Candida albicans (C. albicans), a conditional pathogenic fungus, is widespread in nature and can live in symbiosis with organisms in small quantities. When the normal microflora is imbalanced, the epithelial barrier is disrupted or the immune system becomes dysfunctional, C. albicans can change from commensal to pathogenic pathogen, causing both superficial and life-threatening systemic infections with no effective treatment. The morbidity and mortality of invasive Candida infections in perioperative patients are high due to underlying chronic diseases, immune deficiencies, and pathophysiological disorders. C-type lectin receptors (CLRs) are the main pattern-recognition receptors for fungal activation of innate immunity and host defense. Upon binding to ligands, CLRs induce multiple signal transduction cascades followed by activation of nuclear factor kappa B through spleen tyrosine kinase - and caspase recruitment domain containing protein 9-dependent pathways. Analyzing the effects of regulatory CLR-induced signaling cascades on host immune cells is critical for understanding the molecular mechanism in regulating antifungal immunity. As one of the core factors in host innate immune regulation, protein post-translational modifications regulate the strength of immune effects by modulating protein conformation, stability, affinity, subcellular localization, etc. This makes the post-translational modification sites promising as potential targets for modulating antifungal immunity. This review primarily described the study progress of post-translational modifications in controlling CLR-induced signaling cascades throughout the process of innate immunity against C. albicans. We aim to provide better understanding of these mechanisms and aid in the identification and development of biomarkers and drug targets for invasive candidiasis.

Ethical approval is the first essential step for medical master's students to officially initiate research. This article discusses the ethical issues encountered in various types of research projects conducted by professional master's students, the preparation of ethical application materials, conflicts between the timing of ethical applications and the clinical training rotation schedules, and the continuity of ethical applications among students within the same cohort and across different cohorts.

Objective: Skin is a complex tissue whose health is modulated by multiple factors. Exposure to the environment causes damage to skin cells and skin tissue. Identification of factors that can improve skin cell function potentially can prevent or reverse skin aging. Fibroblast growth factors (FGFs) induce growth of skin cells and regulate multiple genes important for skin function. However, FGFs cannot penetrate skin and thus cannot be used as therapeutic factors. Methods: Here we tested three proline-containing tripeptides for their ability to induce skin cell growth, change gene expression within these cells, and protect cells from harmful agents. We also tested the ability of one peptide to penetrate skin, a prerequisite to influence skin cells in vivo. Results: We identified three short proline-containing tripeptides that increase both fibroblast and keratinocyte cell growth, increase the abundance of COL1A1 (collagen type 1) and AQP3 (aquaporin 3) mRNA transcripts and decrease IL6 (interleukin-6) transcripts, all features of improved skin health. These tripeptides, when used as a pretreatment, prevent an increase in the abundance of MMP1 (matrix metalloprotease 1), a biomarker of skin damage when these cells are treated with an aging compound. Finally, we show that one of these tripeptides can penetrate skin. Conclusions: Proline-containing tripeptides have properties that indicate they can be used to reduce or reverse skin damage.

Employment is the cornerstone of people's livelihood and a vital component of talent cultivation in higher educa-tion institutions. In the pursuit of the "Healthy China 2030" initiative, medical colleges and universities are com-mitted to ensuring high-quality and comprehensive employment for their students by strengthening Party-building efforts. This approach aims to enhance students' employability, secure favorable employment rates, and align their career development with societal needs. This article explores the significance of Party-building in guiding college students towards proactive employment. It provides a comprehensive analysis of the current employment landscape in medical colleges and universities, identifying key challenges and opportunities. In response to these challenges, the article offers targeted recommendations on how Party-building initiatives within these institutions can foster high-quality and full employment for medical students. By integrating ideological guidance, skill en-hancement, and strategic training reforms, the proposed measures aim to support medical graduates in making informed career choices and securing suitable employment, thereby contributing to the advancement of health-care and societal well-being.

Cardiovascular diseases are still the primary threats to people's health around the world. Automatic heart sound classification technology, as a fast and efficient means for diagnosis and treatment, is of great clinical significance. With the rapid development of artificial intelligence technology, deep learning algorithms are widely used in automatic heart sound classification. This paper reviewed the key technologies related to the automatic classification of heart sounds in recent years, including heart sound denoising, segmentation, feature extraction, and classification recognition. The classification and recognition technologies related to deep learning are presented in detail, with a focus on the application and development of convolutional neural network and recurrent neural network, as well as various combination models for heart sound classification in the past five years.

This paper presents a gait prediction method for lower limb exoskeleton robots using a real-time adaptive Kalman filtering algorithm. The exoskeleton robot targets two user groups: individuals with impaired lower limb motor function requiring rehabilitation training, where the device aids in muscle exercise during walking to facilitate recovery, and healthy individuals using it as a wearable assistive device. To enhance movement intention prediction and improve human-machine coordination, this study focuses on the gait prediction algorithm for walking assistance in healthy users and proposes a gait prediction control strategy based on normal gait orientation. The control system utilizes a microcontroller and Raspberry Pi as its core, enabling functional mode selection through multi-sensor data fusion and effective control of the robot via Bluetooth communication. By comparing the original model algorithm with the proposed real-time updating Kalman filter algorithm, the latter demonstrates feasibility, achieving a prediction error within 1°. This validates the model’s effectiveness in real-time gait prediction.

Obstetric and perinatal anesthesia, while crucial for maternal and neonatal health, carries inherent risks that necessitate careful management and resource optimization to ensure patient safety. Improvements in anesthesia methods, ultrasound-assisted blocks, multimodal analgesia and accelerated rehabilitation protocols have enabled individualized and precise control of postoperative pain to be achieved more readily. Risk analysis, dynamic observation, and personalized intervention can all significantly lower the rates of hypotension, nausea and vomiting, and nerve injury. International practice variations highlight how resource availability—including staffing levels and expertise—and adherence to clinical guidelines profoundly impact maternal and neonatal outcomes, underscoring that scientific resource optimization is essential for ensuring safety and enhancing efficiency. This perspective discusses the current trends in perinatal anesthesia, focusing on risk minimization and resource utilization. By synthesizing recent advancements and practice variations, we aim to offer a conceptual framework and valuable insights for clinicians making management decisions.