Objective:To study the effects of exosomes (EXO) released by adenoid cystic carcinoma SACC-83 cells on the expression of fibroblast activation protein (FAP) in normal human salivary gland stromal fibroblasts (hSGSFs).Methods:ACC exosomes were isolated from SACC-83 cell culture supernatant by using Total Exosome Isolation Reagent.The whole-mount EXO were characterized and assessed by transmission electron microscope and Western Blot.The exosomes were labeled with green fluorescent dye PKH67 and co-cultured with hSGSFs for 48h,followed by staining with Alexa Fluor 594 Phalloidin and DAPI.Mterwards,exsosomes uptake was observed under a laser scanning confocal microscope.After a 48-hour co-culture of SACC-83 exosomes with hSGSFs,the expression of FAP in SACC-83-EXO-treated hSGSFs was investigated by qRT-PCR and Western Blot.Results:The vesicles isolated from SACC-83 cell culture supernatant had the reported size range of 30-100 nm,expressed the exosomal marker CD63 and TSG101.Mter co-culture of hSGSFs with PKH67 labeled SACC-83 exosomes,exosomes were taken up by hSGSFs and FAP expression was elevated in hSGSFs.Conclusion:Exosomes derived from SACC-83 cells can be taken up by hSGSFs and can induce the expression of FAP in hSGSFs.These results suggest that exosomes derived from SACC-83 cells might induce the transformation of normal salivary gland strormal fibroblasts to cancer associated fibroblasts.

Objective To investigate the cognition of depression and anxiety and recognition of physical and mental illness,and analyze their correlation in hospitalized elderly patients with chronic diseases. Methods A cross-sectional study was performed.A total of 206 hospitalized elderly patients with chronic diseases from a hospital were investigated using mini mental state examination (MMSE),Hamilton depression rating scale (HAMD),self rating anxiety scale (SAS)and elderly patients with chronic diseases questionnaire. Results The total scores in cognition of depression and anxiety were (5.95 ±3.05)and (4.92 ±3.20).The correct recognition rate of chronic disease was (97 ±8)%,and the correct recognition rate of mental illness was (47 ±29 )%.The recognition of mental illness was positively correlated with the total cognition score of depression and three dimensions of thinking,spirit and mood (P <0.01 ).It was also positively correlated with the total scores of cognition in anxiety and two dimensions of emotion and other symptoms (P <0.01 ). However,there was no significant correlation between recognition of mental illness and physical dimension of depression (P >0.05).There was no significant correlation between recognition of mental illness and physical dimension of anxiety (P >0.05).Conclusions The cognitive level and cognition of depression and anxiety are low in elderly patients with chronic diseases.They tend to recognize the mental illness as chronic physical disease.Therefore,nurses should make depression and anxiety evaluation as routine assessment for the elderly patients with chronic diseases.Early identification of mental illness can avoid the delay of psychological intervention and acquire the best time of treatment.

Objective: To explore the serological and genotypic characteristics of a pedigree with B(A).06 subtype. Methods: Serological methods was used to identify the ABO phenotypes. Exons 6 and 7 of the ABO gene and flanking regions were subjected to direct sequencing and TA clonal sequencing in order to determine the genotype of individuals with inconsistent results for forward and reverse serological typing. Results: Among 12 individuals from 4 generations, 5 were identified with a AwB phenotype, along with a c. 803C>G mutation in exon 7 of the B allele, which was named as B(A).06. The B(A).06/O.01.01 phenotype may be easily missed due to its weak anti-A antibody in the serum upon initial serological test. Conclusion A B(A).06 subtype family was identified. The serological phenotype of individuals carrying the B(A).06 allele may be affected by the opposite DNA strand.

Objective:To explore the relative concentration changes of oxygenated hemoglobin (Oxy Hb) in the prefrontal cortex (PFC) and brain region activation during emotional face recognition tasks in women with perimenopausal depression.Methods:From February to April 2023, forty perimenopausal women were recruited, including 20 women with perimenopausal depression (experimental group) and 20 women with non-perimenopausal depression (control group). All participants were evaluated by the modified Kupperman score, 24-item Hamilton depression scale (HAMD-24), and patient health questionnaire (PHQ-9). Functional near-infrared spectroscopy (fNIRS) equipment was used to measure the relative concentration of Oxy-Hb in the PFC in two groups under the emotional face recognition task. Statistical analysis was performed by SPSS 26.0 software. Data were analyzed by a t-test, rank sum test, and Pearson correlation. Results:There were statistically significant differences in the results of the modified Kupperman score((23.20±3.66), (18.10±1.28)), HAMD-24((15.95±5.47), (3.35±1.84)), and PHQ-9(7.00(5.00, 10.75), 1.50(1.00, 3.00)) scales between the the experimental group and control group ( P<0.05). There was a positive correlation between the modified Kupperman score and the HAMD-24 score in the experimental group ( r=0.685, P=0.01). The reaction time of the experimental group in identifying negative and neutral emotional faces was statistically significant compared to the control group( t=4.01, 4.80, both P<0.05). Compared with identifying neutral emotions, PFC activation was stronger in the experimental group and control group when identifying negative emotions ( P<0.05). The PFC activation in the experimental group was stronger than that in the control group when identifying negative emotions ( P<0.05). There was no statistically significant difference in the activation level between the two groups when identifying neutral emotions ( P>0.05). Conclusion:Women with perimenopausal depression exhibit specificity in emotional processing, with increased PFC activation when identifying negative emotions, impaired emotional processing function of PFC, and dysfunction of aerobic metabolism.

Pan-immune inflammation value(PIV)is a comprehensive immune inflammatory bio-marker based on complete blood cell counts,which has been proven to predict treatment response and survival outcomes for different types of tumors.However,the predictive value of the PIV varies in dif-ferent strategies for tumor treatment.This paper aims to systematically review the latest progress of PIV in predicting survival outcomes and tumor prognosis for immunotherapy,radiotherapy,targeted therapy,endocrine therapy,surgical treatment and neoadjuvant therapy,and analyze its existing challenges and issues,as well as look forward to its future development direction and application prospects.

Objective To investigate the correlation between pre-treatment pan-immune inflam-mation value(PIV)and clinicopathological features in esophageal squamous cell carcinoma(ESCC)patients with postoperative adjuvant radiotherapy and evaluate its value in prognosis assessment com-bined with T stage.Methods A retrospective analysis was conducted on data of 85 ESCC patients with postoperative adjuvant radiotherapy in the Department of Radiation Oncology of the Affiliated Hospital of Yangzhou University from January 2019 to January 2023.The receiver operating character-istic(ROC)curve was drew to obtain the optimal cut-off value of PIV and other immune-inflammatory biomarkers.The area under the curve(AUC)and clinical applicability of PIV and other immune-in-flammatory biomarkers were compared based on the ROC curve and decision curve analysis(DC A).According to the optimal cut-off value,patients were divided into high PIV group and low PIV group,and the correlation between PIV level and clinicopathological features of ESCC was evaluated.Kaplan-Meier method was used for survival analysis,the Cox proportional hazards model was used for multivariate analysis,and a risk stratification model combining PIV and T stage was established by recursive partitioning analysis(RPA).Results The optimal cut-off value of pre-treatment PIV was determined as 187.22 based on the ROC curve.The AUC of PIV was 0.679,which was greater than 0.640,0.583,0.656 and 0.644 of the other four immune-inflammatory biomarkers such as the systemic immune-inflammation index(SII),platelet-to-lymphocyte ratio(PLR),monocyte-to-lymphocyte ratio(MLR),and neutrophil-to-lymphocyte ratio(NLR).The 85 patients were divided into low PIV group(＜187.22,n=48)and high PIV group(≥187.22,n=37).The level of PIV was significantly correlated with tumor diameter(P＜0.05).The 3-year overall survival(OS)(75.6％versus 30.6％,P＜0.001)and 3-year disease-free survival(DFS)(56.1％versus 21.0％,P＜0.001)were significantly higher in the low PIV group than the high PIV group.Tumor diameter,T stage and PIV were independent factors affecting OS in ESCC patients(P＜0.05),and T stage and PIV were independent factors affecting DFS in ESCC patients(P＜0.05).A new stag-ing system with three risk groups was established by the RPA stratification model based on T stage and PIV,which further improved the predictive value of prognosis compared with T stage or PIV alone.Conclusion Pre-treatment PIV is helpful in predicting the prognosis of ESCC patients with postoper-ative adjuvant radiotherapy,and the combination of PIV and T stage can improve the predictive value.

Pan-immune inflammation value(PIV)is a comprehensive immune inflammatory bio-marker based on complete blood cell counts,which has been proven to predict treatment response and survival outcomes for different types of tumors.However,the predictive value of the PIV varies in dif-ferent strategies for tumor treatment.This paper aims to systematically review the latest progress of PIV in predicting survival outcomes and tumor prognosis for immunotherapy,radiotherapy,targeted therapy,endocrine therapy,surgical treatment and neoadjuvant therapy,and analyze its existing challenges and issues,as well as look forward to its future development direction and application prospects.

Objective To investigate the correlation between pre-treatment pan-immune inflam-mation value(PIV)and clinicopathological features in esophageal squamous cell carcinoma(ESCC)patients with postoperative adjuvant radiotherapy and evaluate its value in prognosis assessment com-bined with T stage.Methods A retrospective analysis was conducted on data of 85 ESCC patients with postoperative adjuvant radiotherapy in the Department of Radiation Oncology of the Affiliated Hospital of Yangzhou University from January 2019 to January 2023.The receiver operating character-istic(ROC)curve was drew to obtain the optimal cut-off value of PIV and other immune-inflammatory biomarkers.The area under the curve(AUC)and clinical applicability of PIV and other immune-in-flammatory biomarkers were compared based on the ROC curve and decision curve analysis(DC A).According to the optimal cut-off value,patients were divided into high PIV group and low PIV group,and the correlation between PIV level and clinicopathological features of ESCC was evaluated.Kaplan-Meier method was used for survival analysis,the Cox proportional hazards model was used for multivariate analysis,and a risk stratification model combining PIV and T stage was established by recursive partitioning analysis(RPA).Results The optimal cut-off value of pre-treatment PIV was determined as 187.22 based on the ROC curve.The AUC of PIV was 0.679,which was greater than 0.640,0.583,0.656 and 0.644 of the other four immune-inflammatory biomarkers such as the systemic immune-inflammation index(SII),platelet-to-lymphocyte ratio(PLR),monocyte-to-lymphocyte ratio(MLR),and neutrophil-to-lymphocyte ratio(NLR).The 85 patients were divided into low PIV group(＜187.22,n=48)and high PIV group(≥187.22,n=37).The level of PIV was significantly correlated with tumor diameter(P＜0.05).The 3-year overall survival(OS)(75.6％versus 30.6％,P＜0.001)and 3-year disease-free survival(DFS)(56.1％versus 21.0％,P＜0.001)were significantly higher in the low PIV group than the high PIV group.Tumor diameter,T stage and PIV were independent factors affecting OS in ESCC patients(P＜0.05),and T stage and PIV were independent factors affecting DFS in ESCC patients(P＜0.05).A new stag-ing system with three risk groups was established by the RPA stratification model based on T stage and PIV,which further improved the predictive value of prognosis compared with T stage or PIV alone.Conclusion Pre-treatment PIV is helpful in predicting the prognosis of ESCC patients with postoper-ative adjuvant radiotherapy,and the combination of PIV and T stage can improve the predictive value.