Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

Objective:To investigate the effects of body habitus and gender on radiation dose assessment methodologies in low-dose chest CT, with particular emphasis on clarifying discrepancies among various dose quantification approaches and their associations with patient characteristics.Methods:Imaging data from 19 371 patients who underwent low-dose chest CT at the First Affiliated Hospital of Chongqing Medical University between January 2021 and January 2024 were retrospectively analyzed. Patients were categorized into eight groups based on water-equivalent diameter (WED) and gender: Group A (150 mm≤WED<210 mm; 71 males, 1 032 females), Group B (210 mm≤WED<260 mm; 4 525 males, 8 005 females), Group C (260 mm≤WED<300 mm; 4 234 males, 1 105 females), and Group D (WED≥300 mm; 357 males, 42 females). WED, size-specific dose estimate (SSDE), and organ dose-based effective dose(ED Radimetrics)were calculated using Radimetrics software. Scanner-reported dose metrics, including volume CT dose index (CTDIvol), dose-length product (DLP), and DLP-derived effective dose(ED DLP), were recorded. The ratios of SSDE/CTDIvol and ED Radimetrics/ED DLP were used to quantify discrepancies between dose evaluation methods. The Kruskal-Wallis test was employed to analyze dose metric differences across WED groups within the same gender, while the Wilcoxon rank-sum test compared gender-based differences within each WED group. Results:All dose metrics significantly increased with WED for both genders (all P<0.05). Within the same WED group, ED Radimetrics was significantly higher in females ( P<0.05), whereas ED DLP was higher in males ( P<0.05). The SSDE/CTDIvol ratio decreased with increasing WED, declining from 1.74 in Group A to 1.16 in Group D for females and from 1.68 to 1.12 for males. The ED Radimetrics/ED DLP ratio exhibited a decreasing trend with WED in females (1.82 to 1.30) but showed an initial increase in males (1.29 in Group A to 1.31 in Group B) before decreasing to 0.94 in Group D (all intergroup P<0.05). SSDE/CTDIvol and ED Radimetrics/ED DLP ratios of females were consistently higher than that of males within each WED group (all P<0.05). Conclusions:Patient body habitus and gender significantly influence radiation dose distribution in low-dose chest CT. Larger body habitus is associated with higher radiation doses, while females receive greater ED Radimetrics than males within comparable body habitus. Traditional dose metrics (CTDIvol and ED DLP) were underestimated for patients with small body sizes and female individuals.

Objective Readout segmentation of long variable echo-trains diffusion weighted imaging(RESOLVE DWI)was used to analyze the difference of apparent diffusion coefficient(ADC)value in deep cerebral nucleus and its correlation with clinical characteristics in patients with Parkinson's disease(PD).Methods Clinical data of 60 patients with PD were retrospectively analyzed as PD group,and were divided in-to the tremor group(n=30)and the bradykinesia group(n=30)according to symptom type,middle-aged(≤65 years old)group(n=23)and elderly(＞65 years old)group(n=37)according to age,and 60 healthy vol-unteers were selected as the control group during the same period.ADC values were measured on the ADC map of RESOLVE DWI sequence,and the ADC values of bilateral putamen,pallidus,substantia nigra,rubra,and dentate nucleus were analyzed and their correlation with UPDRS-Ⅲ score and H&Y grading.Results Compared with the control group,the ADC values of both putamen,globus pallidus,globus pallidus,red nucleus,right substantia nigra and right dentate nucleus were increased in the PD group,the ADC values of both putamen,globus pallidus,red nucleus and right substantia nigra in the tremor group were increased,and the ADC values of right putamen,globus pallidus and bilateral red nucleus in the bradykinesia group were increased(P＜0.05).Compared with the bradykinesia group,the values of ADC in the tremor group were similar.Compared with the middle-aged group,the ADC values of right putamen,bilateral globus pallidus,left substantia nigra and left red nucleus were higher in the elderly group(P＜0.05).In the PD group,the ADC values of the right putamen,globus pallidus,and dentate nucleus were positively correlated with H&Y grade and UPDRS-Ⅲscore,and the ADC value of the left putamen was positively correlated with H&Y grade.Conclusion RE-SOLVE DWI can be used to evaluate the differences in deep gray matter nuclei in PD patients,and its ADC value may be used to evaluate and predict the severity of nuclear mass damage and motor symptoms in PD pa-tients.

Medical image recognition is a technology that utilizes computer algorithms to process,analyze and understand medical images,aiming to identify various patterns,targets and objects,thereby aiding doctors in more accurate diagnosis and treatment.Current researches in medical image recognition mainly focuses on medical image classification,lesion location and segmentation,image registration and fusion,content-based image retrieval,as well as three-dimensional reconstruction and visualization.The review provides a summary of the research directions and trends in medical image recognition,introducing concepts and technologies such as deep learning,multimodal fusion,three-dimensional reconstruction and visualization.It also highlights the applications of medical image recognition in medical imaging diagnosis,pathological analysis and radiotherapy planning,while pointing out the existing problems and challenges.Furthermore,the future developments and challenges of medical image recognition technology are put forward for providing a reference for medical image recognition research and clinical medical image analysis.

Medical image recognition is a technology that utilizes computer algorithms to process,analyze and understand medical images,aiming to identify various patterns,targets and objects,thereby aiding doctors in more accurate diagnosis and treatment.Current researches in medical image recognition mainly focuses on medical image classification,lesion location and segmentation,image registration and fusion,content-based image retrieval,as well as three-dimensional reconstruction and visualization.The review provides a summary of the research directions and trends in medical image recognition,introducing concepts and technologies such as deep learning,multimodal fusion,three-dimensional reconstruction and visualization.It also highlights the applications of medical image recognition in medical imaging diagnosis,pathological analysis and radiotherapy planning,while pointing out the existing problems and challenges.Furthermore,the future developments and challenges of medical image recognition technology are put forward for providing a reference for medical image recognition research and clinical medical image analysis.

Objective:To investigate the effects of body habitus and gender on radiation dose assessment methodologies in low-dose chest CT, with particular emphasis on clarifying discrepancies among various dose quantification approaches and their associations with patient characteristics.Methods:Imaging data from 19 371 patients who underwent low-dose chest CT at the First Affiliated Hospital of Chongqing Medical University between January 2021 and January 2024 were retrospectively analyzed. Patients were categorized into eight groups based on water-equivalent diameter (WED) and gender: Group A (150 mm≤WED<210 mm; 71 males, 1 032 females), Group B (210 mm≤WED<260 mm; 4 525 males, 8 005 females), Group C (260 mm≤WED<300 mm; 4 234 males, 1 105 females), and Group D (WED≥300 mm; 357 males, 42 females). WED, size-specific dose estimate (SSDE), and organ dose-based effective dose(ED Radimetrics)were calculated using Radimetrics software. Scanner-reported dose metrics, including volume CT dose index (CTDIvol), dose-length product (DLP), and DLP-derived effective dose(ED DLP), were recorded. The ratios of SSDE/CTDIvol and ED Radimetrics/ED DLP were used to quantify discrepancies between dose evaluation methods. The Kruskal-Wallis test was employed to analyze dose metric differences across WED groups within the same gender, while the Wilcoxon rank-sum test compared gender-based differences within each WED group. Results:All dose metrics significantly increased with WED for both genders (all P<0.05). Within the same WED group, ED Radimetrics was significantly higher in females ( P<0.05), whereas ED DLP was higher in males ( P<0.05). The SSDE/CTDIvol ratio decreased with increasing WED, declining from 1.74 in Group A to 1.16 in Group D for females and from 1.68 to 1.12 for males. The ED Radimetrics/ED DLP ratio exhibited a decreasing trend with WED in females (1.82 to 1.30) but showed an initial increase in males (1.29 in Group A to 1.31 in Group B) before decreasing to 0.94 in Group D (all intergroup P<0.05). SSDE/CTDIvol and ED Radimetrics/ED DLP ratios of females were consistently higher than that of males within each WED group (all P<0.05). Conclusions:Patient body habitus and gender significantly influence radiation dose distribution in low-dose chest CT. Larger body habitus is associated with higher radiation doses, while females receive greater ED Radimetrics than males within comparable body habitus. Traditional dose metrics (CTDIvol and ED DLP) were underestimated for patients with small body sizes and female individuals.

Flow cytometry (FCM) is a technique that can perform the multiparametric analysis of single cell. Recently, FCM has become an important tool to assist the management of chronic diseases. The clinical application of FCM has expanded from blood diseases such as leukemia and lymphoma to other chronic diseases such as solid tumors and chronic obstructive lung. Besides, FCM plays an important role in improving the efficacy of early diagnosis, monitoring on the immune status of patients, understanding of the disease progression, and assessment of prognosis of patients. Henceforth, more assistance could be provided by FCM to optimize the management of chronic diseases with the continuous innovation.

Flow cytometry (FCM) is an interdisciplinary cell analysis technology that integrates optics, fluid dynamics, electronics, and computer science. While FCM is widely utilized in diagnosing and monitoring hematologic malignancies, its application in nonhematopoietic neoplasms (NHN) remains in its nascent stages. However, recent advancements in science and technology have led to the emergence of innovative FCM technologies, such as mass spectrometry flow cytometry (CyTOF) and spectral flow cytometry (SFC), offering promising avenues for their clinical application aiming to assist the clinical diagnosis of NHN patients. This review summarizes the features of fundamentals of traditional FCM, CyTOF, and SFC technologies, along with their applications and future prospective in NHN diagnosis and treatment, aiming to offer updated insights for the continued expansion and utilization of FCM technology in clinical laboratory settings.

In recent years， data mining algorithms have been widely employed in scientific research within the field of traditional Chinese medicine （TCM）. The data mining algorithms are used to effectively handle and analyze the complex data in TCM formulas， providing a rational explanation for the mechanism of action. This method has proven particularly useful in uncovering patterns of compatibility and frequent combinations of herbs in TCM， thereby enhancing the reliability and accuracy of clinical diagnosis， target screening， and the study of new drugs. This paper reviews and analyzes 147 papers on TCM formula research that utilize data mining algorithms. The results indicate that data mining algorithms play a unique advantage in six sub- areas， including the study on the mechanism of action in TCM formula， the dose-efficacy of TCM formulas， the identification of core drugs pairs/groups， mining the relationships among “formulas-drug-symptom”， the discovery of new formulas， and mining the compatibility law. Notably， association rules and clustering algorithms are the most representative.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative method for various hematological diseases. With the optimization of transplantation technology, the clinical application of allo-HSCT is more and more mature. Post-transplant liver injury is one of the common postoperative complications, which seriously affects the quality of life and long-term survival of patients. The causes of liver injury after allo-HSCT can be divided into non-infectious and infectious factors, which show similar clinical manifestations and different treatment principles. Timely diagnosis of post-transplant liver injury and the identification of the disease cause will be beneficial for early prevention or targeted treatment, thereby improving patients' prognosis. This review focuses on the etiology, clinical features, and treatment options of liver injury after allo-HSCT, aiming to deepen the understanding of hematologists on liver injury after allo-HSCT.