Patients with senile pruritus have a distinct skin microbiota and epidermal barrier in comparison with healthy controls

Objective The skin is the second most affected organ after articular involvement in systemic lupus erythematosus (SLE) patients. Cutaneous involvement occurs in approximately 80% of patients during the course of SLE. Interaction between the host and skin microorganism is a complex process. There are few studies on the diversity of skin microbes in SLE patients. Therefore, this study aims to explore the relationship between skin microorganisms and SLE. Methods A total of 20 SLE patients, 20 controls with rosacea and 20 healthy controls were selected as study subjects. Both the skin microbiota of rash region and non-rash region for each SLE patient were collected.16S rRNA gene sequencing was used to detected skin microbiota from 80 specimens. α-Diversity and β-diversity of skin microbiota were analyzed based on operational taxonomic units (OTUs) and minimal entropy decomposition (MED). Using Wilcoxon test and Linear Discriminate Analysis Effect Size (LEfSe), skin microbial diversity and composition were analyzed. Functional capabilities of microbiota were estimated through Kyoto Encyclopedia of Genes and Genomes database. Results Compared to rash region of SLE, diversity and richness were increased in healthy controls, and decreased in non-rash region of SLE and rash region of controls with rosacea. Additionally, changes of skin microbial composition were found at different taxonomic levels between four groups. For example, genus Halomonas was increased and genera Pelagibacterium, Novosphingobium, and Curvibacter were decreased in rash region compared to non-rash region of SLE based on OTUs and MED. Based on OTUs, metabolic pathways were also found differences in SLE patients, such as Xenobiotics Biodegradation and Metabolism. Conclusion Compositions and diversity of skin microbiota in SLE patients are changed. This pilot study provides some suggestive evidence for further exploration of skin microbiota in SLE patients with cutaneous involvement.

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The Effect of Intense Pulsed Light on the Skin Microbiota and Epidermal Barrier in Patients with Mild to Moderate Acne Vulgaris

Lasers in Surgery and Medicine ◽

10.1002/lsm.23426 ◽

2021 ◽

Author(s):

Jiexiong Liu ◽

Lu Liu ◽

Lin Zhou ◽

Lingna Chen ◽

Xia Chen ◽

...

Keyword(s):

Acne Vulgaris ◽

Intense Pulsed Light ◽

Pulsed Light ◽

Skin Microbiota ◽

Epidermal Barrier

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Characterization of skin microbiota in patients with atopic dermatitis and in normal subjects using 16S rRNA gene-based comprehensive analysis

Journal of Medical Microbiology ◽

10.1099/jmm.0.47268-0 ◽

2007 ◽

Vol 56 (12) ◽

pp. 1675-1683 ◽

Cited By ~ 54

Author(s):

Itaru Dekio ◽

Mitsuo Sakamoto ◽

Hidenori Hayashi ◽

Masayuki Amagai ◽

Makoto Suematsu ◽

...

Keyword(s):

Atopic Dermatitis ◽

16S Rrna ◽

16S Rrna Gene ◽

Bacterial Species ◽

Rrna Genes ◽

Rrna Gene ◽

Healthy Controls ◽

Skin Microbiota ◽

Micro Organisms ◽

Normal Controls

A previous study using bacterial 16S rRNA gene-based clone libraries revealed that the microbiota in healthy human skin included uncultured micro-organisms, although the micro-organisms in skin exposed to disease conditions remain to be examined. To compare the profiles of skin microbiota in 13 patients with atopic dermatitis (AD) and 10 healthy controls, terminal RFLP analysis of bacterial 16S rRNA genes was applied to 23 swab-scrubbed samples from facial skin. This culture-independent analysis successfully revealed the complex bacterial members of the microbiota as peak patterns following capillary electrophoresis of terminal restriction fragments (T-RFs). Each T-RF peak reflected a micro-organism, and the micro-organism to which each peak was assigned could be identified by computer simulation of T-RF length using the nucleotide sequence data of bacterial species residing in the skin. Among 18 species detected in the study, Stenotrophomonas maltophilia was detected significantly more commonly in AD patients (5/13 for AD patients vs 0/10 for controls), whilst Dietzia maris was detected significantly more commonly in normal controls (8/10 for controls vs 2/13 for AD patients). Moreover, Streptococcus species, which are considered to be uncommon in uninfected skin, were detected in seven patients and eight normal controls. Although further studies should be undertaken to investigate the roles of these micro-organisms in AD, the microbiota were presumed to include hitherto uninvestigated bacterial species in the major population of patients with AD and of healthy controls.

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Automated Acoustic Analysis of Oral Diadochokinesis to Assess Bulbar Motor Involvement in Amyotrophic Lateral Sclerosis

Journal of Speech Language and Hearing Research ◽

10.1044/2019_jslhr-19-00178 ◽

2020 ◽

Vol 63 (1) ◽

pp. 59-73 ◽

Cited By ~ 3

Author(s):

Panying Rong

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Acoustic Analysis ◽

Speaking Rate ◽

Disease Stage ◽

Healthy Controls ◽

Tongue Movement ◽

Major Barrier ◽

Syllable Repetition ◽

Oral Diadochokinesis ◽

Lateral Sclerosis

Purpose The purpose of this article was to validate a novel acoustic analysis of oral diadochokinesis (DDK) in assessing bulbar motor involvement in amyotrophic lateral sclerosis (ALS). Method An automated acoustic DDK analysis was developed, which filtered out the voice features and extracted the envelope of the acoustic waveform reflecting the temporal pattern of syllable repetitions during an oral DDK task (i.e., repetitions of /tɑ/ at the maximum rate on 1 breath). Cycle-to-cycle temporal variability (cTV) of envelope fluctuations and syllable repetition rate (sylRate) were derived from the envelope and validated against 2 kinematic measures, which are tongue movement jitter (movJitter) and alternating tongue movement rate (AMR) during the DDK task, in 16 individuals with bulbar ALS and 18 healthy controls. After the validation, cTV, sylRate, movJitter, and AMR, along with an established clinical speech measure, that is, speaking rate (SR), were compared in their ability to (a) differentiate individuals with ALS from healthy controls and (b) detect early-stage bulbar declines in ALS. Results cTV and sylRate were significantly correlated with movJitter and AMR, respectively, across individuals with ALS and healthy controls, confirming the validity of the acoustic DDK analysis in extracting the temporal DDK pattern. Among all the acoustic and kinematic DDK measures, cTV showed the highest diagnostic accuracy (i.e., 0.87) with 80% sensitivity and 94% specificity in differentiating individuals with ALS from healthy controls, which outperformed the SR measure. Moreover, cTV showed a large increase during the early disease stage, which preceded the decline of SR. Conclusions This study provided preliminary validation of a novel automated acoustic DDK analysis in extracting a useful measure, namely, cTV, for early detection of bulbar ALS. This analysis overcame a major barrier in the existing acoustic DDK analysis, which is continuous voicing between syllables that interferes with syllable structures. This approach has potential clinical applications as a novel bulbar assessment.

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Heart Rate Variability, Emotions, and Music

Journal of Psychophysiology ◽

10.1027/0269-8803/a000021 ◽

2010 ◽

Vol 24 (2) ◽

pp. 112-119 ◽

Cited By ~ 9

Author(s):

F. Riganello ◽

A. Candelieri ◽

M. Quintieri ◽

G. Dolce

Keyword(s):

Data Mining ◽

Heart Rate ◽

Heart Rate Variability ◽

Vegetative State ◽

Low Frequency ◽

Emotional Reactions ◽

Heart Beat ◽

Healthy Controls ◽

Frequency Spectra ◽

Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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