With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To explore the clinical characteristics of patients with diffuse large B-cell lymphoma (DLBCL) accompanied with KMT2D gene mutation and the impact of its co-mutated genes on prognosis. Methods Clinical data of 155 newly diagnosed DLBCL patients were obtained. The second-generation sequencing method was used to detect 475 hotspot genes, including KMT2D mutation. Patients were divided into the KMT2D mutation group and KMT2D wild-type group based on the presence or absence of KMT2D gene mutation. Clinical characteristics, differences in co-mutated genes, and survival differences between the two groups were compared. Results The frequency of KMT2D mutation was 31%, which is predominantly observed in elderly patients (P=0.07) and less in the double-expressor phenotype (P=0.07). Compared with the KMT2D wild-type group, KMT2D gene mutation was associated with higher co-mutation rates of CDKN2A (OR=2.82, P=0.01) and BCL2 (OR=3.84, P=0.016), while being mutually exclusive with MYC gene mutation (OR=0.11, P=0.013). In univariate survival analysis, no statistically significant difference in overall survival (OS) was found between the KMT2D mutation group and the wild-type group (P=0.54). Further analysis of the prognostic significance of KMT2D with other gene mutations indicated that patients with KMT2D^mutBTG2^mut had poorer OS than those with KMT2D^wt BTG2^mut (P=0.07) and KMT2D^wt BTG2^wt (P=0.05). On the contrary, patients with KMT2D^mut CD79B^mut had better OS than those with KMT2D^mut CD79B^wt (P=0.09), with no prognostic impact observed for other co-mutated genes. Multivariate Cox regression analysis revealed that Ann Arbor stages Ⅲ and Ⅳ (HR=2.751, 95%CI: 1.169-6.472, P=0.02), elevated LDH levels (HR=2.461, 95%CI: 1.396-4.337, P=0.002), Ki-67 index>80% (HR=1.875, 95%CI: 1.066-3.299, P=0.029), and KMT2D^mutBTG2^mut(HR=4.566, 95%CI: 1.348-15.471, P=0.015) were independent risk factors for OS in patients with DLBCL (P<0.05). Conclusion DLBCL patients with KMT2D mutation often have multiple gene mutations, among which patients with a co-mutated BTG2 gene have poor prognosis.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

AIM: To explore the relationship between hyperopia reserve and ocular biometric parameters in 4-14 year-old Uyghur students from Hotan County, Xinjiang, and to provide scientific evidence for myopia prevention.METHODS: From September 1 to October 31, 2023, a stratified random cluster sampling method was used to select 3 264 students(3 264 eyes)from 6 schools in Hotan County. Participants underwent uncorrected distance visual acuity testing, cycloplegic refraction, and ocular biometric measurements. The correlation between spherical equivalent(SE)and ocular biometric parameters was analyzed by multiple linear regression.RESULTS: A total of 1 998 non-myopic students(1 998 eyes)were included in the study, with 1 354 students(67.77%)showing insufficient hyperopia reserve. The detection rate of insufficient hyperopia reserve decreased with age, from 94.12% at age 4 to 18.13% at age 14(P<0.001). Multiple linear regression analysis showed that in the group with sufficient hyperopia reserve, age, gender, uncorrected distance visual acuity, axial length(AL), and keratometry(K)explained 66.5% of the variance in SE; while in the group with insufficient hyperopia reserve, these factors explained only 28.0% of the SE variance.CONCLUSION: In non-myopic Uyghur students aged 4-14 in Hotan County, Xinjiang, the detection rate of insufficient hyperopia reserve was 67.77%. In the group with insufficient hyperopia reserve, age, gender, AL, and K explained only a small portion of the SE variance, suggesting that the refractive status of this population may be influenced by more complex factors.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis （AIH）-related decompensated cirrhosis， to identify independent predictive factors， and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 （n=211）. The primary endpoint was achievement of recompensation， and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up， the patients were divided into the recompensation group （n=16） and the persistent decompensation group（n=150）.The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance， and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； the Kaplan-Meier method was used for survival analysis； the Cox proportional-hazards regression model was used to identify independent predictive factors， and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled， with a median age of 55.0 years and a median follow-up time of 44.0 months， and female patients accounted for 87.2%. Among the 211 patients， 61 （with a cumulative proportion of 35.5%） achieved recompensation. Compared with the persistent decompensation group， the recompensation group had significantly higher white blood cell count， platelet count （PLT）， total bilirubin （TBil）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total bile acid， prothrombin time， international normalized ratio （INR）， SMA positive rate， Model for End-Stage Liver Disease （MELD） score， Child-Pugh score， and rate of use of glucocorticoids （all P0.05）， as well as significantly lower age at baseline， number of complications， and death/liver transplantation rate （all P0.05）. At 3 and 12 months after treatment， the recompensation group had continuous improvements in AST， TBil， INR， IgG， MELD score， and Child-Pugh score， which were significantly lower than the values in the persistent decompensation group （all P0.05）， alongside with continuous increases in PLT and albumin， which were significantly higher than the values in the persistent decompensation group （P0.05）. The multivariate Cox regression analysis showed that baseline ALT （hazard ratio ［HR］=1.067， 95% confidence interval ［CI］： 1.010 — 1.127， P=0.021）， IgG （HR=0.463，95%CI：0.258 — 0.833， P=0.010）， SMA positivity （HR=3.122，95%CI：1.768 — 5.515， P0.001）， and glucocorticoid therapy （HR=20.651，95%CI：8.744 — 48.770， P0.001） were independent predictive factors for recompensation， and the nomogram model based on these predictive factors showed excellent predictive performance （C-index=0.87，95%CI：0.84 — 0.90）. ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity， a high level of ALT， a low level of IgG， and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.

With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*