Objective To predict the lymphovascular invasion(LVI)status of breast cancer patients based on digital breast tomo-synthesis(DBT)intratumoral and peritumoral radiomics nomogram.Methods A total of 192 breast cancer patients from 2 institu-tions were retrospectively selected,in which institution 1 was used for train(n=113)and test(n=49),while institution 2 was used for external validation(n=30).Radiomics features were extracted and selected based on intratumoral and peritumoral 1 mm regions from DBT images.Different machine learning algorithms were used to construct intratumoral,peritumoral,and combined intratumoral and peritumoral models,respectively.Patient clinical data were analyzed by both univariate and multivariate logistic regression analy-ses to identify independent risk factors for the clinical imaging model.The performance of the models was evaluated using the receiver operating characteristic(ROC)curve.The radiomics features with the optimal diagnostic performance and the selected clinical imaging features were combined to construct a comprehensive clinical-radiomics model,and a nomogram was drawn.Results The combined intratumoral and peritumoral model was the optimal radiomics model.Maximum tumor diameter[odds ratio(OR)=1.486,P=0.014],suspicious malignant calcifications(OR=2.898,P=0.015),and axillary lymph node(ALN)metastasis(OR=3.615,P<0.001)were independent risk factors for LVI positive.Furthermore,the area under the curve(AUC)of the comprehensive clinical-radiomics model in the training set,test set and external valida-tion set was 0.889,0.916,and 0.862,respectively,which was higher than those of the combined intratumoral and peritumoral model(0.858,0.849,0.844)and the clinical imaging model(0.743,0.759,0.732).Conclusion The predictive nomogram,derived from both radiomics and clinical imaging features,is relatively accurate in identifying future LVI occurrence in breast cancer,demonstra-ting its potential as an assistive tool for clinicians to devise individualized treatment regimes.

Objective To screen immune-related long non-coding RNAs(LncRNAs)in the TCGA database pancreatic cancer dataset and construct a prognostic risk assessment model with immune-related LncRNAs to explore prognosis-related potential molecular mechanisms.Methods RNA-seq data of 171 pancreatic cancer samples and corresponding clinical information were obtained by The Cancer Genome Atlas(TCGA)database,and two classical immune-related gene datasets(GO0006955/IMMUNE RESPONSE and GO0002376/IMMUNE SYSTERM PROCESS)and gene annotation information were used to identify immune-related LncRNAs.The immune-related LncRNAs associated with pancreatic cancer prognosis were used for univariate and multivariate Cox analyses to establish a model for the assessment of pancreatic cancer prognostic risk based on immune-associated LncRNAs.This risk model was used for survival analysis,clinical correlation analysis,immune cell infiltration analysis,pathway enrichment analysis,and prognostic column line plot modeling.Results We screened 119 immune-related LncRNAs in pancreatic cancer,and five immune-related LncRNAs(AC064836.3,LINC00941,ZNF236-DT,TMEM161B-AS1 and AC068580.2)were identified for the development of pancreatic cancer prognostic risk assessment model.According to the prognostic risk assessment model,pancreatic cancer patients were divided into low-risk group(n=86)and high-risk group(n=85).Compared with the low-risk group,the high-risk group showed a significant negative enrichment trend for immune-related signaling pathways,the 5-year overall survival of pancreatic cancer patients was significantly increased in the low-risk group compared with the high-risk group.The expression of low-risk immune-related LncRNAs(AC064836.3,ZNF236-DT and TMEM161B-AS1)gradually decreased with increasing clinical stage of pancreatic cancer patients.Patient age(P=0.031,risk ratio and 95％CI:1.025/1.002-1.048)and prognostic risk score(P＜0.001,risk ratio and 95％ confidence interval 1.801/1.465-2.215)could be used as independent prognostic risk factors for overall survival in pancreatic cancer.In addition,the prognostic risk assessment model had better predictive efficiency(area under the curve=0.695)compared with the disease predictive ability of common clinical characteristics.Steroid biosynthesis,pentose phosphate pathway,intercellular linkage,cytoskeletal rearrangement and other pathways related to energy metabolism and invasive migration of pancreatic cancer cells were significantly activated in the high-risk group.Meanwhile,pancreatic cancer patients in the high-risk group had lower levels of naive B cells,plasma cells and neutrophils with anti-tumor activity,but their macrophage infiltration levels were significantly higher than those in the low-risk group.Conclusion The prognostic risk assessment model constructed based on five immune-related LncRNAs can effectively predict the survival status,clinical characteristics,molecular pathways,and immune cell infiltration differences of pancreatic cancer patients.Meanwhile,relying on this model,the prognosis of pancreatic cancer patients can be prospectively predicted,which enhances the usefulness of this risk prediction model.

Objective To investigate the correlation between cytokines and the side effects of estrogen deprivation associated with adjuvant endocrine therapy in female patients with early luminal breast cancer. Methods A retrospective analysis was performed on the data of 70 patients with early-stage breast cancer who underwent both the Endocrine Symptom Scale (FACT-ES) assessment and cytokine testing at the Breast Clinic of the Department of Medical Oncology, Cancer Hospital, Chinese Academy of Medical Sciences, between April 2023 and June 2023. Results Binary logistic regression analysis revealed that breast cancer patients experiencing hot flashes had significantly higher serum levels of IL-5 compared with those without hot flashes (3.17 pg/ml vs. 2.33 pg/ml, OR: 1.307-7.66, P=0.011), and the patients experiencing irritability had significantly lower serum levels of IL-10 (0.83 pg/ml vs. 1.37 pg/ml) and INF-γ (19.91 pg/ml vs. 35.93 pg/ml) compared with those without irritability（OR: 0.855-0.983, P=0.015）. Conclusion The elevated IL-5 may be associated with the occurrence of hot flashes, while lower levels of IL-10 and INF-γ may be linked to irritability in patients with early-stage Luminal breast cancer treated with adjuvant endocrine therapy.

Oral leukoplakia is a potentially malignant mucosal disease with a high incidence rate.Macrophages play a significant regulatory role in the malignant transformation of oral leukoplakia,yet there is a lack of research on the molecular mechanisms underlying this process.Recent studies have found that M2 polarization of macrophages has a significant impact on the malignant transformation of oral leukoplakia,and this process is regulated by a complex network involving immune cells,microorganisms,cytokines,and the extracellular matrix,etc.Therefore,this article reviews the biological functions,subtypes,and regulatory factors of macrophage polarization in oral leukoplakia.Building on the preliminary research foundation of our group on the relationship between oral intracellular colonizing bacteria and mucosal malignant tumors,it is proposed that oral intracellular colonizing bacteria,such as Porphyromonas gingivalis,may promote the malignant transformation of leukoplakia by inducing a macrophage M2 polarization that leads to an immunosuppressive microenvironment.This perspective explores potential intervention strategies from the angle of macrophage polarization,providing new research directions for the prevention and treatment of oral leukoplakia and oral cancer.

Objective:To improve the isolation and culture method of seasonal influenza virus in embryonated chicken eggs (ECEs), and evaluate their isolation efficiency.Methods:We randomly selected 80 positive samples of H1N1 (H1N1pdm09) and seasonal H3N2 (H3N2snl) influenza virus nucleic acid, and inoculated them into the amniotic and urinary sac cavities of 10-day-old (traditional method) and 14-day-old (improved method) ECEs respectively to adapt the virus to the ECEs (E1-E2). Both method were used to inoculate 10-day-old urinary sac amplification virus (E2-E3), and the final virus isolation positive rates of the two method were compared; using fluorescence quantitative PCR method to detect viral nucleic acids in the improved amniotic and urinary sac cultures, and evaluate the viral proliferation at different inoculation sites; we analyzed the correlation between virus content and isolation positivity rate in the original specimen based on the CT value of nucleic acid testing and the final virus isolation positivity rate using the improved method.Results:The improved method obtained 42 strains of H1N1pdm09 strain, with a positive rate of 52.5% ( χ2=38.571, P<0.01); obtained 54 strains of H3N2snl strain, with a positive rate of 67.5% ( χ2=40.921, P<0.01). Significant differences were observed in the isolation efficiency of H1N1pdm09 samples when the improved method was applied to different inoculation sites of chicken embryos ( χ2=30.476, P<0.01), and similar differences were noted for H3N2snl samples ( χ2=4.928, P=0.026). There was no significant difference in the isolation rate of different CT value intervals of the original samples ( χH1N1pdm092=10.226, χH3N2snl2=3.764, P>0.05). Conclusions:The improved method of inoculating 14-day old ECEs adapted the virus, and the final number of strains obtained was significantly higher than the traditional method of inoculating 10 day old ECEs, which can significantly improve the positive isolation rate of H1N1pdm09 and H3N2snl influenza virus in ECEs. The amniotic cavity is more sensitive to H1N1pdm09 and H3N2snl influenza viruses, which helps the virus adapt in ECEs. There was no significant difference in the sample isolation rate and total positive rate of virus isolation among different CT value ranges, and further verification is needed.

Objective To screen immune-related long non-coding RNAs(LncRNAs)in the TCGA database pancreatic cancer dataset and construct a prognostic risk assessment model with immune-related LncRNAs to explore prognosis-related potential molecular mechanisms.Methods RNA-seq data of 171 pancreatic cancer samples and corresponding clinical information were obtained by The Cancer Genome Atlas(TCGA)database,and two classical immune-related gene datasets(GO0006955/IMMUNE RESPONSE and GO0002376/IMMUNE SYSTERM PROCESS)and gene annotation information were used to identify immune-related LncRNAs.The immune-related LncRNAs associated with pancreatic cancer prognosis were used for univariate and multivariate Cox analyses to establish a model for the assessment of pancreatic cancer prognostic risk based on immune-associated LncRNAs.This risk model was used for survival analysis,clinical correlation analysis,immune cell infiltration analysis,pathway enrichment analysis,and prognostic column line plot modeling.Results We screened 119 immune-related LncRNAs in pancreatic cancer,and five immune-related LncRNAs(AC064836.3,LINC00941,ZNF236-DT,TMEM161B-AS1 and AC068580.2)were identified for the development of pancreatic cancer prognostic risk assessment model.According to the prognostic risk assessment model,pancreatic cancer patients were divided into low-risk group(n=86)and high-risk group(n=85).Compared with the low-risk group,the high-risk group showed a significant negative enrichment trend for immune-related signaling pathways,the 5-year overall survival of pancreatic cancer patients was significantly increased in the low-risk group compared with the high-risk group.The expression of low-risk immune-related LncRNAs(AC064836.3,ZNF236-DT and TMEM161B-AS1)gradually decreased with increasing clinical stage of pancreatic cancer patients.Patient age(P=0.031,risk ratio and 95％CI:1.025/1.002-1.048)and prognostic risk score(P＜0.001,risk ratio and 95％ confidence interval 1.801/1.465-2.215)could be used as independent prognostic risk factors for overall survival in pancreatic cancer.In addition,the prognostic risk assessment model had better predictive efficiency(area under the curve=0.695)compared with the disease predictive ability of common clinical characteristics.Steroid biosynthesis,pentose phosphate pathway,intercellular linkage,cytoskeletal rearrangement and other pathways related to energy metabolism and invasive migration of pancreatic cancer cells were significantly activated in the high-risk group.Meanwhile,pancreatic cancer patients in the high-risk group had lower levels of naive B cells,plasma cells and neutrophils with anti-tumor activity,but their macrophage infiltration levels were significantly higher than those in the low-risk group.Conclusion The prognostic risk assessment model constructed based on five immune-related LncRNAs can effectively predict the survival status,clinical characteristics,molecular pathways,and immune cell infiltration differences of pancreatic cancer patients.Meanwhile,relying on this model,the prognosis of pancreatic cancer patients can be prospectively predicted,which enhances the usefulness of this risk prediction model.

Objective To predict the lymphovascular invasion(LVI)status of breast cancer patients based on digital breast tomo-synthesis(DBT)intratumoral and peritumoral radiomics nomogram.Methods A total of 192 breast cancer patients from 2 institu-tions were retrospectively selected,in which institution 1 was used for train(n=113)and test(n=49),while institution 2 was used for external validation(n=30).Radiomics features were extracted and selected based on intratumoral and peritumoral 1 mm regions from DBT images.Different machine learning algorithms were used to construct intratumoral,peritumoral,and combined intratumoral and peritumoral models,respectively.Patient clinical data were analyzed by both univariate and multivariate logistic regression analy-ses to identify independent risk factors for the clinical imaging model.The performance of the models was evaluated using the receiver operating characteristic(ROC)curve.The radiomics features with the optimal diagnostic performance and the selected clinical imaging features were combined to construct a comprehensive clinical-radiomics model,and a nomogram was drawn.Results The combined intratumoral and peritumoral model was the optimal radiomics model.Maximum tumor diameter[odds ratio(OR)=1.486,P=0.014],suspicious malignant calcifications(OR=2.898,P=0.015),and axillary lymph node(ALN)metastasis(OR=3.615,P<0.001)were independent risk factors for LVI positive.Furthermore,the area under the curve(AUC)of the comprehensive clinical-radiomics model in the training set,test set and external valida-tion set was 0.889,0.916,and 0.862,respectively,which was higher than those of the combined intratumoral and peritumoral model(0.858,0.849,0.844)and the clinical imaging model(0.743,0.759,0.732).Conclusion The predictive nomogram,derived from both radiomics and clinical imaging features,is relatively accurate in identifying future LVI occurrence in breast cancer,demonstra-ting its potential as an assistive tool for clinicians to devise individualized treatment regimes.

A case of an adult patient who was admitted to the hospital with the primary complaint of dysuria was presented. CT imaging of the urinary tract revealed incomplete duplication of the bladder, accompanied by multiple diverticula in the left bladder. Urodynamic studies indicated low detrusor contraction of the bladder. Cystoscopy revealed that the left bladder was connected to the urethra, with both bladders linked by a narrow connection. Laparoscopic expansion of this junction alleviated dysuria; however, it did not significantly reduce bladder residual volume during the short-term follow-up.

Objective:To identify genetic etiology of ischemic stroke(IS)based on pleiotropy of obe-sity related genes.Methods:A discordant sib-pair study was designed based on the Fangshan family co-hort in Beijing.Body mass index(BMI)polygenic risk score(PRS)was first constructed under different P values.Using the polygenic transmission disequilibrium test(pTDT),we then compared the actual BMI genetic risk of siblings with IS to their expected risk,to analyze whether higher BMI was over-trans-mitted to siblings with IS.The single nucleotide polymorphism(SNP)that comprised the PRS over-trans-mitted with IS and that corresponded to the highest heritability of IS were identified as a pleiotropy SNPs set between BMI and IS.This set was then utilized as a candidate set to identify and verify risk SNPs as-so-ciated IS by transmission disequilibrium test.Finally,we identified independent genomic risk loci and mapped to genes,we then explored the biological function of the identified risk loci and genes by func-tional annotation and pathway enrichment.Results:A total of 541 participants were enrolled,with an average age of(58.4±8.1)years,including 326 discordant sib pairs of ischemic stroke.Compared with non-IS participants,IS participants with males,education level below junior high school,hypertension and hyperlipidemia accounted for a higher proportion(P＜0.05).For all the BMI PRS,we found that the actual genetic risk of BMI in siblings with IS was higher than their expectation,suggesting that genetic risk associated with high BMI was over-transmitted with IS.Compared with other SNP sets,the set(P＜5 × 10-4)corresponded to the best analytical statistics of pTDT and the highest heritability of IS and was identified as the pleiotropy SNP set between BMI and IS.Within this set,there were 45 SNPs having linkage and association with IS,which were located in 43 independent genomic risk loci and mapped to 40 genes.These genes were significantly enriched in the lipid metabolism pathway.The rs2232852 cor-rected by multiple tests was mapped to CYB5R1 and ADIPOR1,which were related to lipid metabolism and the ferroptosis pathway.Conclusion:Pleiotropy between BMI-related genes and IS was observed.Forty-five SNPs were found with linkage and association with IS in the pleiotropy gene set and mapped to 40 genes,which were functionally enriched in lipid metabolic pathways.The rs2232852 corrected by multiple tests during association analysis validation was mapped to CYB5R1 and ADIPOR1,which were related to lipid metabolism and the ferroptosis pathway,suggesting that lipid metabolism and ferroptosis played an important role in the development of IS.

Objective:To explore the spousal correlations of total cholesterol(TC),total triglyceride(TG),low-density lipoprotein cholesterol(LDL-C),and high-density lipoprotein cholesterol(HDL-C),and to investigate the reasons behind these spousal correlations.Methods:Participants and data were from the baseline survey of family-based cohort studies in Fangshan,Beijing and Tulou,Fujian.The ori-gin of spousal correlations were explored from perspectives of convergence,assortative mating,social ho-mogamy.Pearson's correlation and generalized linear models(GLM)were used to estimate the spousal correlation.Convergence was assessed by Pearson's correlation between the phenotypic differences be-tween couples and the duration of marriage,with GLM used for further validation.Pearson's correlation of genetic risk scores(GRS)and couple-specific Mendelian randomization(MR)were calculated to assess the genetic correlation and possible causal relationships between spouses.Two-independent-sample t-tests were used to compare GRS consistency across subgroups divided by education attainment,couple-specific MR and Q statistics used to test assortative mating in subgroups and intergroup differences.Results:In the study,342 couples(287 couples from Fangshan and 55 couples from Fujian)were included,with the average age of(64.91±8.76)years.Spousal correlations of TC,TG,HDL-C,and LDL-C showed statistically significant associations both before and after adjusting for covariates,with effect sizes of 0.229(95％CI:0.125-0.327),0.257(95％CI:0.155-0.354),0.179(95％CI:0.074-0.280),and 0.181(95％CI:0.076-0.282).For convergence,for each additional year of marriage,ΔTC increased by 0.016 mmol/L(95％CI:0.001-0.033 mmol/L),and ΔLDL-C increased by 0.017 mmol/L(95％CI:0.002-0.031 mmol/L).For assortative mating,GRS correlations and results of couple specific MR didn't show any statistical significance.For social homogamy,no differences in GRS or assortative mating were found between subgroups stratified by education attainment.Conclusion:The blood lipid in participants exhibit spousal phenotypic correlations,however,no effects of convergence,assortative mating or social homogamy were observed.More independent studies with larger sample sizes are warranted to further validate these findings in the future.