The treponemes infecting lagomorphs include Treponema paraluisleporidarum ecovar Cuniculus (TPeC) and ecovar Lepus (TPeL), infecting rabbits and hares, respectively. In this study, we described the first complete genome sequence of TPeL, isolate V3603-13, from an infected mountain hare (Lepus timidus) in Sweden. In addition, we determined 99.0% of the genome sequence of isolate V246-08 (also from an infected mountain hare, Sweden) and 31.7% of the genome sequence of isolate Z27 A77/78 (from a European hare, Lepus europeaus, The Netherlands). The TPeL V3603-13 genome had considerable gene synteny with the TPeC Cuniculi A genome and with the human pathogen T. pallidum, which causes syphilis (ssp. pallidum, TPA), yaws (ssp. pertenue, TPE) and endemic syphilis (ssp. endemicum, TEN). Compared to the TPeC Cuniculi A genome, TPeL V3603-13 contained four insertions and 11 deletions longer than three nucleotides (ranging between 6 and2,932 nts). In addition, there were 25 additional indels, from one to three nucleotides long, altogether spanning 36 nts. The number of single nucleotide variants (SNVs) between TPeC Cuniculi A and TPeL V3603-13 were represented by 309 nucleotide differences. Major proteome coding differences between TPeL and TPeC were found in the tpr gene family, and (predicted) genes coding for outer membrane proteins, suggesting that these components are essential for host adaptation in lagomorph syphilis. The phylogeny revealed that the TPeL sample from the European brown hare was more distantly related to TPeC Cuniculi A than V3603-13 and V246-08.
- MeSH
- fylogeneze * MeSH
- genom bakteriální MeSH
- králíci MeSH
- syfilis * mikrobiologie MeSH
- Treponema * genetika izolace a purifikace MeSH
- zajíci * mikrobiologie MeSH
- zvířata MeSH
- Check Tag
- králíci MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Changes in the hippocampus after brain metastases radiotherapy can significantly impact neurocognitive functions. Numerous studies document hippocampal atrophy correlating with the radiation dose. This study aims to elucidate volumetric changes in patients undergoing whole-brain radiotherapy (WBRT) or targeted stereotactic radiotherapy (SRT) and to explore volumetric changes in the individual subregions of the hippocampus. METHOD: Ten patients indicated to WBRT and 18 to SRT underwent brain magnetic resonance before radiotherapy and after 4 months. A structural T1-weighted sequence was used for volumetric analysis, and the software FreeSurfer was employed as the tool for the volumetry evaluation of 19 individual hippocampal subregions. RESULTS: The volume of the whole hippocampus, segmented by the software, was larger than the volume outlined by the radiation oncologist. No significant differences in volume changes were observed in the right hippocampus. In the left hippocampus, the only subregion with a smaller volume after WBRT was the granular cells and molecular layers of the dentate gyrus (GC-ML-DG) region (median change -5 mm3, median volume 137 vs. 135 mm3; P = .027), the region of the presumed location of neuronal progenitors. CONCLUSIONS: Our study enriches the theory that the loss of neural stem cells is involved in cognitive decline after radiotherapy, contributes to the understanding of cognitive impairment, and advocates for the need for SRT whenever possible to preserve cognitive functions in patients undergoing brain radiotherapy.
- Publikační typ
- časopisecké články MeSH
PURPOSE: The aims of this work are (1) to explore deep learning (DL) architectures, spectroscopic input types, and learning designs toward optimal quantification in MR spectroscopy of simulated pathological spectra; and (2) to demonstrate accuracy and precision of DL predictions in view of inherent bias toward the training distribution. METHODS: Simulated 1D spectra and 2D spectrograms that mimic an extensive range of pathological in vivo conditions are used to train and test 24 different DL architectures. Active learning through altered training and testing data distributions is probed to optimize quantification performance. Ensembles of networks are explored to improve DL robustness and reduce the variance of estimates. A set of scores compares performances of DL predictions and traditional model fitting (MF). RESULTS: Ensembles of heterogeneous networks that combine 1D frequency-domain and 2D time-frequency domain spectrograms as input perform best. Dataset augmentation with active learning can improve performance, but gains are limited. MF is more accurate, although DL appears to be more precise at low SNR. However, this overall improved precision originates from a strong bias for cases with high uncertainty toward the dataset the network has been trained with, tending toward its average value. CONCLUSION: MF mostly performs better compared to the faster DL approach. Potential intrinsic biases on training sets are dangerous in a clinical context that requires the algorithm to be unbiased to outliers (i.e., pathological data). Active learning and ensemble of networks are good strategies to improve prediction performances. However, data quality (sufficient SNR) has proven as a bottleneck for adequate unbiased performance-like in the case of MF.
INTRODUCTION: One of the most common complications of coronavirus disease 2019 (COVID-19) is myocardial injury, and although its cause is unclear, it can alter the heart's contractility. This study aimed to characterize the ventricular and atrial strain in patients who recovered from COVID-19 using cardiovascular magnetic resonance feature-tracking (CMR-FT). METHODS: In this single-center study, we assessed left ventricle (LV) and right ventricular (RV) global circumferential strain (GCS), global longitudinal strain (GLS), global radial strain (GRS), left atrial (LA) and right atrial (RA) longitudinal strain (LS) parameters by CMR-FT. The student's t-test and Wilcoxon rank-sum test were used to compare the variables. RESULTS: We compared seventy-two patients who recovered from COVID-19 (49 ± 16 years) to fifty-four controls (49 ± 12 years, p = 0.752). The patients received a CMR examination 48 (34 to 165) days after the COVID-19 diagnosis. 28% had LGE. Both groups had normal LV systolic function. Strain parameters were significantly lower in the COVID-19 survivors than in controls. DISCUSSION: Patients who recovered from COVID-19 exhibited significantly lower strain in the left ventricle (through LVGCS, LVGLS, LVGRS), right ventricle (through RVGLS and RVGRS), left atrium (through LALS), and right atrium (through RALS) than controls.
- Publikační typ
- časopisecké články MeSH
PURPOSE: A supervised deep learning (DL) approach for frequency and phase correction (FPC) of MRS data recently showed encouraging results, but obtaining transients with labels for supervised learning is challenging. This work investigates the feasibility and efficiency of unsupervised deep learning-based FPC. METHODS: Two novel deep learning-based FPC methods (deep learning-based Cr referencing and deep learning-based spectral registration), which use a priori physics domain knowledge, are presented. The proposed networks were trained, validated, and evaluated using simulated, phantom, and publicly accessible in vivo MEGA-edited MRS data. The performance of our proposed FPC methods was compared with other generally used FPC methods, in terms of precision and time efficiency. A new measure was proposed in this study to evaluate the FPC method performance. The ability of each of our methods to carry out FPC at varying SNR levels was evaluated. A Monte Carlo study was carried out to investigate the performance of our proposed methods. RESULTS: The validation using low-SNR manipulated simulated data demonstrated that the proposed methods could perform FPC comparably with other methods. The evaluation showed that the deep learning-based spectral registration over a limited frequency range method achieved the highest performance in phantom data. The applicability of the proposed method for FPC of GABA-edited in vivo MRS data was demonstrated. Our proposed networks have the potential to reduce computation time significantly. CONCLUSIONS: The proposed physics-informed deep neural networks trained in an unsupervised manner with complex data can offer efficient FPC of large MRS data in a shorter time.
BACKGROUND: Treponema pallidum subsp. pertenue (TPE) is the causative agent of human yaws. Yaws is currently reported in 13 endemic countries in Africa, southern Asia, and the Pacific region. During the mid-20th century, a first yaws eradication effort resulted in a global 95% drop in yaws prevalence. The lack of continued surveillance has led to the resurgence of yaws. The disease was believed to have no animal reservoirs, which supported the development of a currently ongoing second yaws eradication campaign. Concomitantly, genetic evidence started to show that TPE strains naturally infect nonhuman primates (NHPs) in sub-Saharan Africa. In our current study we tested hypothesis that NHP- and human-infecting TPE strains differ in the previously unknown parts of the genomes. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we determined complete (finished) genomes of ten TPE isolates that originated from NHPs and compared them to TPE whole-genome sequences from human yaws patients. We performed an in-depth analysis of TPE genomes to determine if any consistent genomic differences are present between TPE genomes of human and NHP origin. We were able to resolve previously undetermined TPE chromosomal regions (sequencing gaps) that prevented us from making a conclusion regarding the sequence identity of TPE genomes from NHPs and humans. The comparison among finished genome sequences revealed no consistent differences between human and NHP TPE genomes. CONCLUSION/SIGNIFICANCE: Our data show that NHPs are infected with strains that are not only similar to the strains infecting humans but are genomically indistinguishable from them. Although interspecies transmission in NHPs is a rare event and evidence for current spillover events is missing, the existence of the yaws bacterium in NHPs is demonstrated. While the low risk of spillover supports the current yaws treatment campaign, it is of importance to continue yaws surveillance in areas where NHPs are naturally infected with TPE even if yaws is successfully eliminated in humans.
The MLST scheme currently used for Enterococcus faecium typing was designed in 2002 and is based on putative gene functions and Enterococcus faecalis gene sequences available at that time. As a result, the original MLST scheme does not correspond to the real genetic relatedness of E. faecium strains and often clusters genetically distant strains to the same sequence types (ST). Nevertheless, typing has a significant impact on the subsequent epidemiological conclusions and introduction of appropriate epidemiological measures, thus it is crucial to use a more accurate MLST scheme. Based on the genome analysis of 1,843 E. faecium isolates, a new scheme, consisting of 8 highly discriminative loci, was created in this study. These strains were divided into 421 STs using the new MLST scheme, as opposed to 223 STs assigned by the original MLST scheme. The proposed MLST has a discriminatory power of D = 0.983 (CI95% 0.981 to 0.984), compared to the original scheme's D = 0.919 (CI95% 0.911 to 0.927). Moreover, we identified new clonal complexes with our newly designed MLST scheme. The scheme proposed here is available within the PubMLST database. Although whole genome sequencing availability has increased rapidly, MLST remains an integral part of clinical epidemiology, mainly due to its high standardization and excellent robustness. In this study, we proposed and validated a new MLST scheme for E. faecium, which is based on genome-wide data and thus reflects the tested isolates' more accurate genetic similarity. IMPORTANCE Enterococcus faecium is one of the most important pathogens causing health care associated infections. One of the main reasons for its clinical importance is a rapidly spreading resistance to vancomycin and linezolid, which significantly complicates antibiotic treatment of infections caused by such resistant strains. Monitoring the spread and relationships between resistant strains causing severe conditions represents an important tool for implementing appropriate preventive measures. Therefore, there is an urgent need to establish a robust method enabling strain monitoring and comparison at the local, national, and global level. Unfortunately, the current, extensively used MLST scheme does not reflect the real genetic relatedness between individual strains and thus does not provide sufficient discriminatory power. This can lead directly to incorrect epidemiological measures due to insufficient accuracy and biased results.
The Pseudomonas aeruginosa population has a nonclonal epidemic structure. It is generally composed of a limited number of widespread clones selected from a background of many rare and unrelated genotypes recombining at high frequency. Due to the increasing prevalence of nosocomial infections caused by multidrug-resistant/extensively drug-resistant (MDR/XDR) strains, it is advisable to implement infection control measures. Pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) are considered the gold standard methods in bacterial typing, despite being limited by cost, staff, and instrumental demands. Here, we present a novel mini-MLST scheme for P. aeruginosa rapid genotyping based on high-resolution melting analysis. Using the proposed mini-MLST scheme, 3,955 existing sequence types (STs) were converted into 701 melting types (MelTs), resulting in a discriminatory power of D = 0.993 (95% confidence interval [CI], 0.992 to 0.994). Whole-genome sequencing of 18 clinical isolates was performed to support the newly designed mini-MLST scheme. The clonal analysis of STs belonging to MelTs associated with international high-risk clones (HRCs) performed by goeBURST software revealed that a high proportion of the included STs are highly related to HRCs and have also been witnessed as responsible for serious infections. Therefore, mini-MLST provides a clear warning for the potential spread of P. aeruginosa clones recognized as MDR/XDR strains with possible serious outcomes. IMPORTANCE In this study, we designed a novel mini-MLST typing scheme for Pseudomonas aeruginosa. Its great discriminatory power, together with ease of performance and short processing time, makes this approach attractive for prospective typing of large isolate sets. Integrating the novel P. aeruginosa molecular typing scheme enables the development and spread of MDR/XDR high-risk clones to be investigated.
- MeSH
- buněčné klony MeSH
- genotyp MeSH
- lidé MeSH
- molekulární epidemiologie metody MeSH
- multilokusová sekvenční typizace MeSH
- prospektivní studie MeSH
- pseudomonádové infekce * epidemiologie mikrobiologie MeSH
- Pseudomonas aeruginosa * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
PURPOSE: Multiple data formats in the MRS community currently hinder data sharing and integration. NIfTI-MRS is proposed as a standard spectroscopy data format, implemented as an extension to the Neuroimaging informatics technology initiative (NIfTI) format. This standardized format can facilitate data sharing and algorithm development as well as ease integration of MRS analysis alongside other imaging modalities. METHODS: A file format using the NIfTI header extension framework incorporates essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to convert single-voxel and spectroscopic imaging data to NIfTI-MRS. Visualization of data in NIfTI-MRS is provided by development of a dedicated plugin for FSLeyes, the FMRIB Software Library (FSL) image viewer. RESULTS: Online documentation and 10 example datasets in the proposed format are provided. Code examples of NIfTI-MRS readers are implemented in common programming languages. Conversion software, spec2nii, currently converts 14 formats where data is stored in image-space to NIfTI-MRS, including Digital Imaging and Communications in Medicine (DICOM) and vendor proprietary formats. CONCLUSION: NIfTI-MRS aims to solve issues arising from multiple data formats being used in the MRS community. Through a single conversion point, processing and analysis of MRS data are simplified, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. Greater standardization and harmonization become possible. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, for visualization.
Theoretical models of retinal hemodynamics showed the modulation of retinal pulsatile patterns (RPPs) by heart rate (HR), yet in-vivo validation and scientific merit of this biological process is lacking. Such evidence is critical for result interpretation, study design, and (patho-)physiological modeling of human biology spanning applications in various medical specialties. In retinal hemodynamic video-recordings, we characterize the morphology of RPPs and assess the impact of modulation by HR or other variables. Principal component analysis isolated two RPPs, i.e., spontaneous venous pulsation (SVP) and optic cup pulsation (OCP). Heart rate modulated SVP and OCP morphology (pFDR < 0.05); age modulated SVP morphology (pFDR < 0.05). In addition, age and HR demonstrated the effect on between-group differences. This knowledge greatly affects future study designs, analyses of between-group differences in RPPs, and biophysical models investigating relationships between RPPs, intracranial, intraocular pressures, and cardiovascular physiology.
- MeSH
- discus nervi optici * MeSH
- lidé MeSH
- nitrooční tlak MeSH
- pulzatilní průtok fyziologie MeSH
- srdeční frekvence MeSH
- vena centralis retinae * fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
