Objective: To investigate the distribution characteristics of ABO and Rh blood group antigen phenotypes among blood donors in the Yantai, Shandong. Methods: Blood samples from 310 180 voluntary blood donors in Yantai collected from January 2019 to December 2023 were tested for ABO and Rh blood group antigens using standard serological methods. RhD-negative samples were further typed for C, c, E, and e antigens. Population genetic analysis of blood groups was performed: allele frequencies were inferred from ABO phenotypes, and Rh allele/haplotype frequencies were estimated based on the proportion of RhD-negative donors and CcEe antigen typing, followed by Hardy-Weinberg equilibrium testing. Results: The phenotypic distribution frequency of ABO blood groups was B(32.72%)>O(28.93%)>A(27.65%)>AB(10.70%). The inferred allele frequencies were r(53.74%)>q(24.78%)>p(21.48%), consistent with Hardy-Weinberg equilibrium (P>0.05). A total of 1 872 Rh-negative donors (0.603%) were identified. The most common Rh phenotypes were ccdee (59.56%) and Ccdee (30.18%). The distribution of Rh antigen phenotypes deviated significantly from Hardy-Weinberg equilibrium (χ =37.15, P<0.001), with the cde haplotype showing the highest frequency. There was no statistically significant difference in ABO blood group distribution between RhD-positive and RhD-negative donors (P>0.05). Conclusion: The ABO blood group distribution among voluntary blood donors in Yantai is generally stable and consistent with population genetic equilibrium, whereas the Rh antigen phenotype distribution deviates from equilibrium, indicating potential underlying genetic structural differences.

Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language models (LLMs) technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. The paper systematically analyzes that the exceptional potential of LLMs in lung cancer auxiliary diagnosis, tumor feature extraction, automatic staging, progression/outcome analysis, treatment recommendations, medical documentation generation, and patient education. However, they face critical technical and ethical challenges including inconsistent performance in complex integrated decision-making (e.g., TNM staging, personalized treatment suggestions) and "black box" opacity issues, along with dilemmas such as training data biases, model hallucinations, data privacy concerns, and cross-lingual adaptation challenges ("data colonization"). Future directions should prioritize constructing high-quality multimodal corpora specific to lung cancer, developing interpretable and compliant specialized models, and achieving seamless integration with existing clinical workflows. Through dual drivers of technological innovation and ethical standardization, LLMs should be prudently advanced for holistic lung cancer management processes, ultimately promoting efficient, standardized, and personalized diagnosis and treatment practices.

ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point， this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding， 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups （10 mice per group）： The 12-month-old control group （12MCON）， the 15-month-old control group （15MCON）， and the 15-month-old group with a high-fat diet （15MHFD）. The 12MCON and 15MCON groups were continuously fed a standard diet， while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups （10 mice per group）： the 20-month-old control group （20MCON）， the model group， and the low-， medium-， and high-dose Liangyi Paste groups （2.91 ， 5.82 ， 11.64 g·kg^-1·d^-1， respectively）. The 20MCON group was continuously fed a standard diet， while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age， the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage， while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage （when the mice reached 20 months of age）， tissue samples were collected. Hepatic TG levels were measured using assay kits； liver histology and lipid deposition were observed via hematoxylin-eosin （HE） and oil red O staining； reactive oxygen species （ROS） were detected by enzyme-linked immunosorbent assay （ELISA）； Cu²⁺， superoxide dismutase （SOD）， and malondialdehyde （MDA） levels were measured by colorimetry； mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction（Real-time PCR） and Wes automated protein expression system. ResultsCompared with 12MCON， the 15MCON group showed significantly increased hepatic TG， Cu²⁺， ROS， and MDA levels （P<0.01）， decreased SOD （P<0.01）， hepatocyte swelling， and disordered arrangement. The mRNA and protein levels of ferredoxin 1 （FDX1）， dihydrolipoamide S-acetyltransferase （DLAT）， heat shock protein 70 （HSP70）， dihydrolipoamide dehydrogenase （DLD）， pyruvate dehydrogenase E1 subunit-β （PDHB）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and peroxisome proliferator-activated receptor γ （PPARγ） were significantly elevated （P<0.05， P<0.01）. Compared with 15MCON group， the 15MHFD and 20MCON groups exhibited further increases in TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group， and no significant lipid deposition was observed in the 20MCON group. FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and protein levels were significantly increased （P<0.05， P<0.01）. Compared with 20MCON group， the model group demonstrated markedly elevated TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， severe hepatic steatosis， and upregulated expression of FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and proteins （P<0.05， P<0.01）. All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.

ObjectiveThis paper aims to investigate the role of NDC80 kinetochore complex component （NUF2） and magnesium homeostasis in ovarian cancer cell apoptosis， as well as the regulatory mechanism of gypenoside L （Gyp-L） on NUF2 and magnesium homeostasis. MethodsOvarian cancer OVCAR3 cells were divided into a blank control group， a low-concentration Gyp-L group （50 µmol·L^-1）， a high-concentration Gyp-L group （100 µmol·L^-1）， and a cisplatin （15 µmol·L^-1） group. The migration， proliferation， and apoptosis capabilities of OVCAR3 cells were evaluated through cell scratch assays， clonal experiments， and terminal-deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling assay （TUNEL） staining. Differentially expressed genes of ovarian cancer were screened by using the Gene Expression Omnibus （GEO） database. The interaction relationships of differentially expressed genes and proteins were analyzed via the Search Tool for Recurring Instances of Neighbouring Genes （STRING） database. The prognostic survival analysis was performed by using the Tumor Immune Estimation Resource （TIMER） database， and the differential expression levels of genes were validated with the Gene Expression Profiling Interactive Analysis （GEPIA） database. The mRNA expression levels of NUF2， magnesium homeostasis-related indicators， such as magnesium transporter 1 （MAGT1）， non-imprinted in Prader-Willi/Angelman syndrome 1 （NIPA1）， NIPA-like domain containing 1 （NIPAL1）， as well as apoptosis-related indicators B cell lymphoma-2 （Bcl-2） and Bcl-2-associated X protein （Bax） in OVCAR3 cells， were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. The protein expression levels of NUF2， MAGT1， NIPA1， NIPAL1， Bcl-2， and Bax in OVCAR3 cells were quantitatively analyzed by ProteinSimple WES. A model of overexpression of NUF2 was constructed， and Gyp-L intervention was performed. The molecular mechanism by which Gyp-L induces ovarian cancer cell apoptosis by regulating NUF2 and influencing magnesium homeostasis was quantitatively analyzed and detected through cell cloning， TUNEL staining， Real-time PCR， and ProteinSimple WES. Finally， the Mg²⁺ content and protein synthesis efficiency were detected by immunofluorescence. ResultsGyp-L significantly inhibited the migration and proliferation capabilities of OVCAR3 cells and promoted their apoptosis （P<0.05）. Overexpression of NUF2 markedly increased the expression levels of MAGT1， NIPA1， NIPAL1， and Bcl-2， while reducing the expression level of Bax （P<0.05）. It also significantly elevated intracellular Mg²⁺ content and protein synthesis efficiency and simultaneously inhibited apoptosis （P<0.05）. Gyp-L could reverse the magnesium homeostasis imbalance and apoptosis inhibition caused by the overexpression of NUF2， downregulating the expression levels of NUF2， MAGT1， NIPA1， NIPAL1， and Bcl-2 （P<0.05）， while upregulating the expression level of Bax （P<0.05）. ConclusionGyp-L can inhibit the occurrence of ovarian cancer， and its mechanism may involve inhibiting the expression of NUF2 to maintain magnesium homeostasis and inducing apoptosis of ovarian cancer cells.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Peroxisome proliferator-activated receptor γ coactivator 1 α (PGC-1α) is a core member of the PGC-1 family and serves as a transcriptional coactivator, playing a crucial regulatory role in various diseases. Mitochondria, the main site of cellular energy metabolism, are essential for maintaining cell growth and function. Their function is regulated by various transcription factors and coactivators. PGC-1α regulates the biogenesis, dynamics, energy metabolism, calcium homeostasis, and autophagy processes of mitochondria by interacting with multiple nuclear transcription factors, thereby exerting significant effects on mitochondrial function. This review explores the biological functions of PGC-1α and its regulatory effects and related mechanisms on mitochondria, providing important information for our in-depth understanding of the role of PGC-1α in cellular metabolism. The potential role of PGC-1α in metabolic diseases, cardiovascular diseases, and neurodegenerative diseases was also discussed, providing a theoretical basis for the development of new treatment strategies.
Humans ; Mitochondria/metabolism* ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/physiology* ; Animals ; Energy Metabolism/physiology* ; Neurodegenerative Diseases/physiopathology* ; Autophagy/physiology* ; Transcription Factors/physiology* ; Metabolic Diseases/physiopathology* ; Cardiovascular Diseases/physiopathology*

At present, the cause of traditional Chinese medicine(TCM) in China has entered a new period of high-quality development. How to strengthen the foundation for the TCM industry from the source is an important issue that deserves the attention of the authorities, industry, and academia. This study systematically analyzed the regulatory system of TCM raw materials and preparations. The study took the TCM industry chain and the product life cycle as a clue and focused on the dimensions of TCM resource protection and plant cultivation(farming), production and quality supervision of TCM raw materials and preparations, and their market access and distribution. It analyzed the current situation of the regulation of TCM raw materials and preparations under the regulatory system of drugs, discussed the main problems, and put forward corresponding suggestions. The results can provide an important reference value for the subsequent improvement of the regulatory system of drugs and the construction of a prominent regulatory system of drugs in accordance with TCM characteristics.
Drugs, Chinese Herbal/economics* ; Medicine, Chinese Traditional/standards* ; China ; Quality Control ; Humans ; Plants, Medicinal/chemistry*

Hepatic fibrosis is a key pathological process in the development of chronic liver disease to cirrhosis, and its core mechanism involves the activation of hepatic stellate cells(HSC) and abnormal deposition of extracellular matrix(ECM). Although existing treatments, such as antiviral drugs, can delay disease progression, they have the problem of single therapeutic targets and cannot reverse fibrosis. Accordingly, multidimensional intervention strategies are urgently needed. Recent studies have shown that circadian rhythm disorders aggravate hepatic fibrosis by regulating metabolism, immunity, and inflammation. Traditional Chinese medicine(TCM) plays a unique role in restoring the circadian clock via multi-target and holistic regulation. This paper establishes a three-dimensional network by systematically integrating biological clock, metabolism, and immunity for the first time to elucidate the scientific connotation of the theory of time-concerned treatment of TCM, and proposes a new strategy for the development of time-targeted compound prescriptions, providing innovative ideas for the treatment of hepatic fibrosis.
Humans ; Liver Cirrhosis/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Circadian Rhythm/drug effects* ; Animals ; Medicine, Chinese Traditional ; Hepatic Stellate Cells/drug effects*

Clinical grading diagnosis of disorder of consciousness (DOC) patients relies on behavioral assessment, which has certain limitations. Combining multi-modal technologies and brain-computer interface (BCI) paradigms can assist in identifying patients with minimally conscious state (MCS) and vegetative state (VS). This study collected electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals under motor BCI paradigms from 14 DOC patients, who were divided into two groups based on clinical scores: 7 in the MCS group and 7 in the VS group. We calculated event-related desynchronization (ERD) and motor decoding accuracy to analyze the effectiveness of motor BCI paradigms in detecting consciousness states. The results showed that the classification accuracies for left-hand and right-hand movement tasks using EEG were 93.28% and 76.19% for the MCS and VS groups, respectively; the classification precisions using fNIRS were 53.72% and 49.11% for these groups. When combining EEG and fNIRS features, the classification accuracies for left-hand and right-hand movement tasks in the MCS and VS groups were 95.56% and 87.38%, respectively. Although there was no statistically significant difference in motor decoding accuracy between the two groups, significant differences in ERD were observed between different consciousness states during left-hand movement tasks ( P < 0.001). This study demonstrates that motor BCI paradigms can assist in assessing the level of consciousness, with EEG being more sensitive for evaluating residual motor intention intensity. Moreover, the ERD feature of motor intention intensity is more sensitive than BCI classification accuracy.
Humans ; Brain-Computer Interfaces ; Spectroscopy, Near-Infrared/methods* ; Electroencephalography/methods* ; Consciousness Disorders/diagnosis* ; Male ; Movement ; Adult ; Female ; Intention ; Persistent Vegetative State/diagnosis*