[Objective] To compare next generation sequencing (NGS) library construction technology between probe hybridization capture and amplicon methods, and analyze the influencing factors of HLA genotyping resolution level and its prospects in clinical applications. [Methods] A total of 207 clinical samples with known typing results and samples from the proficiency testing plan were selected. The conformity rate of HLA genotyping results, allele coverage and typing data analysis indicators were confirmed, and the effects of two library construction methods on the level of HLA genotyping discrimination were compared. [Results] The concordance rate of 207 samples with the feedback results of PT or prior well-characterized HLA genotypes was 100%. Among them, 91 samples were captured using hybridization probe capture method. Compared with the original amplicon method, the hybridization probe capture method can distinguish the alleles of DRB1 and DPB1 that cannot be determined in 13 samples. The allelic imbalance of DRB1, DPA1, and DQB1 loci in 6 samples was resolved. Three samples were found to have missed detection of alleles at the DQA1 and DQB1 loci. [Conclusion] The performance indicators of hybridization probe capture and amplicon performance confirmation meet the requirements of clinical detection of HLA genotyping, which provides an experimental method and basis for clinical application.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Systemic lupus erythematosus （SLE）， a refractory autoimmune disease， is among the dominant diseases where traditional Chinese medicine （TCM） shows advantages in the field of rheumatology and immunology. The China-Japan Friendship Hospital hosted the "46^th Youth Salon on Dominant Diseases （Systemic Lupus Erythematosus）" organized by the China Association of Chinese Medicine， which led to a consensus on "the advantages， challenges， interdisciplinary approaches， and translational achievements of integrated TCM and Western medical approaches in the diagnosis and treatment of SLE." The diagnosis and treatment of SLE currently face several challenges， such as frequent misdiagnosis and missed diagnosis in the early stages， difficulty in achieving treatment targets， multiple side effects from pharmacotherapy， and the lack of management strategies for special populations， all of which hinder the fulfillment of the clinical needs of patients. Integrated TCM and Western medical approaches can improve clinical symptoms such as skin erythema， aversion to cold and cold limbs， fatigue， dry mouth， restlessness， and heat sensation in the palms and soles， thereby improving patients' quality of life. The approaches also help consolidate the efficacy of conventional Western medicine， slow disease progression， reduce relapse rates， address multi-organ involvement， and prevent or treat complications. Additionally， they enhance efficacy and reduce toxicity， prevent the side effects of Western medications， help reduce hormone use， and offer distinct advantages in the individualized intervention of special populations， contributing to the whole-process management of the disease. However， evidence-based medical support for this integrated approach remains limited， and the quality of available evidence is generally low. Common evaluation systems and modern research methodologies should be adopted to clarify the efficacy of TCM in SLE treatment. Efforts should be made to carry out high-quality evidence-based medical research， strengthen the development of fundamental and pharmacological research， and further explain the distinct advantages of TCM in the diagnosis and treatment of SLE. Future efforts should focus on advancing the integration of TCM and modern medicine， incorporating multi-omics technologies， individualized stratification， and other precision medicine concepts， in combination with artificial intelligence. Moreover， interdisciplinary collaboration should be promoted to utilize modern technology in exploring the essence of TCM theories and screening effective formulae， thereby comprehensively improving the diagnosis and treatment of SLE through integrated TCM and Western medical approaches.

Systemic lupus erythematosus （SLE）， a refractory autoimmune disease， is among the dominant diseases where traditional Chinese medicine （TCM） shows advantages in the field of rheumatology and immunology. The China-Japan Friendship Hospital hosted the "46^th Youth Salon on Dominant Diseases （Systemic Lupus Erythematosus）" organized by the China Association of Chinese Medicine， which led to a consensus on "the advantages， challenges， interdisciplinary approaches， and translational achievements of integrated TCM and Western medical approaches in the diagnosis and treatment of SLE." The diagnosis and treatment of SLE currently face several challenges， such as frequent misdiagnosis and missed diagnosis in the early stages， difficulty in achieving treatment targets， multiple side effects from pharmacotherapy， and the lack of management strategies for special populations， all of which hinder the fulfillment of the clinical needs of patients. Integrated TCM and Western medical approaches can improve clinical symptoms such as skin erythema， aversion to cold and cold limbs， fatigue， dry mouth， restlessness， and heat sensation in the palms and soles， thereby improving patients' quality of life. The approaches also help consolidate the efficacy of conventional Western medicine， slow disease progression， reduce relapse rates， address multi-organ involvement， and prevent or treat complications. Additionally， they enhance efficacy and reduce toxicity， prevent the side effects of Western medications， help reduce hormone use， and offer distinct advantages in the individualized intervention of special populations， contributing to the whole-process management of the disease. However， evidence-based medical support for this integrated approach remains limited， and the quality of available evidence is generally low. Common evaluation systems and modern research methodologies should be adopted to clarify the efficacy of TCM in SLE treatment. Efforts should be made to carry out high-quality evidence-based medical research， strengthen the development of fundamental and pharmacological research， and further explain the distinct advantages of TCM in the diagnosis and treatment of SLE. Future efforts should focus on advancing the integration of TCM and modern medicine， incorporating multi-omics technologies， individualized stratification， and other precision medicine concepts， in combination with artificial intelligence. Moreover， interdisciplinary collaboration should be promoted to utilize modern technology in exploring the essence of TCM theories and screening effective formulae， thereby comprehensively improving the diagnosis and treatment of SLE through integrated TCM and Western medical approaches.

Objective: In in vitro systems for differentiating and expanding natural killer (NK) cells, feeder cells provide essential cell-cell contact and paracrine signals that drive precursor proliferation and terminal maturation. However, existing xenogeneic feeder cells or tumor-derived genetically modified feeder cells pose risks of residual immunogenicity and malignant transformation, limiting clinical use. This study aims to develop a humanized mesenchymal-like stromal cell (hematopoietic organoid-derived human mesenchymal stromal cells, HO-hMSCs) derived from iPSC-based hematopoietic organoids, and elucidate its mechanisms of NK-supportive activity to enable a safe, efficient platform for clinical-grade NK cell production. Methods: Human induced pluripotent stem cells (iPSCs) were differentiated into hematopoietic organoids, from which HO-hMSCs were isolated. Flow-cytometric phenotyping and bulk RNA-sequencing were performed to compare HO-hMSCs with umbilical cord-derived MSCs (UC-hMSCs). The effect of HO-hMSCs on NK cell differentiation efficiency (CD3 CD56 ) and effector maturation (CD16 expression) were assessed by co-culture experiments, using UC-hMSCs as control. Results: 1) Hematopoietic organoid induction and NK differentiation: iPSCs were induced to form hematopoietic organoids using cytokine cocktails, which further differentiated into high-purity CD45 CD56 NK cells [(82.8%±12.07)% efficiency on day 21]. 2) HO-hMSC characteristics: HO-hMSCs exhibited upregulated expression of Notch pathway ligands (DLL4, JAG1, 4.06-8.04-fold), homeobox genes (HOXA3, HOXA5, log FC=1.28 and 1.44), and key regulators of NK development (GATA3, BCL11A) and cytokine receptors (IL7R, IL27RA, 6.76 to 13.34-fold increase). 3) Functional validation: Compared to UC-hMSCs, HO-hMSCs co-culture significantly enhanced NK cell proportion by 30.5% (P<0.05) and increased CD16 positivity (+20.5%). Conclusion: This study for the first time reveals that human hematopoietic organoid-derived HO-hMSCs possess potent hematopoietic niche-supportive activity. It provides a humanized, feeder-free platform for robust clinical-grade NK cell production and expands the translational utility of organoid technologies in cell therapy.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.