Skin Illnesses Research Articles

Guided Analysis of Selected Ethnobotanical Acanthaceous Plants for Anti-Inflammatory Properties

Acanthaceous plants have emerged as important therapeutic plants on a global scale, producing biologically active chemical compounds with larvicidal, antimicrobial, and cytotoxic properties. In traditional Thai medicine, the crude extracts of these plants, including Clinacanthus nutans, Justicia gendarussa, and Rhinacanthus nasutus, have been used to detoxify bug bites and some skin illnesses caused by fungus and viruses. This study argued for investigating acanthaceous plant extracts for alternate advantages such as anti-inflammation. The presence of anti-inflammatory components in extracts was examined using HPLC in order to evaluate their potential. Lupeol, a prospective anti-inflammatory triterpene found in medicinal plants, was employed as a chemical marker. The anti-inflammatory activities of extracts containing the active chemical were studied utilizing protein denaturation and inhibition of nitric oxide production in RAW 264.7 cells stimulated with LPS. Also, the extract of combined active plants was assessed. Lupeol was detected in the tested extracts in quantities ranging from 0.25 to 1.22% w/w. It was found in the highest concentration in the extract of Clinacanthus nutans and in the lowest concentration in the extract of Justicia gendarussa. All extracts of plants containing the active ingredient exhibited anti-inflammatory effects. Their IC50 values ranged between 0.87 and 29.28 mg/mL. The extract made from a combination of plants that contained lupeol demonstrated the most potent anti-inflammatory effect, with a 0.6-fold difference when compared to diclofenac. This research implied that investigating acanthaceous plant extracts containing this active agent might be more beneficial in the design of herbal recipes with anti-inflammatory characteristics.

Formulation Development, Optimization by Box–Behnken Design, and In Vitro and Ex Vivo Characterization of Hexatriacontane-Loaded Transethosomal Gel for Antimicrobial Treatment for Skin Infections

There are many different infections and factors that can lead to skin illnesses, but bacteria and fungi are the most frequent. The goal of this study was to develop a hexatriacontane-loaded transethosome (HTC-TES) for treating skin conditions caused by microbes. The HTC-TES was developed utilizing the rotary evaporator technique, and Box-Behnken design (BBD) was utilized to improve it. The responses chosen were particle size (nm) (Y1), polydispersity index (PDI) (Y2), and entrapment efficiency (Y3), while the independent variables chosen were lipoid (mg) (A), ethanol (%) (B), and sodium cholate (mg) (C). The optimized TES formulation with code F1, which contains lipoid (mg) (A) 90, ethanol (%) (B) 25, and sodium cholate (mg) (C) 10, was chosen. Furthermore, the generated HTC-TES was used for research on confocal laser scanning microscopy (CLSM), dermatokinetics, and in vitro HTC release. The results of the study reveal that the ideal formulation of the HTC-loaded TES had the following characteristics: 183.9 nm, 0.262 mV, -26.61 mV, and 87.79% particle size, PDI, and entrapment efficiency, respectively. An in vitro study on HTC release found that the rates of HTC release for HTC-TES and conventional HTC suspension were 74.67 ± 0.22 and 38.75 ± 0.23, respectively. The release of hexatriacontane from TES fit the Higuchi model the best, and the Korsmeyer-Peppas model indicates the release of HTC followed a non-Fickian diffusion. By having a higher negative value for cohesiveness, the produced gel formulation demonstrated its stiffness, whereas good spreadability indicated better gel application to the surface. In a dermatokinetics study, it was discovered that TES gel considerably increased HTC transport in the epidermal layers (p < 0.05) when compared to HTC conventional formulation gel (HTC-CFG). The CLSM of rat skin treated with the rhodamine B-loaded TES formulation demonstrated a deeper penetration of 30.0 µm in comparison to the hydroalcoholic rhodamine B solution (0.15 µm). The HTC-loaded transethosome was determined to be an effective inhibitor of pathogenic bacterial growth (S. aureus and E. coli) at a concentration of 10 mg/mL. It was discovered that both pathogenic strains were susceptible to free HTC. According to the findings, HTC-TES gel can be employed to enhance therapeutic outcomes through antimicrobial activity.

Preclinical study models of psoriasis: State-of-the-art techniques for testing pharmaceutical products in animal and nonanimal models.

Local and systemic treatments exist for psoriasis, but none can do more than control its symptoms because of its numerous unknown mechanisms. The lack of validated testing models or a defined psoriatic phenotypic profile hinders antipsoriatic drug development. Despite their intricacy, immune-mediated diseases have no improved and precise treatment. The treatment actions may now be predicted for psoriasis and other chronic hyperproliferative skin illnesses using animal models. Their findings confirmed that a psoriasis animal model could mimic a few disease conditions. However, their ethical approval concerns and inability to resemble human psoriasis rightly offer to look for more alternatives. Hence, in this article, we have reported various cutting-edge techniques for the preclinical testing of pharmaceutical products for the treatment of psoriasis.

Pharmacognostic, Phytochemical and Pharmacological Review of Ficus religiosa

Ficus Religiosa is a perennial evergreen tree. It is belonging to moraceae own circle of relatives and In India its commonly referred to as Peepal tree, Bodhi tree. The tree is local of India. Peepal tree incorporates many main bioactive components which own diverse pharmacological interest and additionally beneficial with inside the remedy of diverse illnesses and problems consists of Diabetes, ulcer, cancer, epilepsy, pores and skin illnesses, flu and additionally own many medicinal interest together with anti-inflammatory interest, analgesic interest, anti-acetyl cholinesterase interest, anti-helminthic interest and wound recovery interest and additionally famous a few different interest together with antibacterial, anti-fungal etc. All components of tree (leaves, bark, fruit, root and flower) are beneficial for the preparation of many ayurvedic components and beneficial for making natural treatments etc. that is beneficial for deal with and cure diverse illnesses. The tree product now no longer reasons any main or intense aspect effect. The foremost intention of this review/take a look at turned into to find out or sell the information approximately this multipurpose medicinal valued tree.

Probiotics: A Review on Microbiome That Helps for Better Health – A Dermatologist’s Perspective

Commensal microorganisms heavily influence human health and disease pathogenesis, and the impact of the skin microbiome on numerous skin illnesses has recently piqued researchers’ interest, in addition to the gut microbiome. Probiotics are live microbial organisms that are good for the host’s health when given in sufficient proportions. The concept of probiotics has sparked much curiosity and scientific investigation since its inception. Probiotics alter the intestinal microbiota and are employed as a treatment technique for a variety of diseases. Despite several studies, the significance of probiotics in dermatological illnesses such as acne, vaginal infections, and atopic dermatitis has yet to be demonstrated. Evidence pointing to the “gut-skin axis” link has increased, and intestinal microbiota regulation may play a role in dermatological diseases. There is, however, no consensus on the species or the dosage to be utilized for such therapies. This article makes an effort to review recent evidence from the literature.

Synergistic Antimicrobial Activity of Ceftriaxone and Polyalthia longifolia Methanol (MEPL) Leaf Extract against Methicillin-Resistant Staphylococcus aureus and Modulation of mecA Gene Presence.

Medicinal plants are an essential source of traditional curatives for numerous skin diseases. Polyalthia longifolia (Sonn.) Thwaites (Annonaceae family) is a medicinal plant used to cure skin illnesses. P. longifolia is usually applied in folkloric therapeutical systems to treat skin diseases. The methicillin-resistant Staphylococcus aureus (MRSA) bacteria is among the essential bacteria contributing to skin diseases. Hence, to verify the traditional medicinal claim of P. longifolia usage in skin disease treatment, the current research was performed to study the synergistic antibacterial activity of standardized Polyalthia longifolia methanol leaf extract (MEPL) against MRSA bacteria. The synergistic antimicrobial activity result of ceftriaxone, when mixed with MEPL, against MRSA was investigated by the disc diffusion method, broth microdilution method, checkerboard dilution test, and modulation of mecA gene expression by multiplex polymerase chain reaction (multiplex PCR). The MEPL extract exhibited good synergistic antimicrobial activity against MRSA. Using the checkerboard method, we confirmed the synergistic effect of MEPL from P. longifolia and ceftriaxone (2:1) for MRSA with a marked reduction of the MIC value of the ceftriaxone from 8000 µg/mL to 1000 µg/mL. Moreover, the combination of MEPL with ceftriaxone significantly (p < 0.05) inhibited the presence of the resistant mecA gene in the tested strain. The LC-ESI-MS/MS analysis identified compounds that were reported to exhibit antimicrobial activity. Conclusively, the MEPL extract, an important etiological agent for skin diseases, showed worthy synergistic antimicrobial action against MRSA bacteria, thus supporting the traditional use of P. longifolia.

KNOWLEDGE ATTITUDE AND PRACTICE ABOUT SUN-PROTECTION AND SUNSCREEN USAGE AMONG NURSING STUDENTS

Background: Photoprotection refers to safeguarding against UV rays as well as secondary variables like oxidative stress with the use of antioxidants, etc. Additionally, the harm done by UV radiations is one of the factors contributing to the public's rising rate of skin illnesses. Sunscreens are employed as photoprotective measures to guard against these dangerous UV rays. The effectiveness of it is signicantly inuenced by the sun protection factor. It is crucial that individuals are aware of the importance of wearing sunscreen, and numerous research have been done to examine this issue. To assess knowledge, attitude and practice towards sun protection and Objectives: sunscreen usage among nursing students. A cross-sectional, descriptive study using a specially designed Materials and Methods: questionnaire was conducted among nursing students in a tertiary care center. The questionnaire was completed and r Results: eturned by 200 females in the age range of 15-25 years. Only 88 out of 200 females were using sunscreens. Majority of the patients, 136(68%) belonged to rural background. Assessment of the sun exposure revealed that 130(65%)respondents reported daily sun exposure whereas 70 (35%) had occasional sun exposure. Assessment of the knowledge revealed that all of them 200 (100%) are aware of the adverse effects of excessive sun exposure but only 56(28%) were aware of the carcinogenic effect of sunlight.62 (31%) respondents reported that they use sunscreen on a daily basis.53 (26.5%) patient mentioned sunscreens are expensive and is the reason for not using them. Media was the most common source of information. 26 (13%) of them think sunscreens are harmful to the skin. 64 (32%) of them agree that wearing sunscreen can cause vitamin D deciency. Conclusion: This study shows that proper method of use of sunscreens is low among young females and suggests need of proper training about sunscreen and their usage and also need for general public health education program.

TRANSFER LEARNING MODELS COMPARISON FOR DETECTING AND DIAGNOSING SKIN CANCER

Skin cancer is a severe problem that is frequently disregarded. In circumstances of manual examination by a clinician, the human eye is occasionally unable to detect disorders precisely from imaging data. Deep learning techniques are increasingly being used nowadays to solve various problems in our daily lives. Therefore, deep neural network techniques are used to create an automated and computerized mechanism for detecting skin illnesses. To identify and diagnose skin illnesses over a range of criteria several neural network algorithms are evaluated and tested in the suggested model to see how well they perform. The networks are constructed to provide better outcomes using the CNN (Convolution neural network) and the Keras Sequential API architectures. The paper also compares the outcomes of the models using several metrics, such as accuracy, precision, f1 score, and recall. The transfer learning model involves seven models like DenseNet201, InseptionResnetV2, MobileNetV2, InceptionV3, ResNet50, DenseNet169, and VGG16. Among the employed models, the DenseNet169 model achieved the highest score of 87.58% in terms of accuracy; also, in terms of sensitivity and F1 score, DenseNet201 achieved the highest scores of 95.28% and 89.09%, respectively. On the other hand, VGG16 gained a score of 89.67% in terms of specificity, and DenseNet169 achieved the highest score of 90.64% in terms of precision.

Brewing epidemic of communicable diseases after massive flooding in Pakistan.

Brewing epidemic of communicable diseases after massive flooding in Pakistan.

Feasible Skin Lesion Detection using CNN and RNN

A prevalent form of cancer that affects millions of individuals globally is skin cancer. The visual examination of skin lesions, however, is a challenging and time-consuming procedure that calls for the knowledge of dermatologists. The proposed effort intends to create an accurate, feasible and effective system for detecting skin lesions that can help dermatologists identify and treat a variety of skin conditions. To extract features from skin lesion photos, the method uses a pre-trained Convolutional Neural Network (CNN). These characteristics are then fed into a Recurrent Neural Network (RNN) for temporal modelling. The early diagnosis of numerous skin illnesses depends greatly on the detection of skin lesions. Deep learning models, particularly CNNs, have demonstrated impressive performance in the computer-aided diagnosis of skin lesions in recent years. This work uses the HAM 10000 dataset to suggest a hybrid CNN and RNN model for skin lesion detection.

Deep Learning and MachineLearning to Diagnose Melanoma

The most dangerous disorders include melanoma. Yet, a precise diagnosis of skin cancer is difficult. Recent research has shown that a variety of activities can be performed better using deep learning and machine learning techniques. For skin conditions, these algorithms are highly useful. In this article, we examine various deep learning and machine learning techniques and how they could be applied to the detection of melanoma. This paper provides a number of publicly downloadable datasets, information on common melanoma, instructions for getting dermatology pictures, and more. Once machine learning and deep learning concepts have been introduced, our attention shifts to analysing common machine learning and deep learning architectures as well as popular frameworks for putting machine and deep learning algorithms into practice. Metrics for performance evaluation are then offered. In this section, we will cover the research on machine learning and deep learning and how they can be applied to the detection of melanoma skin illnesses. We also go over potential research avenues and the difficulties in the field. The main objective of this work is to discuss modern machine learning and deep learning techniques for melanoma diagnosis.

PREVALENCE OF SKIN PROBLEMS IN PAEDIATRIC GROUP BELOW THAN 12 YEARS OLD

Background:Childrens skin illnesses are a significant cause of morbidity and may be impacted by regional, racial, social, cultural, and economic variables. Despite their global prevalence, skin disorders have not played a significant role in the development of public health initiatives. Methods: The current study aimed to determine the prevalence of dermatological disorders among pediatric population at a single point of measurement as reported by parents. The most suitable design is cross-sectional study. It was descriptive and correlational study. This enables the researcher to measure the effect and the outcome at a single point of time. This study design gives reliable results with short time and less effort. The study was conducted at (place). The participants were selected during the period during October 2022. This study included children aged less than 12 years old via non-probability convenient sampling technique at a confidence level of 95% using Epi Info software equation. Results: The study included 1106 parents reporting dermatological disorders among their children. The most frequent dermatological disorders among children as reported by parents were cuts, scratches and grazes (n= 127, 11.5%). Cuts, scratches and grazes and insects bite was the most frequent combination of dermatological disorders among children (n= 108, 9.8%). There were 7% of children suffered from eczema (n= 77). Other dermatological disorders that children included in the current study suffered from are: Boils (n= 30, 2.7%), Cellulitis (= 24, 2.2%), Fifth disease (n= 12, 1.1%), Impetigo (n= 13, 1.2%), Herpes zoster (n= 12, 1.1%), Ring worm (n= 24, 2.2%), Warts (n= 10, 0.9%). The most frequent age group among children was 3-6 years (n= 357, 32.3%). Male to female ratio among children was very close and almost 1:1. There were 575 males (52%) and 531 females (48%). Conclusion:The group studied had a high frequency of skin irritation, infection, and insect bite reactions. Dermatological diseases are readily recognized, treated, and prevented. Many of the examined children had not sought medical help for the identified pathology, which may indicate a lack of access to health care. The studys strengths include its large sample size and age-focused epidemiology. Due to its methodology, this study, like many prevalence studies, cannot show causal relationships.This study reveals that its necessary to give fast access to health care services, enhance cleanliness in homes and public areas, and adopt preventive measures including complete vaccination and targeted fumigation.

Comparison of Phenolic Contents and Antioxidant Activities for Black and White Desert Truffles Spread in Syria

Desert truffle is considered as a type of Syrian wild fungi that spreads heavily, and it occupies important rank in folk medicine, where its aqueous extract is used for the treatment of some eye and skin illnesses, and people prefer the use of black truffle. This work interested in studying of the most available species; Terfezia claveryi (black) and Tirmania pinoyi (white). The extracts of the two species of truffle were prepared by maceration with water, methanol, and ethanol 70%. Their total phenolic contents (TPC) and total flavonoid contents (TFC) were analyzed using Folin-ciocalteu and Aluminum chloride methods respectively, and their antioxidant activities was tested using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Ferric Reducing Antioxidant Power (FRAP) methods, after microscopic examination and detection of phytochemical components. Then, phenolic profile of ethanolic 70% extract of black truffle T.claveryi was studied by using LC-MS/MS. The values of TPC were between 25.3-43.6 mg GAE/g dry extract and TFC were between 2.5-6.8 mg QE/g dry extract. The values of DPPH (IC50) and FRAP were between 5.6-9.0 mg/ml and 90.1-153.4 µmol AAE/g dry extract respectively. There is a great similarity in content and activity of two species, also the aqueous extract is similar to other extracts in content and activity, and this means that the method of extract preparation in traditional medicine is reliable. It has been predicted about 14 phenolic compounds in the extract; as p-Hydroxy benzoic acid, Syringic acid and trans-Cinnamic acid. As a result, both truffle species are a new rich resource of antioxidant compounds which are usable in nutritional, cosmetic, and therapeutic applications.

Nails Deformation Sensing For Disease Detection Using Fusion Method For Texture Analysis

Medical image processing is essential for identifying conditions like skin cancer, brain tumors, breast cancer, and illnesses of the heart and lungs. To detect disorders, the human nail serves as a window into the body. Various methods are available in the healthcare industry for early disease diagnosis. One method for diagnosing diseases in their early stages is nail image analysis. It is possible to forecast some general and dermatological disorders using human nails. The naked human eye cannot detect numerous variations in nail color or texture. In this research, models for illness prediction using nail pictures are constructed. In this work, the fusion of statistical and structural texture featuresis employed to forecast diseases. Merging structural and statistical features allows for the analysis of the correctness of many models and the selection of the most relevant one. Numerous methods, particularly GLCM, LBP, and Gabor filter, were used to combine statistical and structural features

Methodologies of Autologous Skin Cell Spray Graft.

Healthcare workers continue to struggle with skin wound management. Despite the fact that there have been many methods created throughout the decades for skin regeneration, contemporary developments in regenerative medicine provide highly reliable methods for creating synthetic skin replacements, such as electrospinning, 3D bioprinting, or spraying, among all others. Specifically, skin sprays have been a cutting-edge method that is currently undergoing clinical testing and has lots of promise for providing cells and hydrogels to cure both acute and chronic wounds. Deposition of cells and scaffolding materials in successive layers over the burnt regions characterises 3D bioprinting for burn injury repair. Depending on the desired outcome, bioprinting of skin may be performed in vivo or in vitro. However, the location of the printing and the time required for the tissue to mature separates these two methods. Bioprinted skin for use in burn repair faces technical and regulatory hurdles before it may be used in clinical settings. Skin sprays provide various benefits to traditional wound care methods, inclusive of ease of administration, the ability to treat broad wound regions, and a consistent dispersion of the sprayed substance. The most recent developments in this technology are reviewed in this article, along with a thorough explanation of investigational and presently marketed acellular and cellular skin spray solutions that are utilized to treat a range of illnesses and administer various experimental materials. Additionally, we describe regulatory processes for their capitalization and cover key clinical studies for various skin illnesses and associated treatment circumstances because skin spray products are susceptible to several classifications. Finally, we provide an argument and offer potential future developments in the biotechnology of skin sprays for improved clinical dermatological applications.

Human Skin Infection A Review Study

All across the world, skin diseases are rather frequent. The likelihood of pediculosis capitis (0.2-35 percent, 6.9-35 percent in Sub-Saharan Africa in addition to other parts of South Africa. ), pyoderma (prevalence range 0.2-35 percent, 6.9–35% in Sub-Saharan Africa and other parts of South Africa, tinea capitis (1–19.7%), scabies (0.2–24%, 1.3–17% in Sub-Saharan Africa), and viral skin illnesses (0.4–9%, mainly molluscum contagiosum,0-57 percent). A bacterial skin infection is the most frequent kind of skin infection. Numerous bacterial skin infections have been linked to necrotizing fasciitis, scarlet fever, erysipelas, erythrasma, abscesses, folliculitis, furunculosis, and impetigo. Additionally, ecthyma, furunculosis, and mycobacterium skin disorders are covered in this review. Recent studies have revealed modifications in the causes and remedies of bacterial skin infections. In the United States, the prevalence of MRSA (methicillin-resistant Staphylococcus aureus) is rising.

Homoeopathic management of non-communicable chronic skin conditions: A clinical study on the effectiveness of homoeopathic medicines for exacerbations of psoriasis

Non-communicable chronic skin illnesses like psoriasis, vitiligo, and lichen planus have an increasing worldwide burden and are challenging to treat therapeutically. Despite the fact that there are many treatment options available under conventional therapies, these approaches cannot be taken into consideration in the long run due to their unfavourable side effects and excessive financial implications. These diseases exhibit remissions and exacerbations throughout their chronic course, which are frequently discouraging for both patients and doctors. Therefore, the major goal was to determine the effectiveness of homoeopathic medications in treating acute psoriasis exacerbations, and the secondary goal was to identify the primary triggering events producing these exacerbations. Here, based on conventional homoeopathic principles, we provide a prospective clinical investigation on the efficiency of homoeopathic medications in treating psoriasis flare-ups. Homoeopathic management provided good symptomatic relief in patients suffering from exacerbations of psoriasis.

33388 A case of eruptive trichofolliculomas

A 61-year-old female presented several months after an abrupt onset of multiple pruritic, hyperpigmented papules that began on the temporal region and progressed to involve the entire face and neck. She denied using new products on her skin or recent illnesses. Physical exam revealed multiple hyperpigmented lichenified papules involving the face, neck, and chest. Punch biopsies from the face and neck revealed unusual multifocal pseudoepitheliomatous hyperplasia radiating down from a distorted hyperplastic follicle.

ResNet based Deep Learning model for Skin Diseases Classification

Skin disease are commonest than other diseases. It might be caused by bacteria, parasites and viruses etc. The Advanced medical technology has made it possible to identify the skin disease faster and accurate. However, the cost of such skin diseases remains limited and expensive. So image processing techniques aid in the development of an automated screening system for dermatology at an early stage. The features extraction plays vital role in the classification of skin diseases. Computer vision has a function in the detection of pores and skin illnesses in variety of strategies. This research aims to detect three common diseases such as acne, hyper pigmentation and psoriasis. We proposed an image processing techniques that accepts the digital image of disease, then image analysis to identify the type of disease. The proposed method is very simple, fast and does not need any additional equipment. It accepts input of color image and it resizes the image to extract features using CNN. Then multi class features are classified using first order feature extraction method. Lastly, the type of disease, spread and severity are shown to the user. The system identifies three different types of disease accurately.

Framework to detect skin disease using deep learning techniques

Dermatological issues are one of the most unpreventable disorders on earth. In any case, being typical, its investigation is exceedingly problematic due to its intricacies of coloring, concealing, and handiness of hair. Recognizing skin sicknesses at the beginning phase plays a significant part in therapy. The steps which are used to dig down the problem statement and find out the solution for skin injury are finalized with the domain knowledge of the giant in that field. The analytic interaction should be exact and ideal. Because of the innovative improvements both in medication and data advancements, the achievement rates of both clinical diagnosing and clinical treatment frameworks are expanding step by step. A human-developed domain that works based on logic is utilized in the field of finding out skin illnesses with the help of AI calculations and the abuse of the immense measure of information accessible in wellbeing places and medical clinics, gathering past examinations for the specialists’ classifications is common practice in numerous works. A few frameworks have been effective in characterizing skin sicknesses and accomplishing fluctuating indicative precision. Different frameworks have depended on techniques for picture handling and component extraction that help foresee and recognize sickness types.