Detailed phenotypic and genotypic characterization of bietti crystalline dystrophy

OBJECTIVE: To provide a detailed phenotype/genotype characterization of Bietti crystalline dystrophy (BCD). DESIGN: Observational case series. PARTICIPANTS: Twenty patients from 17 families recruited from a multiethnic British population. METHODS: Patients underwent color fundus photography, near-infrared (NIR) imaging, fundus autofluorescence (FAF) imaging, spectral domain optical coherence tomography (SD-OCT), and electroretinogram (ERG) assessment. The gene CYP4V2 was sequenced. MAIN OUTCOME MEASURES: Clinical, imaging, electrophysiologic, and molecular genetics findings. RESULTS: Patients ranged in age from 19 to 72 years (median, 40 years), with a visual acuity of 6/5 to perception of light (median, 6/12). There was wide intrafamilial and interfamilial variability in clinical severity. The FAF imaging showed well-defined areas of retinal pigment epithelium (RPE) loss that corresponded on SD-OCT to well-demarcated areas of outer retinal atrophy. Retinal crystals were not evident on FAF imaging and were best visualized with NIR imaging. Spectral domain OCT showed them to be principally located on or in the RPE/Bruch's membrane complex. Disappearance of the crystals, revealed by serial recording, was associated with severe disruption and thinning of the RPE/Bruch's membrane complex. Cases with extensive RPE degeneration (N = 5) had ERGs consistent with generalized rod and cone dysfunction, but those with more focal RPE atrophy showed amplitude reduction without delay (N = 3), consistent with restricted loss of function, or that was normal (N = 2). Likely disease-causing variants were identified in 34 chromosomes from 17 families. Seven were novel, including p.Met66Arg, found in all 11 patients from 8 families of South Asian descent. This mutation appears to be associated with earlier onset (median age, 30 years) compared with other substitutions (median age, 41 years). Deletions of exon 7 were associated with more severe disease. CONCLUSIONS: The phenotype is highly variable. Several novel variants are reported, including a highly prevalent substitution in patients of South Asian descent that is associated with earlier-onset disease. Autofluorescence showed sharply demarcated areas of RPE loss that coincided with abrupt edges of outer retinal atrophy on SD-OCT; crystals were generally situated on or in the RPE/Bruch's complex but could disappear over time with associated RPE disruption. These results support a role for the RPE in disease pathogenesis.

Increasing the variability of centre frequency locations in multiple-band sigma-delta modulators via the use of fractional delay filters

This paper presents the design analysis of novel tunable narrow-band bandpass sigma-delta modulators, that can achieve concurrent multiple noise-shaping for multi-tone input signals. This approach utilises conventional comb filters in conjunction with FIR, or allpass IIR fractional delay filters, to deliver the desired nulls for the quantisation noise transfer function. Detailed simulation results show that FIR fractional delay comb filter based sigma-delta modulators tune accurately to most centre frequencies, but suffer from degraded resolution at frequencies close to Nyquist. However, superior accuracies are obtained from their allpass IIR fractional delay counterpart at the expense of a slight shift in noise-shaping bands at very high frequencies.

The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency

Objective: The Finometer (FMS, Finapres Measurement Systems, Amsterdam) records the beat-to-beat finger pulse contour and has been recommended for research studies assessing shortterm changes of blood pressure and its variability. Variability measured in the frequency domain using spectral analysis requires that the impact of breathing be restricted to high frequency spectra (> 0.15 Hz) so data from participants needs to be excluded when the breathing impact occurs in the low frequency spectra (0.04 - 0.15 Hz). This study tested whether breathing frequency can be estimated from standard Finometer recordings using either stroke volume oscillation frequency or spectral stroke volume variability maximum scores. Methods: 22 healthy volunteers were tested for 270s in the supine and upright positions. Finometer recorded the finger pulse contour and a respiratory transducer recorded breathing. Stoke volume oscillation frequency was calculated manually while the stroke volume spectral maximums were obtained using the software Cardiovascular Parameter Analysis (Nevrokard Kiauta, Izola, Slovenia). These estimates were compared to the breathing frequency using the Bland-Altman procedures. Results: Stroke volume oscillation frequency estimated breathing frequency to <±10% 95% levels of agreement in both supine (-7.7 to 7.0%) and upright (-6.7 to 5.4%) postures. Stroke volume variability maximum scores did not accurately estimate breathing frequency. Conclusions: Breathing frequency can be accurately derived from standard Finometer recordings using stroke volume oscillations for healthy individuals in both supine and upright postures. The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency.

Respiratory and non-respiratory sinus arrhythmia: implications for heart rate variability

The quantity of blood arriving at the left side of the heart oscillates throughout the breathing cycle due to the mechanics of breathing. Neurally regulated fluctuations in the length of the heart period act to dampen oscillations of the left ventricular stroke volume entering the aorta. We have reported that stroke volume oscillations but not spectral frequency variability stroke volume measures can be used to estimate the breathing frequency. This study investigated with the same recordings whether heart period oscillations or spectral heart rate variability measures could function as estimators of breathing frequency. Continuous 270 s cardiovascular recordings were obtained from 22 healthy adult volunteers in the supine and upright postures. Breathing was recorded simultaneously. Breathing frequency and heart period oscillation frequency were calculated manually, while heart rate variability spectral maximums were obtained using heart rate variability software. These estimates were compared to the breathing frequency using the Bland–Altman agreement procedure. Estimates were required to be \±10% (95% levels of agreement). The 95% levels of agreement measures for the heart period oscillation frequency (supine: -27.7 to 52.0%, upright: -37.8 to 45.9%) and the heart rate variability spectral maximum estimates (supine: -48.7 to 26.5% and -56.4 to 62.7%, upright: -37.8 to 39.3%) exceeded 10%. Multiple heart period oscillations were observed to occur during breathing cycles. Both respiratory and non-respiratory sinus arrhythmia was observed amongst healthy adults. This observation at least partly explains why heart period parameters and heart rate variability parameters are not reliable estimators of breathing frequency. In determining the validity of spectral heart rate variability measurements we suggest that it is the position of the spectral peaks and not the breathing