Leishmaniasis is a neglected and old emerging/reemerging disease that has extremely increased and expanded in the different geographical areas. Cutaneous leishmaniasis (CL) is a common global public health concern in the tropics and subtropics reported from the Eastern Mediterranean Region, Africa, Latin America, and the Indian subcontinent. The presence of numerous epidemiological and clinical characteristics of the disease present a challenge in managing and controlling it. Despite wonderful efforts to control the disease in endemic areas, it appears that the burden of CL is still high. There is no comprehensive survey considering the interactive role of patients and medical services in the international CL control system. In the present study, the effective and mutual responsibility of the patients and the healthcare management in controlling the CL are reviewed, described, and discussed. Some patient-related factors that have a remarkable impact on the proper treatment and control strategies are low-socioeconomic condition, lack of sufficient knowledge about the disease, absence of personal protection, disregarding adherence to treatment, culture and incorrect beliefs about disease and therapy, depression, and lack of appropriate support from the family. On the other hand, some healthcare system-related factors that have an important effect on the suitable therapy and management of the disease are the economic burden of healthcare and drug preparation, unsuitable follow-up assessments, health education, early detection, and the right treatment, handling of unresponsive cases, active case detection, and monitoring/evaluation. Improving the socioeconomic conditions and living standards supports longstanding elimination approaches, and facilitates the wide-ranging control of the disease. Trained health staff and experienced clinicians should strengthen the building capacity for appropriate control programs throughout the healthcare system. These measures need sustained encouragement and appropriate multifunctional activities through all government segments including policymakers, the health system, clinical physicians, researchers, and also the private sector. In a suitable strategy, it is essential to understand precisely all the aspects of control strategies to respond correctly to the requests. Nevertheless, due to the complexity of the causative agent, major challenges/gaps remain, and vigorous conservative control plans should be continued until novel tools become available.

Background and Objectives: It is well known that Staphylococcus aureus biofilm plays an important role in adenoiditis and biofilm resistance frequently results in failure of therapy. The goal of this study was to evaluate the biofilm production of S. aureus isolates obtained from adenoid specimens and assess the relationship between biofilm formation ability and ica operon genes. Materials and Methods: A total of 112 adenoid samples were obtained from patients under 15 years old with adenoid hypertrophy. All S. aureus isolates were initially identified by standard microbiological tests and amplification of nuc by polymerase chain reaction (PCR) technique. Biofilm formation of S. aureus isolates was evaluated and icaADBC genes were detected by PCR technique. Results: There were 46 isolates (41%) identified as S. aureus. The ability to produce biofilm was detected among total S. aureus isolates. Molecular study of ica operon revealed that 2 (6.3%) and 19 (59.4%) isolates carried icaA and icaD, respec- tively. The prevalence of icaA + icaD was seen among 11 (34.4%) S. aureus isolates, while icaC and icaB were not detected. Conclusion: Our findings indicated that icaABCD operon are associated with biofilm formation in S. aureus isolates, how- ever the absence of these genes may not necessarily exclude this property.

Leishmaniasis is an important neglected disease among infectious diseases, which is highly affected by diverse adverse conditions. Due to the intricate nature of Leishmania , the impact of the disease remains significant. In this review, we aim to assess the role of these factors that influence disease trends and introduce preventive and control strategies, highlighting their importance in public health issues. Numerous influencing factors, such as trade and travel, civil unrest, migration, low socioeconomic status, peri‐urban settlements, ecological changes, climate variations, and many other confounding factors, play significant roles in the transmission and distribution of leishmaniasis. On the other hand, inadequate infrastructure and disruptions in the health system services are closely linked with the incidence of leishmaniasis in vulnerable populations. These circumstances contribute to the alteration of vector and reservoir compositions, land degradation, agricultural setbacks, water scarcity, and livestock depletion, resulting in increased infectious and noninfectious disease conditions. In conclusion, significant anthropic and natural environmental changes have the potential to trigger leishmaniasis outbreaks in established endemic areas and lead to the emergence/reemergence of new foci in previously unaffected regions. Consequently, enhancing public health awareness, particularly in high‐risk regions, along with implementing active and passive surveillance, ensuring early diagnosis, and providing timely and effective treatment for patients, are vital measures for controlling the disease.

Cutaneous leishmaniasis (CL) remains a significant global public health disease, with the critical distinction and exact detection between responsive and unresponsive cases dictating treatment strategies and patient outcomes. However, image‐based methods for differentiating these groups are unexplored. This study addresses this gap by developing a deep learning (DL) model utilizing transfer learning to automatically identify responses in CL lesions. A dataset of 102 lesion images (51 per class; equally distributed across train, test, and validation sets) is employed. The DenseNet161, VGG16, and ResNet18 networks, pretrained on a massive image dataset, are fine‐tuned for our specific task. The models achieved an accuracy of 76.47%, 73.53%, and 55.88% on the test data, respectively, with a sensitivity of 80%, 75%, and 100% and specificity of 73.68%, 72.22%, and 53.12%, individually. Transfer learning successfully addressed the limited sample size challenge, demonstrating the models’ potential for real‐world application. This work underscores the significance of automated response detection in CL, paving the way for treatment and improved patient outcomes. While acknowledging limitations like the sample size, the need for collaborative efforts is emphasized to expand datasets and further refine the model. This approach stands as a beacon of hope in the contest against CL, illuminating the path toward a future where data‐driven diagnostics guide effective treatment and alleviate the suffering of countless patients. Moreover, the study could be a turning point in eliminating this important global public health and widespread disease.

In semi-arid and arid regions, mulching with various materials is one of the highly significant ways to keep soil surface coverage. This approach helps efficiently reduce drought stress and soil erosion, thus preserving soil composition and ecosystem. The research aimed to pinpoint the physicochemical alterations and fungal diversity brought on by food waste mulch (FWM) in the desert soil. An experimental field assessment was conducted from early April (spring) to late August (summer) 2021 in the soil of the Jupar desert, the main watershed of the Central Plateau, southeastern Iran. The mulch was made from a combination of clay (70%), food waste (15%), and water and sprayed in 3 plots on the Jupar desert soil surface as a case group. Moreover, 3 plots of the Jupar desert soil and clay were selected as a non-mulch-controlled surface (control groups). The physicochemical changes were studied in all groups including FWM, desert soil, and clay. Besides, the samples were cultured and checked daily to determine the growth of fungal colonies. All fungal isolates were characterized to the species level by phenotypical and molecular methods. Sequence analysis of the ITS1, 5.8S, and ITS2 regions was done. The statistical findings displayed that the physical and chemical characteristics of FWM (case group) were significantly different compared to clay and soil samples (control groups) (P<0.05). Phenotypic and genotypic analysis of the fungal consortium showed that the most frequent filamentous and yeast fungi belonged to the Alternaria and Naganishia genera, respectively. Identified fungi are classified as growth-inducing and anti-pest fungi. This study showed that adding FWM of organic matter can cause partial variety in soil fungal diversity and stabilize the desert soil due to enriching the organic matter in eroding soils.