ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective Patients with lung cancer often experience interrelated symptoms such as fatigue, pain, and sleep disturbances during chemotherapy, forming a core symptom cluster that significantly impacts daily functioning, treatment experience, and quality of life. Currently, evidence on non-pharmacological management of this core symptom cluster is scattered, and there is a lack of standardized, patient- and caregiver-friendly guidance tools that are easy to understand and implement. This patient guideline aims to provide decision support for self-management of the core symptom cluster in patients undergoing chemotherapy for lung cancer. Methods Guided by evidence-based methodology, qualitative interviews and on-site questionnaire surveys were conducted to identify the health-related needs of stakeholders. Domestic and international guideline websites, relevant professional association websites, and comprehensive databases were systematically searched according to the inclusion and exclusion criteria. The included literature was evaluated for quality, and recommendations were extracted, integrated, and graded to form a summary of the best evidence. Based on the identified health issues and evidence summary, preliminary recommendations for the patient guideline were developed. The recommendations were then revised through two rounds of Delphi expert consultation, and consensus was reached on the strength of recommendations, forming the final version of the patient guideline. Results The patient guideline covered four major sections: screening and assessment of core symptom clusters, daily management, intervention measures, and timing of referral. The core content included nine aspects: screening of core symptom clusters, assessment, lifestyle habits, dietary interventions, sleep environment, exercise interventions, psychological interventions, Traditional Chinese Medicine interventions, and referral indications. In total, the guidelines addressed 16 health issues and provided 25 recommendations. Conclusion The development process of this patient guideline is rigorous and fully considered the needs of patients. Expert review concludes that the recommendations are highly feasible and appropriate.

BackgroundMonitoring the blood concentrations of antipsychotic drugs and their metabolites can guide the adjustment of clinical treatment plans， improving therapeutic efficacy while reducing adverse effects. However， there is currently a lack of a method that can accurately and efficiently quantitatively detect multiple antipsychotic drugs and their metabolites. ObjectiveTo establish a ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method for the simultaneous identification and quantitation of 12 antipsychotic drugs and their main metabolites in human serum. MethodsUsing UPLC-MS/MS technology， protein precipitation method was employed for sample pretreatment. An Agela Technologies Durashell C₈ chromatographic column （50 mm×3.0 mm， 5 μm） was selected for chromatographic separation with gradient elution. The flow rate was 0.4 mL/min， and the total analysis time was 5 minutes. The column temperature was 40℃. The mass spectrometry detection was carried out in the multiple reaction monitoring （MRM） mode， and the isotope internal standard method was used for quantification. ResultsThe relative standard deviation （RSD） of the internal standard normalization matrix effect factor for 12 antipsychotic drugs and their main metabolites at low and high quality concentrations was all less than 15%. The extraction recovery rate was 85% to 115%. They showed good linear relationships within their respective standard curve ranges （r>0.995）. At low， medium， and high quality concentrations， the accuracy was 85.24% to 114.71%， and the RSD of intra-batch and inter-batch precision was all ≤14.15%， with good stability. ConclusionAll the analytical performance indicators of this method meet the verification requirements， providing an analytical means for the quantitative detection of antipsychotic drugs and their main metabolites in human serum. ［Funded by The Third Batch of Science and Technology Projects in Chaozhou City in 2023 （number， 202303GY02）］

OBJECTIVE To explore a synergistic medication strategy integrating stage-specific modifications of Bushen huoxue decoction with hormone replacement therapy （HRT） for premature ovarian insufficiency （POI）. METHODS The connotation of Academician Tong Xiaolin’s “state-target differentiation and treatment” theory and the disease stage characteristics of POI were summarized. The latent stage， subclinical stage， clinical stage and exhaustion stage of POI were classified into corresponding core pathogenesis “states” and key objective indicator “targets”. Taking Bushen huoxue decoction as the basic prescription， its staged modification scheme and its sequential combination with HRT were analyzed. RESULTS & CONCLUSIONS The four stages of POI correspond to four pathogenic states respectively： kidney yin deficiency， kidney deficiency and blood stasis， heart-kidney disharmony， and deficiency of both yin and yang. Follicle-stimulating hormone （FSH）， anti-Müllerian hormone （AMH）， antral follicle count （AFC） and Kupperman score were taken as the evaluation targets of staging. Combined with the “state-target” characteristics of each stage， a medication principle based on Bushen huoxue decoction with syndrome differentiation modification and stage-adjusted administration was established： traditional Chinese medicine dominates in the latent stage， a sequential collaborative regimen is adopted in the subclinical stage， HRT is dominant supplemented by traditional Chinese medicine in the clinical stage， and integrated traditional Chinese and Western medicine is applied to consolidate the root cause in the exhaustion stage.

Functional disorders of the Golgi apparatus are harmful to the health of organisms, leading to various diseases. Removing damaged Golgi apparatus is crucial for maintaining cellular homeostasis, therefore, autophagy of Golgi apparatus has gradually attracted attention. This article summarizes Golgi autophagy, briefly describes its structure and functions, Golgi autophagy receptors, and the role of Golgi autophagy in disease treatment. It also proposes the new concept of Golgimedicine, which looks forward to the role of Golgi in disease diagnosis, treatment, prognosis, genetic diseases, and rare diseases. This article aims to explore the scientific connotations of Golgi autophagy, Golgi structure and function from the perspective of Golgimedicine, providing theoretical references for drug target research, new drug development, and the healthy development of humanity.

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

The innate immune system detects cellular stressors and microbial infections, activating programmed cell death (PCD) pathways to eliminate intracellular pathogens and maintain homeostasis. Among these pathways, pyroptosis, apoptosis, and necroptosis represent the most characteristic forms of PCD. Although initially regarded as mechanistically distinct, emerging research has revealed significant crosstalk among their signaling cascades. Consequently, the concept of PANoptosis has been proposed—an inflammatory cell death pathway driven by caspases and receptor-interacting protein kinases (RIPKs), and regulated by the PANoptosome, which integrates key features of pyroptosis, apoptosis, and necroptosis. The core mechanism of PANoptosis involves the assembly and activation of the PANoptosome, a macromolecular complex composed of three structural components: sensor proteins, adaptor proteins, and effector proteins. Sensors detect upstream stimuli and transmit signals downstream, recruiting critical molecules via adaptors to form a molecular scaffold. This scaffold activates effectors, triggering intracellular signaling cascades that culminate in PANoptosis. The PANoptosome is regulated by upstream molecules such as interferon regulatory factor 1 (IRF1), transforming growth factor beta-activated kinase 1 (TAK1), and adenosine deaminase acting on RNA 1 (ADAR1), which function as molecular switches to control PANoptosis. Targeting these switches represents a promising therapeutic strategy. Furthermore, PANoptosis is influenced by organelle functions, including those of the mitochondria, endoplasmic reticulum, and lysosomes, highlighting organelle-targeted interventions as effective regulatory approaches. Cardiovascular diseases (CVDs), the leading global cause of morbidity and mortality, are profoundly impacted by PCD. Extensive crosstalk among multiple cell death pathways in CVDs suggests a complex regulatory network. As a novel cell death modality bridging pyroptosis, apoptosis, and necroptosis, PANoptosis offers fresh insights into the complexity of cell death and provides innovative strategies for CVD treatment. This review summarizes current evidence linking PANoptosis to various CVDs, including myocardial ischemia/reperfusion injury, myocardial infarction, heart failure, arrhythmogenic cardiomyopathy, sepsis-induced cardiomyopathy, cardiotoxic injury, atherosclerosis, abdominal aortic aneurysm, thoracic aortic aneurysm and dissection, and vascular toxic injury, thereby providing critical clinical insights into CVD pathophysiology. However, the current understanding of PANoptosis in CVDs remains incomplete. First, while PANoptosis in cardiomyocytes and vascular smooth muscle cells has been implicated in CVD pathogenesis, its role in other cell types—such as vascular endothelial cells and immune cells (e.g., macrophages)—warrants further investigation. Second, although pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are known to activate the PANoptosome in infectious diseases, the stimuli driving PANoptosis in CVDs remain poorly defined. Additionally, methodological challenges persist in identifying PANoptosome assembly in CVDs and in establishing reliable PANoptosis models. Beyond the diseases discussed, PANoptosis may also play a role in viral myocarditis and diabetic cardiomyopathy, necessitating further exploration. In conclusion, elucidating the role of PANoptosis in CVDs opens new avenues for drug development. Targeting this pathway could yield transformative therapies, addressing unmet clinical needs in cardiovascular medicine.