The phylogeographical structure of the temperate shrub Rosa pendulina at 45 locations in Europe was studied using sequencing of a non-coding cpDNA region (trnL-trnF). Our study revealed a clear geographic structure of cpDNA haplotypes. Three main haplotypes were geographically widespread, but showed little overlap in their distributions, suggesting that postglacial expansion occurred from at least two distinct glacial refugia, probably located (1) at the edge of the Alps, N Apennines or Dinaric Alps, and (2) in the Balkan Peninsula or S Carpathians. All populations at locations in the Czech Republic and surrounding regions are of Carpathian origin. This finding disproved an Alpine origin of R. pendulina populations in the Šumava Mts (Czech Republic). A contact zone between Carpathian and Alpine migration routes of R. pendulina is probably located in the Danube valley.
Cardiac resynchronization therapy (CRT) has proven efficacious
in the treatment of patients with heart failure and
dyssynchronous activation. Currently, we select suitable CRT
candidates based on the QRS complex duration (QRSd) and
morphology with left bundle branch block being the optimal
substrate for resynchronization. To improve CRT response rates,
recommendations emphasize attention to electrical parameters
both before implant and after it. Therefore, we decided to study
activation times before and after CRT on the body surface
potential maps (BSPM) and to compare thus obtained results with
data from electroanatomical mapping using the CARTO system.
Total of 21 CRT recipients with symptomatic heart failure (NYHA
II-IV), sinus rhythm, and QRSd ≥150 ms and 7 healthy controls
were studied. The maximum QRSd and the longest and shortest
activation times (ATmax and ATmin) were set in the BSPM maps
and their locations on the chest were compared with CARTO
derived time interval and site of the latest (LATmax) and earliest
(LATmin) ventricular activation. In CRT patients, all these
parameters were measured during both spontaneous rhythm and
biventricular pacing (BVP) and compared with the findings during
the spontaneous sinus rhythm in the healthy controls. QRSd was
169.7±12.1 ms during spontaneous rhythm in the CRT group and
104.3±10.2 ms after CRT (p<0.01). In the control group the
QRSd was significantly shorter: 95.1±5.6 ms (p<0.01). There
was a good correlation between LATmin(CARTO) and
ATmin(BSPM). Both LATmin and ATmin were shorter in the
control group (LATmin(CARTO) 24.8±7.1 ms and ATmin(BSPM)
29.6±11.3 ms, NS) than in CRT group (LATmin(CARTO) was
48.1±6.8 ms and ATmin(BSPM) 51.6±10.1 ms, NS). BVP
produced shortening compared to the spontaneous rhythm of
CRT recipients (LATmin(CARTO) 31.6±5.3 ms and ATmin(BSPM)
35.2±12.6 ms; p<0.01 spontaneous rhythm versus BVP). ATmax
exhibited greater differences between both methods with higher
values in BSPM: in the control group LATmax(CARTO) was
72.0±4.1 ms and ATmax (BSPM) 92.5±9.4 ms (p<0.01), in the
CRT candidates LATmax(CARTO) reached only 106.1±6.8 ms
whereas ATmax(BSPM) 146.0±12.1 ms (p<0.05), and BVP paced
rhythm in CRT group produced improvement with
LATmax(CARTO) 92.2±7.1 ms and ATmax(BSPM) 130.9±11.0 ms
(p<0.01 before and during BVP). With regard to the propagation
of ATmin and ATmax on the body surface, earliest activation
projected most often frontally in all 3 groups, whereas projection
of ATmax on the body surface was more variable. Our results
suggest that compared to invasive electroanatomical mapping
BSPM reflects well time of the earliest activation, however
provides longer time-intervals for sites of late activation.
Projection of both early and late activated regions of the heart on
the body surface is more variable than expected, very likely due
to changed LV geometry and interposed tissues between the
heart and superficial ECG electrode.
In the paper, an algorithm that allows to detect and reject outliers in a self-organizing map (SOM) has been proposed. SOM is used for data clustering as well as dimensionality reduction and the results obtained are presented in a special graphical form. To detect outliers in SOM, a genetic algorithm-based travelling salesman approach has been applied. After outliers are detected and removed, the SOM quality has to be estimated. A measure has been proposed to evaluate the coincidence of data classes and clusters obtained in SOM. A larger value of the measure means that the distance between centers of different classes in SOM is longer and the clusters corresponding to the data classes separate better. With a view to illustrate the proposed algorithm, two datasets (numerical and textual) are used in this investigation.