Objective:To conduct a survey on the influence of personality trait on depres-sive symptom and obesity in patients before bariatric and metabolic surgery.Methods:The retros-pective cross-sectional investigation study was conducted. Patients who underwent bariatric and metabolic surgery in The Third Xiangya Hospital of Central South University and The First Affiliated Hospital of Ji′nan University from January 1 to June 1,2024 were recruited. The survey was conducted in electronic format using the general information survey questionnaire, the patient health question-naire-9 (PHQ-9), and the Chinese big five personality inventory brief version (CBF-PI-B). Observa-tion indicators: (1) results of the questionnaire; (2) general data of patient; (3) personality trait scores for patient with different subtypes of obesity; (4) depression symptom scores for patient with different subtypes of obesity; (5) correlation analysis for patient personality trait, depressive symptom and body mass index (BMI). Comparison of measurement data with normal distribution between groups was conducted using the independent t test, and one-way analysis of variance was used for comparison among multiple groups. LSD test was used for pairwise comparison. Comparison of measurement data with skewed distribution among multiple groups was conducted using the Kruskal-Wallis H test, and Dunn Bonferroni test was used for pairwise comparison. The Spearman correlation analysis and Pearson correlation analysis were used for correlation analysis, and the mediation effect analysis was conducted using the Process 4.0 model and the Bootstrap test. Results:(1)Results of the questionnaire. A total of 146 questionnaires were distributed and collected, including 83 questionnaires from The Third Xiangya Hospital of Central South University and 63 questionnaires from The First Affiliated Hospital of Ji′nan University. Of 146 questionnaires, 137 questionnaires were valid, yielding an effective response rate of 93.836%(137/146). (2)General data of patient. Of the 137 patients who completed valid questionnaires, 52 were male with BMI of (41±5)kg/m 2, 85 were female with BMI of (38±6)kg/m 2, showing a significant difference between them ( t=2.586, P<0.05). There were 40 patients aged ≤25 years, with BMI of (42±5)kg/m 2, 28 patients aged 26-30 years, with BMI of (39±5)kg/m 2, 49 patients aged 31-40 years, with BMI of (38±6)kg/m 2, 14 patients aged 41-50 years, with BMI of (38±7)kg/m 2, 6 patients aged >50 years, with BMI of (37±3)kg/m 2. There were significant differences in BMI of patients of different age groups ( F=2.697, P<0.05). (3)Persona-lity trait scores for patient with different subtypes of obesity. Of the 137 patients who completed valid questionnaires, there were 15 patients of mild obesity, with personality trait neuroticism score of 19.0(14.0,24.0), personality trait strictness score of 32.5±5.2, personality trait extroversion score of 30.0(24.0,40.0), 36 patients of moderate obesity, with personality trait neuro-ticism score of 26.5(22.3,28.8), personality trait strictness score of 32.6±5.9, personality trait extro-version score of 34.0(26.3,39.0), 81 patients of severe obesity, with personality trait neuroticism score of 35.0(29.5,41.0), personality trait strictness score of 26.8±7.4, personality trait extroversion score of 28.0(20.5,35.0), 5 patients of extreme obesity, with personality trait neuroticism score of 28.0(26.5,44.0), personality trait strictness score of 19.6±3.4, personality trait extroversion score of 22.0(18.5,25.0). There were significant differences in personality trait neuroticism, strictness and extroversion among patients of different subtypes of obesity ( H=50.316, F=10.774, H=14.446, P<0.05). (4)Depression symptom scores for patient with different subtypes of obesity. Of the 137 pati-ents who completed valid questionnaires, the depressive symptom score were 4.0(2.0,9.0) for 15 pati-ents of mild obesity, 5.0(3.0,7.0) for 36 patients of moderate obesity, 13.0(8.5,17.0) for 81 patients of severe obesity, and 18.0(9.5,22.0) for 5 patients of extreme obesity, respectively, showing a significant difference among them ( H=50.129, P<0.05). (5) Correlation analysis for patient personality trait, depressive symptom and BMI. Results of Spearman correlation analysis showed that personality trait neuroticism were positively correlated with depressive symptoms and BMI ( r=0.780, 0.557, P<0.05), personality trait strictness was negatively correlated with depressive symptoms ( r=-0.523, P<0.05), personality trait extroversion were negatively correlated with depressive symptoms and BMI ( r=-0.448, -0.323, P<0.05), and depressive symptoms was positively correlated with BMI ( r=0.568, P<0.05). Results of Pearson correlation analysis showed that personality trait strictness was negatively correlated with BMI ( r=-0.489, P<0.05). Conclusion:Preoperative personality trait of patients undergoing bariatric and metabolic surgery can influence their depressive symptom and BMI.

Objective:To explore the relapse-related genes and their clinicopathological connections of diffuse large B cell lymphoma (DLBCL).Methods:Targeted panel sequencing was conducted on 32 eligible DLBCL samples; the patients were diagnosed, treated, and went into complete remission at the First Affiliated Hospital of Nanjing Medical University from January 2015 to December 2019, including 14 cases with recurrence (relapsed group) and 18 cases with long-term complete remission of over five years (remission group). Clinical and pathological data were further reviewed. Fisher′s exact test was employed to compare the differences in clinicopathological characteristics and mutation patterns between the two groups.Results:Among the 32 patients, there were 18 males and 14 females, with a male to female ratio of 1.3∶1.0 and a median age of 53 (45.5, 67.0) years. In the relapsed group, PIM1 (11/14), KMT2D (7/14), PRDM1 (6/14), MYD88 (6/14), DTX1 (6/14) emerged as the most frequently mutated genes. In the remission group, while recurrent PIM1, KMT2D and MYD88 mutations were also observed, the TP53 gene exhibited the highest mutation frequency (6/18). Compared to the remission group, relapsed group showed elevated mutation frequencies of PIM1 ( P=0.013) and FAT4 ( P=0.010), alongside a reduced incidence of TP53 mutations. In all 32 patients, DLBCL with CD79B, CCND3, DTX1, KMT2D and PRDM1 mutations demonstrated a propensity towards advanced clinicopathologic stage. Conclusions:Relapsed DLBCL has distinctive clinicopathological and genetic features. PIM1 and FAT4 may be served as potential biomarkers for screening relapsed DLBCL-NOS and as targets for novel therapeutic strategies.

Objective:To explore the clinical and pathological features of EBV-positive diffuse large B cell lymphoma (EBV +DLBCL) and to analyze the prognostic significance of CD30 expression in this entity. Methods:A retrospective analysis was conducted from 34 cases of EBV +DLBCL and 198 cases of EBV -DLBCL diagnosed and treated at the First Affiliated Hospital of Nanjing Medical University, from January 2017 to June 2023. Based on CD30 expression, 34 patients with EBV +DLBCL were categorized into CD30-positive and CD30-negative groups. Fisher exact test and Kaplan-Meier survival curves were employed to analyze the relationship between CD30 expression and clinicopathological parameters as well as its prognostic implications. Chi-square tests were used to compare the clinicopathological features between EBV +DLBCL and EBV -DLBCL. Results:There were 19 males and 15 females with a median age of 69.5 (15-83) years in the EBV +DLBCL group. Compared with EBV -DLBCL, EBV +DLBCL was more likely to present with clinical features such as B symptoms ( χ2=23.818, P<0.001), Ann Arbor stage Ⅲ-Ⅳ ( χ2=8.540, P=0.003), ECOG (Eastern Cooperative Oncology Group Performance Status) score 2-4 ( χ2=6.722, P=0.010), IPI score 3-5 ( χ2=9.953, P=0.002), and involvement of more than one extranodal site ( χ2=6.825, P=0.009). Additionally, EBV +DLBCL exhibited higher frequencies of elevated LDH ( χ2=4.307, P=0.038), CRP ( χ2=5.596, P=0.018), and β2-MG ( χ2=7.008, P=0.008) levels. Histopathologically, EBV +DLBCL was more commonly of the non-GCB subtype ( χ2=12.421, P<0.001), with higher frequencies of CD30-positive ( χ2=62.706, P<0.001),CD10-negative ( χ2=8.687, P=0.003),bcl-6-negative ( χ2=11.123, P<0.001), and bcl-2-negative ( χ2=22.779, P=0.003) expression. Using 20% as the positive threshold for CD30, the CD30-positive group had a higher proliferation index ( P=0.045). No significant differences were observed in overall survival between the two groups. Conclusions:EBV +DLBCL is more prevalent in the elderly and often exhibits aggressive clinical features. The expression of CD30 is not associated with the overall prognosis of EBV +DLBCL.

Vast majority of human RNA are non-coding RNA(ncRNA),which can regulate physiological activities and affects functions on cells.Although each part of them is obscure,they are involved in different levels of gene regulation,from epigene-tic gene silencing to post transcriptional regulation.Metabolic reprogramming of tumor-associated macrophages(TAMs)can promote tumor progression and is closely related to activation phenotypes of anti-tumor(M1)or pro-tumor(M2).A lot of ncRNAs are involved in metabolic reprogramming of TAMs,reshaping tumor microenvironment and playing a key role in tumor progression.Improving understanding of effect on ncRNA regulating metabolic reprogramming of TAMs may provide new methods for developing effective clinical treatments.

Objective:To conduct a survey on the influence of personality trait on depres-sive symptom and obesity in patients before bariatric and metabolic surgery.Methods:The retros-pective cross-sectional investigation study was conducted. Patients who underwent bariatric and metabolic surgery in The Third Xiangya Hospital of Central South University and The First Affiliated Hospital of Ji′nan University from January 1 to June 1,2024 were recruited. The survey was conducted in electronic format using the general information survey questionnaire, the patient health question-naire-9 (PHQ-9), and the Chinese big five personality inventory brief version (CBF-PI-B). Observa-tion indicators: (1) results of the questionnaire; (2) general data of patient; (3) personality trait scores for patient with different subtypes of obesity; (4) depression symptom scores for patient with different subtypes of obesity; (5) correlation analysis for patient personality trait, depressive symptom and body mass index (BMI). Comparison of measurement data with normal distribution between groups was conducted using the independent t test, and one-way analysis of variance was used for comparison among multiple groups. LSD test was used for pairwise comparison. Comparison of measurement data with skewed distribution among multiple groups was conducted using the Kruskal-Wallis H test, and Dunn Bonferroni test was used for pairwise comparison. The Spearman correlation analysis and Pearson correlation analysis were used for correlation analysis, and the mediation effect analysis was conducted using the Process 4.0 model and the Bootstrap test. Results:(1)Results of the questionnaire. A total of 146 questionnaires were distributed and collected, including 83 questionnaires from The Third Xiangya Hospital of Central South University and 63 questionnaires from The First Affiliated Hospital of Ji′nan University. Of 146 questionnaires, 137 questionnaires were valid, yielding an effective response rate of 93.836%(137/146). (2)General data of patient. Of the 137 patients who completed valid questionnaires, 52 were male with BMI of (41±5)kg/m 2, 85 were female with BMI of (38±6)kg/m 2, showing a significant difference between them ( t=2.586, P<0.05). There were 40 patients aged ≤25 years, with BMI of (42±5)kg/m 2, 28 patients aged 26-30 years, with BMI of (39±5)kg/m 2, 49 patients aged 31-40 years, with BMI of (38±6)kg/m 2, 14 patients aged 41-50 years, with BMI of (38±7)kg/m 2, 6 patients aged >50 years, with BMI of (37±3)kg/m 2. There were significant differences in BMI of patients of different age groups ( F=2.697, P<0.05). (3)Persona-lity trait scores for patient with different subtypes of obesity. Of the 137 patients who completed valid questionnaires, there were 15 patients of mild obesity, with personality trait neuroticism score of 19.0(14.0,24.0), personality trait strictness score of 32.5±5.2, personality trait extroversion score of 30.0(24.0,40.0), 36 patients of moderate obesity, with personality trait neuro-ticism score of 26.5(22.3,28.8), personality trait strictness score of 32.6±5.9, personality trait extro-version score of 34.0(26.3,39.0), 81 patients of severe obesity, with personality trait neuroticism score of 35.0(29.5,41.0), personality trait strictness score of 26.8±7.4, personality trait extroversion score of 28.0(20.5,35.0), 5 patients of extreme obesity, with personality trait neuroticism score of 28.0(26.5,44.0), personality trait strictness score of 19.6±3.4, personality trait extroversion score of 22.0(18.5,25.0). There were significant differences in personality trait neuroticism, strictness and extroversion among patients of different subtypes of obesity ( H=50.316, F=10.774, H=14.446, P<0.05). (4)Depression symptom scores for patient with different subtypes of obesity. Of the 137 pati-ents who completed valid questionnaires, the depressive symptom score were 4.0(2.0,9.0) for 15 pati-ents of mild obesity, 5.0(3.0,7.0) for 36 patients of moderate obesity, 13.0(8.5,17.0) for 81 patients of severe obesity, and 18.0(9.5,22.0) for 5 patients of extreme obesity, respectively, showing a significant difference among them ( H=50.129, P<0.05). (5) Correlation analysis for patient personality trait, depressive symptom and BMI. Results of Spearman correlation analysis showed that personality trait neuroticism were positively correlated with depressive symptoms and BMI ( r=0.780, 0.557, P<0.05), personality trait strictness was negatively correlated with depressive symptoms ( r=-0.523, P<0.05), personality trait extroversion were negatively correlated with depressive symptoms and BMI ( r=-0.448, -0.323, P<0.05), and depressive symptoms was positively correlated with BMI ( r=0.568, P<0.05). Results of Pearson correlation analysis showed that personality trait strictness was negatively correlated with BMI ( r=-0.489, P<0.05). Conclusion:Preoperative personality trait of patients undergoing bariatric and metabolic surgery can influence their depressive symptom and BMI.

In recent years,artificial intelligence(AI)technologies,particularly those represented by deep learn-ing,have demonstrated tremendous potential in the advancement of medical applications.This article reviews recent re-search progress in AI applications for the diagnosis and treatment of triple-negative breast cancer,aiming to inform the development of clinically relevant AI algorithms that align with real-world practice scenarios.The ultimate objectives in-clude enhancing diagnostic accuracy through efficient computational approaches,reducing manual labor burdens,im-proving patient prognosis,and facilitating the identification of therapeutic targets in oncology through AI-driven predic-tive modeling.

Long non-coding RNAs(lncRNAs)regulate gene expression at the transcriptional,post-transcription-al,or epigenetic levels,and play crucial roles in tumor cell proliferation,invasion,apoptosis,and metabolism.With ongoing research,an increasing number of human microproteins encoded by lncRNAs have been discovered,although their complete functional characterization remains to be explored.This article reviews the research progress on the func-tions and partial mechanisms of the small integral membrane protein(SMIM)family encoded by lncRNAs in tumor ini-tiation and progression.

Objective:To explore the relapse-related genes and their clinicopathological connections of diffuse large B cell lymphoma (DLBCL).Methods:Targeted panel sequencing was conducted on 32 eligible DLBCL samples; the patients were diagnosed, treated, and went into complete remission at the First Affiliated Hospital of Nanjing Medical University from January 2015 to December 2019, including 14 cases with recurrence (relapsed group) and 18 cases with long-term complete remission of over five years (remission group). Clinical and pathological data were further reviewed. Fisher′s exact test was employed to compare the differences in clinicopathological characteristics and mutation patterns between the two groups.Results:Among the 32 patients, there were 18 males and 14 females, with a male to female ratio of 1.3∶1.0 and a median age of 53 (45.5, 67.0) years. In the relapsed group, PIM1 (11/14), KMT2D (7/14), PRDM1 (6/14), MYD88 (6/14), DTX1 (6/14) emerged as the most frequently mutated genes. In the remission group, while recurrent PIM1, KMT2D and MYD88 mutations were also observed, the TP53 gene exhibited the highest mutation frequency (6/18). Compared to the remission group, relapsed group showed elevated mutation frequencies of PIM1 ( P=0.013) and FAT4 ( P=0.010), alongside a reduced incidence of TP53 mutations. In all 32 patients, DLBCL with CD79B, CCND3, DTX1, KMT2D and PRDM1 mutations demonstrated a propensity towards advanced clinicopathologic stage. Conclusions:Relapsed DLBCL has distinctive clinicopathological and genetic features. PIM1 and FAT4 may be served as potential biomarkers for screening relapsed DLBCL-NOS and as targets for novel therapeutic strategies.

Objective:To explore the clinical and pathological features of EBV-positive diffuse large B cell lymphoma (EBV +DLBCL) and to analyze the prognostic significance of CD30 expression in this entity. Methods:A retrospective analysis was conducted from 34 cases of EBV +DLBCL and 198 cases of EBV -DLBCL diagnosed and treated at the First Affiliated Hospital of Nanjing Medical University, from January 2017 to June 2023. Based on CD30 expression, 34 patients with EBV +DLBCL were categorized into CD30-positive and CD30-negative groups. Fisher exact test and Kaplan-Meier survival curves were employed to analyze the relationship between CD30 expression and clinicopathological parameters as well as its prognostic implications. Chi-square tests were used to compare the clinicopathological features between EBV +DLBCL and EBV -DLBCL. Results:There were 19 males and 15 females with a median age of 69.5 (15-83) years in the EBV +DLBCL group. Compared with EBV -DLBCL, EBV +DLBCL was more likely to present with clinical features such as B symptoms ( χ2=23.818, P<0.001), Ann Arbor stage Ⅲ-Ⅳ ( χ2=8.540, P=0.003), ECOG (Eastern Cooperative Oncology Group Performance Status) score 2-4 ( χ2=6.722, P=0.010), IPI score 3-5 ( χ2=9.953, P=0.002), and involvement of more than one extranodal site ( χ2=6.825, P=0.009). Additionally, EBV +DLBCL exhibited higher frequencies of elevated LDH ( χ2=4.307, P=0.038), CRP ( χ2=5.596, P=0.018), and β2-MG ( χ2=7.008, P=0.008) levels. Histopathologically, EBV +DLBCL was more commonly of the non-GCB subtype ( χ2=12.421, P<0.001), with higher frequencies of CD30-positive ( χ2=62.706, P<0.001),CD10-negative ( χ2=8.687, P=0.003),bcl-6-negative ( χ2=11.123, P<0.001), and bcl-2-negative ( χ2=22.779, P=0.003) expression. Using 20% as the positive threshold for CD30, the CD30-positive group had a higher proliferation index ( P=0.045). No significant differences were observed in overall survival between the two groups. Conclusions:EBV +DLBCL is more prevalent in the elderly and often exhibits aggressive clinical features. The expression of CD30 is not associated with the overall prognosis of EBV +DLBCL.

In recent years,artificial intelligence(AI)technologies,particularly those represented by deep learn-ing,have demonstrated tremendous potential in the advancement of medical applications.This article reviews recent re-search progress in AI applications for the diagnosis and treatment of triple-negative breast cancer,aiming to inform the development of clinically relevant AI algorithms that align with real-world practice scenarios.The ultimate objectives in-clude enhancing diagnostic accuracy through efficient computational approaches,reducing manual labor burdens,im-proving patient prognosis,and facilitating the identification of therapeutic targets in oncology through AI-driven predic-tive modeling.