The Effect of Botulinum Toxin Type A on Expression Profiling of Long Noncoding RNAs in Human Dermal Fibroblasts

Clinically Actionable Topical Strategies for Addressing the Hallmarks of Skin Aging: A Primer for Aesthetic Medicine Practitioners

In this narrative review, we sought to provide a comprehensive overview of the mechanisms underlying cutaneous senescence, framed by the twelve traditional hallmarks of aging. These include genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, impaired macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, and dysbiosis. We also examined how topical interventions targeting these hallmarks can be integrated with conventional aesthetic medicine techniques to enhance skin rejuvenation. The potential of combining targeted topical therapies against the aging hallmarks with minimally invasive procedures represents a significant advancement in aesthetic medicine, offering personalized and effective strategies to combat skin aging. The reviewed evidence paves the way for future advancements and underscores the transformative potential of integrating scientifically validated interventions targeted against aging hallmarks into traditional aesthetic practices.

Multifaced roles of PLAC8 in cancer

The role of PLAC8 in tumorigenesis has been gradually elucidated with the development of research. Although there are common molecular mechanisms that enforce cell growth, the impact of PLAC8 is varied and can, in some instances, have opposite effects on tumorigenesis. To systematically understand the role of PLAC8 in tumors, the molecular functions of PLAC8 in cancer will be discussed by focusing on how PLAC8 impacts tumorigenesis when it arises within tumor cells and how these roles can change in different stages of cancer progression with the ultimate goal of suppressing PLAC8-relevant cancer behavior and related pathologies. In addition, we highlight the diversity of PLAC8 in different tumors and its functional output beyond cancer cell growth. The comprehension of PLAC8's molecular function might provide new target and lead to the development of novel anticancer therapies.

Aberrantly expressed lncRNAs and mRNAs after botulinum toxin type A inhibiting salivary secretion

OBJECTIVE

In this study, we sought to determine the expression profiles of long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) and construct functional networks to analyze their potential roles following botulinum toxin type A (BTXA)-mediated inhibition of salivary secretion.

METHODS

The submandibular gland of rats in the BTXA and control groups was injected with BTXA and saline, respectively. Microarray analysis was used to identify the differentially expressed lncRNAs and mRNAs. Gene ontology and pathway analysis were performed to examine the biological functions. Functional networks, including lncRNA-mRNA co-expression and competing endogenous RNA (ceRNA) networks, were constructed to reveal the interaction between the coding and non-coding genes.

RESULTS

Microarray analysis revealed that 254 lncRNAs and 631 mRNAs were differentially expressed between the BTXA and control groups. Bioinformatic analysis revealed that most of the mRNAs were closely related to transmembrane transporter activity. lncRNA-mRNA co-expression and ceRNA networks were constructed, and several critical mRNA-lncRNA axes and key microRNAs related to salivary secretion were identified.

CONCLUSIONS

Our study identified differentially expressed lncRNAs and mRNAs through microarray analysis and explored the interactions between the coding and non-coding genes through bioinformatic analysis. These findings provide new insights into the mechanism of BTXA-mediated inhibition of salivary secretion.

The effect of botulinum toxin type A in different dilution on the contraction of fibroblast-In vitro study

BACKGROUND

Botulinum toxin type A (BoNT-A) may directly remodel dermal tissues or induce a loss of normal morphology and cytoplasmic retraction and spread. Intradermal injection was claimed to produce a dermo-lifting effect, including midface lifting by using low concentration with variable dilution.

OBJECTIVE

To understand how intradermal BoNT-A achieves tissue lifting, we examined different type of BoNT-A and their effects on dermal fibroblast contraction.

METHODS

Normal human dermal fibroblasts were treated with onabotulinumtoxin (ONA), abobotulinumtoxin (ABO), prabotulinumtoxinA (PRABO), incobotulinumtoxinA (INCO), and letibotulinumtoxin A (LETI) in dilutions used in real-world practice. Fifty fibroblasts per dilution were photographed and measured the length to demonstrate their contraction every 2 hours from baseline (0 hours) to 12 hours post-treatment.

RESULTS

ONA did not significantly decrease fibroblast lengths, at any timepoint or dilution. At 1:7 dilution ratios, ABO decreased fibroblast lengths after 2 hours and significantly after 10-12 hours. At 1:7, 1:8, 1:9, and 1:10 dilution, PRABO decreased length, and most rapidly at 1:7 and 1:8. At 1:6, 1:8, 1:9, and 1:10 dilution, INCO decreased lengths almost immediately. At 1:6 dilution, INCO decreased lengths almost immediately. At 1:7 dilution, INCO decreased lengths after 2-4 hours, while at 1:8, 1:9, and 1:10 dilution, INCO decreased lenghts nearly imediately. LETI decreased lengths at all dilutions except 1:9, with near-immediate effects at 1:6, 1:7, 1:8, and 1:10. At 1:4 dilution, LETI decreased lengths from 1 hour.

CONCLUSIONS

Different commercial preparations of BoNT-A toxins cause different fibroblast contractions in vitro. Product selection and dilution used may affect the clinical outcome of intradermal injection of BoNT-A for face lifting.

Tissue Expression Difference between mRNAs and lncRNAs

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) are two main subgroups of RNAs participating in transcription regulation. With the development of next generation sequencing, increasing lncRNAs are identified. Many hidden functions of lncRNAs are also revealed. However, the differences in lncRNAs and mRNAs are still unclear. For example, we need to determine whether lncRNAs have stronger tissue specificity than mRNAs and which tissues have more lncRNAs expressed. To investigate such tissue expression difference between mRNAs and lncRNAs, we encoded 9339 lncRNAs and 14,294 mRNAs with 71 expression features, including 69 maximum expression features for 69 types of cells, one feature for the maximum expression in all cells, and one expression specificity feature that was measured as Chao-Shen-corrected Shannon's entropy. With advanced feature selection methods, such as maximum relevance minimum redundancy, incremental feature selection methods, and random forest algorithm, 13 features presented the dissimilarity of lncRNAs and mRNAs. The 11 cell subtype features indicated which cell types of the lncRNAs and mRNAs had the largest expression difference. Such cell subtypes may be the potential cell models for lncRNA identification and function investigation. The expression specificity feature suggested that the cell types to express mRNAs and lncRNAs were different. The maximum expression feature suggested that the maximum expression levels of mRNAs and lncRNAs were different. In addition, the rule learning algorithm, repeated incremental pruning to produce error reduction algorithm, was also employed to produce effective classification rules for classifying lncRNAs and mRNAs, which gave competitive results compared with random forest and could give a clearer picture of different expression patterns between lncRNAs and mRNAs. Results not only revealed the heterogeneous expression pattern of lncRNA and mRNA, but also gave rise to the development of a new tool to identify the potential biological functions of such RNA subgroups.