant (Time point 1) was 14 days (IQR: 4–87 days). Since our study was primarily interested in analyzing viral rebound in CSF, the earliest available time points at which HIV RNA levels were sufficient for sequence analysis were included as Time point 1. Because of the characteristic delay between rebound in blood and CSF, HIV RNA levels in blood had plateaued and were no longer substantially increasing during this time period (see Fig. 1 ). At Time point 1, median CD4 T cell count was 412 cells/μl [IQR: 397–476] and HIV RNA levels in blood and CSF supernatant were 4.7 log 10 (copies/ml) [IQR: 4.2–5.1] and 3.3 log 10 (copies/ml) [IQR: 2.7–3.8], respectively. With the exception of participant 34535, we sampled HIV RNA from blood and CSF supernatant for one or more additional time points (referred as Time points 2–5) after a median of 55 days from Time point 1 (IQR: 9–364 days). For participants 34535, 26919 and 25839, plasma and CSF supernatant were available from a time point preceding the initiation of ART.

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The Twenty-Third Annual Conference of the Association of Mathematics Teacher Educators will be held February 7 – 9, 2019, in Orlando, Florida.The conference sessions will begin Thursday morning.

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was Tuesday, May 15, 201811:59 PDT.

For 2018, the AMTE Board named the following priorities:

We encourage proposal writers to highlight connections to these priorities as well as the AMTE Standards for Preparing Teachers of Mathematics (as appropriate) when submitting proposals to any of the nine presentation strands.

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All presenters must register for the conference by Sept 15, 2018, or their session may be canceled.

Presentations focused on practice and/or research in mathematics teacher education are welcome. Sessions related to practice may include presenting or sharing resources for mathematics teacher educators. During the submission process, you will be asked to classify your presentation into one of the following strands that most closely aligns with your topic.

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Development of Mathematics Teacher Educators

Sessions related to the preparation of individuals (e.g., teacher leaders, university faculty, consultants, mathematics specialists) to serve as mathematics teacher educators in K-12 schools, institutions of higher learning, or other organizations. Includes efforts related to the continuing professional development of mathematics teacher educators.

Sessions related to equity, diversity and social justice in mathematics teacher education. Includes efforts related to access, inclusion, respectful and fair engagement with others, and advocating for a more just and equitable mathematics education free of systemic forms of inequality such as those based on race, class, language, national origin, culture, gender, age, sexual orientation, religion, and dis/ability.

Sessions related to the work of preparing coaches, specialists, and teachers (preservice and/or inservice) in the realm of mathematics content, processes, and/or practices. Includes efforts undertaken in content courses and content-based professional development.

Sessions related to national or international policy as well as programmatic issues in mathematics education. Includes efforts focused on position statements, calls for action, national and state standards, accreditation, pathways towards teacher certification, and teacher education programs.

Sessions related to the work of preparing coaches, specialists, and teachers (preservice and/or inservice) in the realm of mathematics pedagogy and instructional practice. Includes efforts undertaken in methods courses and pedagogically-focused professional development.

Sessions related to the experiences and impact of preservice teachers attending and working in K-12 school settings in mathematics education. Includes those that address early field experiences as well as student teaching and internships.

Sessions related to collaborations between K-12 schools and institutions of higher learning in mathematics education. Includes a focus on the aspects related to mathematics teacher education within these projects or partnerships.

Sessions related to the content and/or structure of, environments for, or policies surrounding professional development work with mathematics teachers, administrators, and other school personnel engaged in teacher leadership. Includes reports on teachers engaged in structured self-inquiry such as lesson study and action research.

Sessions related to the use of technology in teaching and learning in mathematics teacher education. Includes efforts related to Technological Pedagogical Content Knowledge (TPACK). Please read the NTLI Fellowship description below .

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