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Background and Objective: Melanoma is a complex malignancy where the interplay between immune cells, cytokines, and the tumor microenvironment (TME) significantly influences disease progression and patient outcomes. This review explores the involvement of the interleukin‐2 (IL‐2) cytokine family in both the development and therapeutic approaches for melanoma. Methods: A narrative literature review was conducted, synthesizing findings from studies on immune cell behavior, cytokine functions, and their implications in melanoma and other cancers. This narrative review emphasizes the roles of immune cells and cytokines in both promoting and inhibiting tumor growth. Results: Neutrophils, influenced by tumor‐derived cytokines, can adopt phenotypes that either inhibit or promote tumor growth. B cells in the TME often correlate with better survival, although their regulatory forms can suppress immune responses. Tissue‐resident memory T cells (TRM cells) are crucial for antitumor immunity, particularly in response to immune checkpoint inhibitors (ICIs). Dendritic cells (DCs) are vital for antigen presentation, yet their function can be compromised in melanoma. Macrophages frequently support tumor growth through immunosuppressive actions. The IL‐2 cytokine family, including IL‐2, IL‐4, IL‐7, IL‐9, IL‐15, and IL‐21, plays diverse roles in immune regulation. These cytokines are involved in T‐cell proliferation, B‐cell differentiation, and modulation of other immune responses, influencing both tumor progression and the effectiveness of immunotherapies. Conclusions: Immune cells and cytokines are pivotal in the pathogenesis, progression, and immunotherapy of melanoma. Understanding their complex roles offers insights into potential therapeutic strategies, highlighting the importance of targeted immunotherapies in treating melanoma and possibly other cancers. Additional studies are required to clarify the precise mechanisms and interactions occurring within the TME to enhance treatment strategies.

There has been a notable rise in cases of Candida Endocarditis (CE). Even with surgical procedures and antifungal treatments, the worldwide impact of Candida on health, including morbidity and mortality, has escalated. This narrative review was carried out through the PubMed and Scopus databases, where the search terms “Candida” and “Endocarditis” were used. The search strategy included meta-analyses, randomized controlled trials, clinical trials, observational studies, reviews, and case reports. The search was restricted to articles written in the English language from 2010 to Dec 30, 2022. Moreover, duplicate articles and non-available full-text articles were excluded. The extracted data of the search results were retrieved in this study. A background involving central venous catheters (CVC), congenital heart conditions and persistent debilitating illnesses heightens the chances of infection. Early initiation of antifungal treatment is crucial when considering Candida species and associated risk factors. The majority of research has concentrated on adult populations, leaving a gap in studies concerning pediatric patients. Presents manuscript review pediatric CE, including recent advances in management.

We conducted a cross-sectional study to (I) determine the relative frequency of antifungal-resistant Aspergillus clinical isolates, (II) address changes in susceptibility to available antifungals in patients infected with Aspergillus spp. with COVID-19, and (III) determine mutations in the CYP51A and CYP51B genes of Aspergillus spp. Isolated from the clinical specimens. A total of 30 fungal species were enrolled in the study. The antifungal activities of itraconazole and voriconazole were assessed using azole-containing agar media in Petri dishes. After identifying resistance in the isolates, the CYP51A and CYP51B gene regions were sequenced using the designed primers, and mutations were identified. To amplify CYP51A and CYP51B, primers with the specified sequences were used. Genomic DNA from 22 azole-resistant Aspergillus isolates was amplified using the CYP51-A and CYP51-B gene primers. 12/22 (54.54%) azole-resistant A. flavus isolates with the Tandem Repeat (TR34)/L98H (leucine-to-histidine substitution) mutation, MICs above the CLSI Epidemiological Cutoff Value. One carried the F46Y /TR34. 5/22 azole non-WT A. fumigatus isolates, CYP51-A analysis revealed that M220I, S297T/ TR34/L98H mutations, 4 A.orezea isolates had C498T/TR34 at a CYP51-B gene. Antifungal susceptibility testing should be performed when possible, and efficient systems must be implemented to monitor the evolution of newly introduced azole-resistant Aspergillus spp. In addition, these data are useful for clinicians to understand the incidence of azole resistance, enabling optimal management of affected patients and helping choose the right solution for infection management.

Background Diaper dermatitis, also recognized as diaper rash, is one of the most frequent skin conditions in neonates. Materials and Methods A total of 100 babies participated in the study. Eligibility included neonates aged 5–28 days and full‐time diaper wearers. Participants were categorized into two groups: those who received systemic antibiotics for at least 1 week and those who did not, in order to assess the impact of antibiotic use on diaper rash. The antifungal susceptibility was determined based on the reference method M60 CLSI. Results Among 100 specimens, 50 cases suffered from Candida infection. The Candida albicans (34, 68%) was reported as the most frequent species, followed by C. kefyer (10, 20%), C. tropicalis (4, 8%), and C. glabrata (2; 4%). Nystatin, posaconazole, voriconazole, amphotericin B, ketoconazole, and clotrimazole showed high activity against all species (Minimum Inhibitory Concentration ≤ 0.125 µg/mL). The resistance frequency of C. albicans to itraconazole and fluconazole was 65.5% and 12.7%, respectively (minimum inhibitory concentration ≥ 16 and minimum inhibitory concentration ≥ 64, respectively). The allele with the K143R and Y132F replacements displayed the strongest characterized combination effect, with 14‐fold and 18‐fold increased itraconazole and fluconazole MICs, respectively. Conclusion The selection of itraconazole and fluconazole‐resistant isolates of candida among pediatric population may be a concern because C. albicans can be involved in invasive infections. The treatment of recurrent invasive candidiasis, needing repeated course of fluconazole or itraconazole, could be a risk factor for selecting resistant isolates. In addition, as the liposomal amphotericin B is no more commercialized in our country, a higher drug selection pressure for azoles may be expected in the future. Summary Present data showed that mutations in ERG11 are predominant among azole‐resistant clinical isolates and that most mutations lead to considerable changes in fluconazole and itraconazole susceptibilities.

The present systematic review was conducted to investigate the knowledge of health care workers (HCWs) regarding first aid in burns. A comprehensive, systematic search was performed in different international electronic databases, such as Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex, and Scientific Information Database using keywords extracted from Medical Subject Headings such as ‘Knowledge’, ‘First aid’, ‘Health personnel’ and ‘Burns’ from the earliest to 1 February 2023. The appraisal tool for cross‐sectional studies (AXIS tool) evaluates the quality of the included studies. A total of 3213 HCWs participated in seven cross‐sectional studies. Of the HCWs, 44.50% were physicians. The studies included in this systematic review were conducted in Saudi Arabia, Australia, Turkey, the UK, Ukraine, and Vietnam. The knowledge rate of HCWs related to first aid for burns was 64.78 out of 100, which indicates their relatively desirable knowledge. The factors of first aid training experience, age, and experienced burn traumas had a significant positive effect on the knowledge of HCWs related to first aid for burns. Also, factors such as gender, nationality, marital status, and job position had a significant relationship with the knowledge of HCWs about first aid for burns. Therefore, it is suggested that health care managers and policymakers implement training programs and practical workshops related to first aid, especially first aid for burns.

Candida parapsilosis was introduced as the second most responsible for nail involvement. The colonization of biotic and abiotic surfaces by Candida spp. can result in the formation of biofilms, which possess a high level of resistance to typical antifungal agents. Since Candida spp. can produce biofilm mass on the surface of the nails, dermatologists should consider appropriate antifungals to eliminate both the planktonic and biofilm cells. The aim of this research was to determine the antifungal efficacy of itraconazole against C. parapsilosis sensu lato biofilm formations, in addition to its static effects. Ten C. parapsilosis sensu lato isolates were enrolled in this study. The use of itraconazole results in the accumulation of reactive oxygen species (ROS) during treatment. In order to verify the correlation between ROS and itraconazole-induced cell death, the viability of cells was analyzed by administering the ROS scavenger Ascorbic acid. The apoptotic features of itraconazole were analyzed using the Annexin V-FITC method. Based on current data, it was found that the generation of intracellular stresses by itraconazole is not observed in cells upon ROS inhibition, emphasizing the importance of intracellular ROS in the apoptotic mechanism of itraconazole. Targeting the oxidative defense system is a powerful point to use ROS-inducing antifungals as a superior choice for more effective therapies in case of recalcitrant onychomycosis. Graphical Abstract

Children's burns are a major public health concern due to their long‐term physical, psychological, and social impacts, as well as their high financial burden. This study aimed to evaluate the effectiveness of a smartphone‐based educational program on outcomes of children with severe burns. This study was designed as a double‐blinded, randomized controlled trial (RCT) to test the effectiveness of a developed mobile application. A total of 93 participants were included in the final analysis. The participants were randomly assigned to either the intervention or control groups. Participants in both groups received usual self‐care training at discharge, but those in the intervention group used an Android‐based application for 2 months. The primary goal of the burn application was scar recovery, and the secondary goals were to increase child caregivers' satisfaction rate and decrease unplanned hospital readmissions. Data collection was conducted using valid and reliable questionnaires. Data were analysed using SPSS software. The study showed that the mobile application significantly affected the frequency of patient visits to the burn clinic and the satisfaction of caregivers of children with burns with the treatment process (p‐value <0.05). Also, there was a significant relationship between the duration of application use and wound healing status ((p‐value <0.001). These findings suggest that smartphone‐based educational programs can be valuable for optimizing care for children with severe burns. Further research is warranted to explore the long‐term impact of this intervention and its potential application in different healthcare settings.

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life and expenditures. Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in nursing practice and is increasingly used for diagnosis, complications, prognosis, and recurrence prediction. This study aims to investigate hospital‐acquired PI (HAPI) risk predictions in ICU based on a ML algorithm by R programming language analysis. The former evidence was gathered through PRISMA guidelines. The logical analysis was applied via an R programming language. ML algorithms based on usage rate included logistic regression (LR), Random Forest (RF), Distributed tree (DT), Artificial neural networks (ANN), SVM (Support Vector Machine), Batch normalisation (BN), GB (Gradient Boosting), expectation–maximisation (EM), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost). Six cases were related to risk predictions of HAPI in the ICU based on an ML algorithm from seven obtained studies, and one study was associated with the Detection of PI risk. Also, the most estimated risksSerum Albumin, Lack of Activity, mechanical ventilation (MV), partial pressure of oxygen (PaO2), Surgery, Cardiovascular adequacy, ICU stay, Vasopressor, Consciousness, Skin integrity, Recovery Unit, insulin and oral antidiabetic (INS&OAD), Complete blood count (CBC), acute physiology and chronic health evaluation (APACHE) II score, Spontaneous bacterial peritonitis (SBP), Steroid, Demineralized Bone Matrix (DBM), Braden score, Faecal incontinence, Serum Creatinine (SCr) and age. In sum, HAPI prediction and PI risk detection are two significant areas for using ML in PI analysis. Also, the current data showed that the ML algorithm, including LR and RF, could be regarded as the practical platform for developing AI tools for diagnosing, prognosis, and treating PI in hospital units, especially ICU.

The present systematic review was conducted to investigate the knowledge of health care workers (HCWs) regarding first aid in burns. A comprehensive, systematic search was performed in different international electronic databases, such as Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex, and Scientific Information Database using keywords extracted from Medical Subject Headings such as ‘Knowledge’, ‘First aid’, ‘Health personnel’ and ‘Burns’ from the earliest to 1 February 2023. The appraisal tool for cross‐sectional studies (AXIS tool) evaluates the quality of the included studies. A total of 3213 HCWs participated in seven cross‐sectional studies. Of the HCWs, 44.50% were physicians. The studies included in this systematic review were conducted in Saudi Arabia, Australia, Turkey, the UK, Ukraine, and Vietnam. The knowledge rate of HCWs related to first aid for burns was 64.78 out of 100, which indicates their relatively desirable knowledge. The factors of first aid training experience, age, and experienced burn traumas had a significant positive effect on the knowledge of HCWs related to first aid for burns. Also, factors such as gender, nationality, marital status, and job position had a significant relationship with the knowledge of HCWs about first aid for burns. Therefore, it is suggested that health care managers and policymakers implement training programs and practical workshops related to first aid, especially first aid for burns.

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life and expenditures. Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in nursing practice and is increasingly used for diagnosis, complications, prognosis, and recurrence prediction. This study aims to investigate hospital‐acquired PI (HAPI) risk predictions in ICU based on a ML algorithm by R programming language analysis. The former evidence was gathered through PRISMA guidelines. The logical analysis was applied via an R programming language. ML algorithms based on usage rate included logistic regression (LR), Random Forest (RF), Distributed tree (DT), Artificial neural networks (ANN), SVM (Support Vector Machine), Batch normalisation (BN), GB (Gradient Boosting), expectation–maximisation (EM), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost). Six cases were related to risk predictions of HAPI in the ICU based on an ML algorithm from seven obtained studies, and one study was associated with the Detection of PI risk. Also, the most estimated risksSerum Albumin, Lack of Activity, mechanical ventilation (MV), partial pressure of oxygen (PaO2), Surgery, Cardiovascular adequacy, ICU stay, Vasopressor, Consciousness, Skin integrity, Recovery Unit, insulin and oral antidiabetic (INS&OAD), Complete blood count (CBC), acute physiology and chronic health evaluation (APACHE) II score, Spontaneous bacterial peritonitis (SBP), Steroid, Demineralized Bone Matrix (DBM), Braden score, Faecal incontinence, Serum Creatinine (SCr) and age. In sum, HAPI prediction and PI risk detection are two significant areas for using ML in PI analysis. Also, the current data showed that the ML algorithm, including LR and RF, could be regarded as the practical platform for developing AI tools for diagnosing, prognosis, and treating PI in hospital units, especially ICU.