Abstract: Recurrent Vulvovaginal Candidiasis (RVVC) is increasing worldwide, with biofilm persistence and antifungal resistance limiting treatment options. The combined use of antifungal treatments with antibiofilm agents has become a promising strategy. This review explores advanced therapeutic approaches, their limitations, and prospects. Overgrowth of vaginal Candida inflames the mucosa, causing itching, dryness, and whitish discharge. Biofilm formation worsens the condition, contributing to treatment failure, resistance, and recurrence. Conventional antifungal modalities are often inadequate against these multidimensional biofilm assemblies. Combining natural and synthetic antifungal agents with antibiofilm adjuncts has shown improved outcomes by targeting Candida cells within biofilms. This review compiles studies on multicomponent approaches to managing vaginal Candida infections, focusing on pan-Candida species to clarify species-specific resistance and persistence. Host factors in non-virgin women, a highly affected population, are examined alongside regional data on recurrence and treatment failure. Together, these insights highlight the microbiology of Candida biofilms, host and regional influences, and the socio-economic burden of RVVC, while emphasising the translational importance of combination therapy and biotechnology-driven innovations such as molecular docking, nanocarriers, CRISPR-based gene modulation, and engineered probiotics.
Following publication of the article entitled “Artificial Intelligence in Cancer Diagnosis: A Game-changer in Healthcare” [1], certain phrases and expressions were identified that were unclear or inconsistent with established scientific terminology. To ensure the accuracy and clarity of the published record, these expressions have been corrected using appropriate terminology that more accurately conveys the intended scientific meaning. These corrections are limited to the wording and terminology of the affected passages and do not alter the data, results, scientific interpretations, or conclusions of the article. The specific corrections are provided below: 4.1. Key Concepts and Model Architectures Definition, Paragraph 1, Line 21 Original text: ….Table 1 gives a summary of common supervised learning approaches, covering older decision tree and deep learning (DL) algorithms as well as more recent choice tree and logistic regression (LR) statistical models. Corrected text: ....Table 1 gives a summary of common supervised learning approaches, covering older decision tree and deep learning (DL) algorithms as well as more recent decision tree and logistic regression (LR) statistical models. The original article has been updated accordingly. This corrigendum is published to maintain transparency and accuracy of the scholarly record. The corrected version of the article is available online at: https://www.eurekaselect.com/article/140874 The authors regret these errors and apologise for any inconvenience they may have caused.
In the article “The Gut Health Revolution: Herbs and Dietary Phytochemicals in Balancing Gut Microbiota for Optimal Human Health”, published in Current Pharmaceutical Biotechnology [1], Table 1 was published in an incomplete form. The table has now been corrected and completed. The original article can be found at: https://www.eurekaselect.com/article/143439
Introduction/Objective: Chronic pain and opioid-related harm intersect through overlapping biological, behavioral, and clinical pathways. This narrative review presents a framework linking dopamine homeostasis, opioid-risk reduction, and objective cognitive testing in precision pain and addiction medicine. Methods: Literature on chronic pain, opioid exposure, mesocorticolimbic dopamine signaling, reward-circuit vulnerability, pharmacogenomics, dopamine precursor and pro-dopaminergic adjuncts, and Continuous Visual Attention Test (CVAT) metrics was synthesized narratively; this is not a systematic review or clinical guideline. Results: Pain relief, reinforcement, withdrawal, mood, attention, and recovery motivation involve overlapping regulatory systems. Dopamine biology is relevant to these intersections but does not provide a single-cause explanation for pain or addiction. Genetic risk stratification and pharmacogenomic testing may enrich research models and selected counseling but require external validation, ancestry-aware calibration, and ethical safeguards. CVAT reaction time, variability, omissions, and commissions may complement pain and disability scales during treatment. Discussion: The framework distinguishes established opioid-sparing care from investigational dopamine precursor strategies and emphasizes repeated measurement of function, medication exposure, and cognition. Conclusion: Precision pain care should integrate biological risk, opioid stewardship, multimodal analgesia, dopamine-homeostasis hypotheses, and objective cognitive monitoring.
