Objective: To report the antibody identification, blood management during pregnancy and the monitoring process of fetal hemolytic disease of fetus and newborn (HDFN) in a pregnant woman with a history of blood transfusion and pregnancy who developed anti-Jr . Methods: Saline tube technique and anti-human globulin technique were used for maternal blood typing, unexpected antibody screening and identification, as well as for determining antibody titer and IgG subclasses. PCR-SSP was employed for genotyping of 18 blood group systems. Next-generation sequencing (NGS) was utilized for gene sequencing of 38 blood group systems. Sanger sequencing was applied to verify rare blood group mutations detected by NGS and to investigate the corresponding rare blood group genes in family members. Blood preparation was achieved through anemia management in prenatal clinics and autologous blood collection during pregnancy. The newborn underwent the three primary tests for HDFN and plasma IgG subclass testing. Results: The pregnant woman's blood type was B, RhD positive, with a positive unexpected antibody screen, and the antibody identification pattern was consistent with a high-frequency antigen antibody. Gene sequencing revealed a homozygous ABCG2 c.376C>T mutation in the woman, resulting in the Jr(a-) phenotype, and anti-Jr antibody was present in her plasma. No compatible Jr(a-) blood was found among family members. The maternal anti-Jr IgG titer remained stable at 256 during pregnancy, with no detectable IgG1 or IgG3 subclasses against the Jr antigen. A total of 800 mL of autologous blood was collected in two stages during pregnancy. The newborn was B, RhD positive, Jr(a+), with a positive unexpected antibody screen (anti-Jr ). IgG subclass typing detected no IgG1 or IgG3. The direct antiglobulin test was positive, while the acid elution test was negative. Conclusion: The combination of serology and blood group genetic analysis provides a diagnostic basis for identifying antibodies to high-frequency antigens. Managing perinatal anemia and implementing staged autologous blood storage can secure blood supply for the perioperative period. IgG antibody subclass typing offers a reference for clinical assessment and prevention of HDFN.

A 42-year-old male with chest tightness and dyspnea was admitted to the hospital. Chest CT indicated diffuse interstitial lung infiltration. Despite receiving anti-infective therapy, glucocorticoid therapy, and immunosuppressive agents, the patient developed refractory hypoxaemia. Endotracheal intubation and invasive mechanical ventilation failed to improve oxygenation. Therefore the patient was diagnosed with rapidly progressive interstitial lung disease (RP-ILD) accompanied by type Ⅰ respiratory failure. Veno-venous (VV) extracorporeal membrane oxygenation (ECMO) was initiated, and oxygenation improved in this patient. The patient subsequently underwent bilateral lung transplantation with veno-arterio-venous (VAV) ECMO support. ECMO machine was withdrawn on day 1, and extubation was achieved on day 9 after surgery. Histopathology revealed fibrotic nonspecific interstitial pneumonia (NSIP) with hyaline membrane formation. The patient developed ICU-acquired myasthenia and received early rehabilitation, with gradual recovery of muscle strength. During follow-up, graft lung function remained stable. This case demonstrates that ECMO can serve as a bridge to lung transplantation in RP-ILD patients.

In this study, the synthetic process of 18α-glycyrrhizic acid was optimized. Using 18β-glycyrrhizic acid monoammonium salt as the starting material, the target compound 18α-glycyrrhizic acid was obtained through isomerization, esterification, and hydrolysis, with a total yield of 9.43%, purity of 99.23% and key impurity A of 0.17% (HPLC). The optimized process significantly improved the isomerization conversion rate, reduced the formation of related substances, simplified the purification steps, and enhanced both industrial scalability and cost efficiency.

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

Diabetes mellitus type 2 (T2DM) is one of the most common metabolic diseases in the world and has a significant impact on the health of patients. As a key factor in cellular mechanical transduction, Piezo1 protein plays a crucial role in regulating the basic life activities of the body. By participating in energy metabolism, it not only promotes the improvement of basic metabolic rate, but also helps to maintain the stability of the internal environment of the body. The activation of Piezo1 pathway has a significant effect on the release of insulin by islet beta cells, and also plays an important role in the production of adipose tissue after food intake. This study reviews the effects of exercise intervention on the expression and function of Piezo1 protein, as well as its role in metabolic regulation and insulin level regulation in T2DM patients. The study showed that a modest exercise intervention activated Piezo1 signaling pathway, which improved insulin sensitivity and improved sugar metabolism. In addition, the activation of Piezo1 pathway is closely related to the metabolic regulation of adipose tissue, helping to regulate the differentiation and maturation of adipose cells, thereby affecting the metabolic function of adipose tissue. Based on a comprehensive analysis of existing literature, Piezo1 pathway is found to play a complex role in the pathogenesis of T2DM. Exercise intervention, as a non-drug therapy, provides a new strategy for the treatment of T2DM by activating Piezo1 signaling pathway. However, the exact mechanism of action of Piezo1 pathway in T2DM still needs further investigation. Future studies should focus on the interaction between the Piezo1 pathway and T2DM, and how to regulate the Piezo1 pathway to optimize treatment for T2DM. The effects of exercise intervention on Piezo1 protein and its role in metabolic regulation and insulin level regulation of T2DM patients were comprehensively analyzed in this paper, aiming to provide a new perspective for further research and development of therapeutic strategies for metabolic diseases such as diabetes and obesity.

AIM: To compare the changes in corneal epithelial thickness(CET)after small incision lenticule extraction(SMILE)and femtosecond laser-assisted in situ keratomileusis(FS-LASIK).METHODS: A total of 187 patients(187 eyes)who underwent either SMILE or FS-LASIK at Urumqi Aier Eye Hospital between December 2022 and November 2023 were collected. The patients were divided into SMILE group and FS-LASIK group according to surgical methods. The CET of the patients was measured by optical coherence tomography(OCT)system before surgery and at 1 wk, 1, 3, and 6 mo postoperatively.RESULTS: Changes in corneal epithelial thickness(△CET)in the central, paracentral, and mid-peripheral regions were compared at 6 mo postoperatively. The SMILE group was characterized by the most significant thickening in the central area and the least thickening in the mid-peripheral area; while the FS-LASIK group was characterized by the most significant thickening in the paracentral area and the least thickening in the mid-peripheral region. At 1 wk, 1, 3, and 6 mo postoperatively, within the 0-7 mm corneal area, the △CET for both the SMILE and FS-LASIK groups was correlated with the preoperative spherical equivalent.CONCLUSION: Within 6 mo postoperatively, both SMILE and FS-LASIK showed a similar trend in epithelial thickening but with distinct characteristics. The change in corneal epithelial thickness for both procedures was positively correlated with the preoperative diopter.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.