Validity and Reliability of the Persian Version of Positive Body Image Among Adolescents Scale.

Background and Purpose: This study evaluated the validity and reliability of the Persian version of Positive Body Image among Adolescents Scale (PBIAS-P) in Tehran, Iran, in order to better understand adolescents' positive perceptions of their physical selves and the accompanying thoughts and emotions. Methods: This cross-sectional study was carried out involving adolescents from Tehran Province, Iran, in 2022. Both exploratory factor analysis and confirmatory factor analysis were performed in order to evaluate the construct validity of the PBIAS-P. Cronbach's alpha, McDonald's omega, and intraclass correlation coefficients were also used to confirm the internal consistency of the scale. Results: The findings indicate that three factors extracted from the PBIAS-P account for 50.1% of the total variance. The model fit is considered good based on cut points for various fit indices. All factors had values of Cronbach's alpha, McDonald's omega, and average interitem correlation above .73, .74 and .4, respectively. Also, test-retest reliability for three factors was acceptable. Conclusions: The PBIAS-P has acceptable validity and reliability in Iranian adolescents, making it useful for researchers, psychologists, and health care professionals.

In vitro digestion and colonic fermentation of phenolic compounds and their antioxidant potential in Australian beach-cast seaweeds.

Beach-cast seaweed has recently garnered attention for its nutrient-rich composition, including proteins, carbohydrates, vitamins, minerals, and phytochemicals. This study focuses on the phenolic content and antioxidant potential of five Australian beach-cast seaweed species during in vitro digestion and colonic fermentation. The bioaccessibility of the selected phenolic compounds was estimated and short chain fatty acids (SCFAs) production was determined. Cystophora sp., showed a notable increase in phenolic content (23.1 mg GAE/g) and antioxidant capacity (0.42 mg CE/g) during the intestinal and gastric phases of in vitro digestion. Durvillaea sp. demonstrated a significant release of flavonoids (0.35 mg QE/g), while Phyllosphora comosa released high levels of tannins (0.72 mg CE/g) during the intestinal phase. During colonic fermentation, P. comosa released the highest levels of phenolic compounds (4.3 mg GAE/g) after 2 h, followed by an increase in flavonoids (0.15 mg QE/g), tannins (0.07 mg CE/g), and antioxidant activity (DPPH: 0.12 mg CE/g; FRAP: 0.61 mg CE/g) after 4 h. Moreover, P. comosa released a considerable amount of phenolic compounds during both in vitro digestion and colonic fermentation. All species consistently released phenolic compounds throughout the study. Phloroglucinol, gallic acid, and protocatechuic acid were identified as the most bioaccessible phenolic compounds in all five Australian beach-cast seaweeds in the in vitro digestion. Nevertheless, compound levels declined during the colonic fermentation phase due to decomposition and fermentation by gut microbiota. With regard to SCFAs, P. comosa displayed elevated levels of acetic (0.51 mmol/L) and propionic acid (0.36 mmol/L) at 2 h, while Durvillaea sp. showed increased butyric (0.42 mmol/L) and valeric (0.26 mmol/L) production acid after 8 h. These findings suggest that seaweed such as Cystophora sp., Durvillaea sp., and P. comosa are promising candidates for food fortification or nutraceutical applications, given their rich phenolic content and antioxidant properties that potentially offer gut health benefits.

Fat transplant: Amazing growth and regeneration of cells and rebirth with the miracle of fat cells.

BACKGROUNDS AND OBJECTIVE: During fat transplantation, adipose tissue is removed from the body and injected into different areas under the skin. The goal of this review article is to look into the efficacy and applicability of fat transplantation in regenerative medicine and rejuvenation, including Nanofat, Microfat, and Millifat. METHODS: As a search strategy and study selection, we searched the PubMed and Medline databases until 2023 using related keywords (e.g., Nanofat, Microfat and Millifat, Regenerative Medicine, and Rejuvenation). RESULTS: Autologous fat transplantation has no risk of an allergic reaction or rejection of the transplant by the individual. Autologous adipose tissue is considered an ideal filler for facial rejuvenation and is suggested as the most biocompatible and non-immunogenic skin filler. Adipose tissue transplant may have semi-permanent to permanent effects. According to recent reports, adipose tissues possess a high percentage of mature stem cells. The effect of regenerating adipose tissue and its intrinsic cells can be described as an obvious process. Variations in the sizes of adipose tissues can result in different results depending on the surgical site. Based on topographic assessment, graft fats are assigned depending on the anatomical locations and the size such as Millifat (2-2.5 mm), Microfat (1 mm), and Nanofat (500 µm or less). CONCLUSION: Some characteristics of fat tissue increase its effectiveness, such as increasing stem cells, growth factors, cytokines, and compounds effective in repair, regeneration, and rejuvenation.

Treatment with Exosomes Derived from Mesenchymal Stem Cells: A New Window of Healing Science in Regenerative Medicine.

Many studies have been conducted on the potential applications of mesenchymal stem cells (MSCs) over recent years due to their growing importance in reconstructive medicine. Exosomes are considered cargos capable of transporting proteins, peptides, lipids, mRNAs, and growth factors. MSCs-derived exosomes are also involved in the prevention or treatment of a variety of diseases, including cardiovascular diseases, neurological diseases, skin disorders, lung diseases, osteoarthritis, damaged tissue repair, and other diseases. This review attempted to summarize the importance of employing MSCs in reconstructive medicine by gathering and evaluating information from current literature. The role of MSCs and the potential applications of MSCs-derived exosomes have also been discussed.

Application of mesenchymal stem cells in regenerative medicine: A new approach in modern medical science.

Mesenchymal Stem Cells (MSCs) are non-hematopoietic and multipotent stem cells, which have been considered in regenerative medicine. These cells are easily separated from different sources, such as bone marrow (BM), umbilical cord (UC), adipose tissue (AT), and etc. MSCs have the differentiation capability into chondrocytes, osteocytes, and adipocytes; This differentiation potential along with the paracrine properties have made them a key choice for tissue repair. MSCs also have various advantages over other stem cells, which is why they have been extensively studied in recent years. The effectiveness of MSCs-based therapies depend on several factors, including differentiation status at the time of use, concentration per injection, delivery method, the used vehicle, and the nature and extent of the damage. Although, MSCs have emerged promising sources for regenerative medicine, there are potential risks regarding their safety in their clinical use, including tumorigenesis, lack of availability, aging, and sensitivity to toxic environments. In this study, we aimed to discuss how MSCs may be useful in treating defects and diseases. To this aim, we will review recent advances of MSCs action mechanisms in regenerative medicine, as well as the most recent clinical trials. We will also have a brief overview of MSCs resources, differences between their sources, culture conditions, extraction methods, and clinical application of MSCs in various fields of regenerative medicine.

Comparative Study on the Effect of Phenolics and Their Antioxidant Potential of Freeze-Dried Australian Beach-Cast Seaweed Species upon Different Extraction Methodologies.

Brown seaweed is rich in phenolic compounds and has established health benefits. However, the phenolics present in Australian beach-cast seaweed are still unclear. This study investigated the effect of ultrasonication and conventional methodologies using four different solvents on free and bound phenolics of freeze-dried brown seaweed species obtained from the southeast Australian shoreline. The phenolic content and their antioxidant potential were determined using in vitro assays followed by identification and characterization by LC-ESI-QTOF-MS/MS and quantified by HPLC-PDA. The Cystophora sp. displayed high total phenolic content (TPC) and phlorotannin content (FDA) when extracted using 70% ethanol (ultrasonication method). Cystophora sp., also exhibited strong antioxidant potential in various assays, such as DPPH, ABTS, and FRAP in 70% acetone through ultrasonication. TAC is highly correlated to FRAP, ABTS, and RPA (p < 0.05) in both extraction methodologies. LC-ESI-QTOF-MS/MS analysis identified 94 and 104 compounds in ultrasound and conventional methodologies, respectively. HPLC-PDA quantification showed phenolic acids to be higher for samples extracted using the ultrasonication methodology. Our findings could facilitate the development of nutraceuticals, pharmaceuticals, and functional foods from beach-cast seaweed.

Cross-Cultural Evaluation of the Psychometric Properties of the Spiritual Well-Being Scale: A Systematic Review.

Since spiritual well-being has a significant role in individual and social health, using a valid scale to identify these properties is essential. Comparing factor structure and differences in the number of dimensions and items of subscales could be an indicator of differences in individuals' attitudes toward spirituality among diverse cultures. The present review was performed for psychometric evaluation of the spiritual well-being measures. A systematic review of international databases and Iranian databases was conducted to evaluate studies published between January 1, 1970, and October 1, 2022. QUADAS-2, STARD, and COSMIN scales were used for risk of bias assessment. Following two rounds of screening, 14 articles entered quality assessment. According to the results, studies examining the factor structure of the spiritual well-being scale (SWBS) instrument have been conducted for the years 1998 to 2022. The mean age of the participants in these studies ranged from 20.8 to 79.08 years. During the process of exploratory factor analysis, the researchers reported the presence of two to five latent factors, and the range of explained variance was between 35.6 and 71.4%. However, most of the reports indicated the existence of two or three latent factors. The findings of the present study provide an image of the psychometric status of the SWBS for researchers and clinicians in this field and can help them make optimum decisions in selecting a scale or conducting additional psychometric studies or adopting this scale for studies in new populations.

COMPARATIVE EFFICACY OF 1% CURCUMIN NANOMICELLE GEL AND 2% CURCUMIN GEL FOR TREATMENT OF RECURRENT APHTHOUS STOMATITIS: A DOUBLE-BLIND RANDOMIZED CLINICAL TRIAL.

OBJECTIVE: Recurrent aphthous stomatitis (RAS) is a highly prevalent painful inflammatory condition. Curcumin is currently used as a medicinal herb with optimal anti-inflammatory properties for many inflammatory conditions. However, due to its low water solubility and consequently low bioavailability, its nanoparticulate formulation has been considered for use. This study aimed to compare the efficacy of topical application of 1% curcumin nanomicelle gel and 2% curcumin gel for treatment of RAS. METHODS: This double-blind randomized clinical trial evaluated 48 RAS patients. The patients randomly received 1% curcumin nanomicelle gel or 2% curcumin gel, and were asked to apply it 3 times/day for 1 week. The severity of pain was measured using a visual analog scale (VAS), and the size of lesions (in millimeters) was measured by a periodontal probe before (baseline), and at 4, and 7 days after treatment. Data were analyzed by repeated measures ANOVA. RESULTS: No significant difference was noted in the pain score (P = .160) or size of lesions (P = .432) between the 2 groups at baseline. At 7 days, the pain score and size of lesions significantly decreased in both groups (P < .05). The reduction in pain score and lesion size was significantly greater in the curcumin nanomicelle gel group at both 4 and 7 days (P < .05). Also, the efficacy index (EI) was higher in curcumin nanomicelle gel group. CONCLUSIONS: The 1% curcumin nanomicelle gel can be effectively used to enhance the healing of RAS.

Advances in understanding the specificity function of transporters by machine learning.

Understanding the underlying molecular mechanism of transporter activity is one of the major discussions in structural biology. A transporter can exclusively transport one ion (specific transporter) or multiple ions (general transporter). This study compared categorical and numerical features of general and specific calcium transporters using machine learning and attribute weighting models. To this end, 444 protein features, such as the frequency of dipeptides, organism, and subcellular location, were extracted for general (n = 103) and specific calcium transporters (n = 238). Aliphatic index, subcellular location, organism, Ile-Leu frequency, Glycine frequency, hydrophobic frequency, and specific dipeptides such as Ile-Leu, Phe-Val, and Tyr-Gln were the key features in differentiating general from specific calcium transporters. Calcium transporters in the cell outer membranes were specific, while the inner ones were general; additionally, when the hydrophobic frequency or Aliphatic index is increased, the calcium transporter act as a general transporter. Random Forest with accuracy criterion showed the highest accuracy (88.88% ±5.75%) and high AUC (0.964 ± 0.020), based on 5-fold cross-validation. Decision Tree with accuracy criterion was able to predict the specificity of calcium transporter irrespective of the organism and subcellular location. This study demonstrates the precise classification of transporter function based on sequence-derived physicochemical features.

Image processing unravels the evolutionary pattern of SARS-CoV-2 against SARS and MERS through position-based pattern recognition.

SARS-COV-2, Severe Acute Respiratory Syndrome (SARS), and the Middle East respiratory syndrome-related coronavirus (MERS) viruses are from the coronaviridae family; the former became a global pandemic (with low mortality rate) while the latter were confined to a limited region (with high mortality rates). To investigate the possible structural differences at basic levels for the three viruses, genomic and proteomic sequences were downloaded and converted to polynomial datasets. Seven attribute weighting (feature selection) models were employed to find the key differences in their genome's nucleotide sequence. Most attribute weighting models selected the final nucleotide sequences (from 29,000th nucleotide positions to the end of the genome) as significantly different among the three virus classes. The genome and proteome sequences of this hot zone area (which corresponds to the 3'UTR region and encodes for nucleoprotein (N)) and Spike (S) protein sequences (as the most important viral protein) were converted into binary images and were analyzed by image processing techniques and Convolutional deep Neural Network (CNN). Although the predictive accuracy of CNN for Spike (S) proteins was low (0.48%), the machine-based learning algorithms were able to classify the three members of coronaviridae viruses with 100% accuracy based on 3'UTR region. For the first time ever, the relationship between the possible structural differences of coronaviruses at the sequential levels and their pathogenesis are being reported, which paves the road to deciphering the high pathogenicity of the SARS-COV-2 virus.

A large-scale study of indicators of sub-clinical mastitis in dairy cattle by attribute weighting analysis of milk composition features: highlighting the predictive power of lactose and electrical conductivity.

Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-scale mining of milk composition features by pattern recognition models can identify the best predictors of SCM within the milk composition features. To this end, using data mining algorithms, we conducted a large-scale and longitudinal study to evaluate the ability of various milk production parameters as indicators of SCM. SCM is the most prevalent disease of dairy cattle, causing substantial economic loss for the dairy industry. Developing new techniques to diagnose SCM in its early stages improves herd health and is of great importance. Test-day Somatic Cell Count (SCC) is the most common indicator of SCM and the primary mastitis surveillance approach worldwide. However, test-day SCC fluctuates widely between days, causing major concerns for its reliability. Consequently, there would be great benefit to identifying additional efficient indicators from large-scale and longitudinal studies. With this intent, data was collected at every milking (twice per day) for a period of 2 months from a single farm using in-line electronic equipment (346 248 records in total). The following data were analysed: milk volume, protein concentration, lactose concentration, electrical conductivity (EC), milking time and peak flow. Three SCC cut-offs were used to estimate the prevalence of SCM: Australian ≥ 250 000 cells/ml, European ≥200 000 cells/ml and New Zealand ≥ 150 000 cells/ml. At first, 10 different Attribute Weighting Algorithms (AWM) were applied to the data. In the absence of SCC, lactose concentration featured as the most important variable, followed by EC. For the first time, using attribute weighted modelling, we showed that the concentration of lactose in milk can be used as a strong indicator of SCM. The development of machine-learning expert systems using two or more milk variables (such as lactose concentration and EC) may produce a predictive pattern for early SCM detection.

SpliceDetector: a software for detection of alternative splicing events in human and model organisms directly from transcript IDs.

In eukaryotes, different combinations of exons lead to multiple transcripts with various functions in protein level, in a process called alternative splicing (AS). Unfolding the complexity of functional genomics through genome-wide profiling of AS and determining the altered ultimate products provide new insights for better understanding of many biological processes, disease progress as well as drug development programs to target harmful splicing variants. The current available tools of alternative splicing work with raw data and include heavy computation. In particular, there is a shortcoming in tools to discover AS events directly from transcripts. Here, we developed a Windows-based user-friendly tool for identifying AS events from transcripts without the need to any advanced computer skill or database download. Meanwhile, due to online working mode, our application employs the updated SpliceGraphs without the need to any resource updating. First, SpliceGraph forms based on the frequency of active splice sites in pre-mRNA. Then, the presented approach compares query transcript exons to SpliceGraph exons. The tool provides the possibility of statistical analysis of AS events as well as AS visualization compared to SpliceGraph. The developed application works for transcript sets in human and model organisms.