BACKGROUND:U937 cells can be used as a cell model for studying the biological characteristics,signaling pathways,and therapeutic targets of acute myeloid leukemia.Although it has been reported that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia,its biological function in U937 cells remains unclear,and its mechanism of action in the occurrence and development of acute myeloid leukemia needs to be further clarified. OBJECTIVE:To investigate the expression level of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia and its effect on the proliferation and apoptosis of U937 cells. METHODS:RNA-sequencing was used to analyze the bone marrow monocyte samples from acute myeloid leukemia patients,and the differentially expressed gene long non-coding RNA KIAA0125 was screened.The expression of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia was detected by qRT-PCR.The relationship between long non-coding RNA KIAA0125 mRNA expression and prognosis in bone marrow cells of 173 acute myeloid leukemia patients and 70 healthy people was statistically analyzed by GEPIA database.Subsequently,recombinant lentivirus technology and CRISPR/Cas9-SAM technology were used to construct U937 cell lines with knockdown/overexpression of long non-coding RNA KIAA0125.qRT-PCR was used to detect the knockdown/overexpression efficiency of long non-coding RNA KIAA0125.Next,CCK-8 assay,flow cytometry,and western blot assay were used to detect the effects of knockdown/overexpression of long non-coding RNA KIAA0125 on the proliferation and apoptosis of U937 cells.Finally,western blot assay was used to detect the effect of knockdown/overexpressed long non-coding RNA KIAA0125 on Wnt/β-catenin signaling pathway-related proteins. RESULTS AND CONCLUSION:(1)The results of qRT-PCR showed that long non-coding RNA KIAA0125 was highly expressed in peripheral blood of acute myeloid leukemia patients.The results of GEPIA database showed that long non-coding RNA KIAA0125 was highly expressed in bone marrow cells of acute myeloid leukemia patients,and the high expression group had worse overall survival.(2)The knockdown efficiency of long non-coding RNA KIAA0125 in knockdown group was 70%,and the U937 cells that stably down-regulated long non-coding RNA KIAA0125 expression were successfully constructed.The expression of long non-coding RNA KIAA0125 in overexpression group was four times that of vector group,and stable U937 cells were successfully constructed.(3)Knockdown of long non-coding RNA KIAA0125 inhibited the proliferation of U937 cells and promoted their apoptosis.Overexpression of long non-coding RNA KIAA0125 promoted the proliferation of U937 cells but had no significant effect on the apoptosis of U937 cells.(4)Knockdown of long non-coding RNA KIAA0125 inhibited the activity of Wnt/β-catenin signaling pathway,while overexpression of long non-coding RNA KIAA0125 activated Wnt/β-catenin signaling pathway.These results confirm that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia peripheral blood.Long non-coding RNA KIAA0125 may affect the proliferation and apoptosis of U937 cells by regulating the Wnt/β-catenin signaling pathway,and may be a potential prognostic marker for acute myeloid leukemia.

Objective: To explore the impact of sleep quality, experience of childhood maltreatment, and their interaction on depressive symptoms among middle school students, so as to provide the reference for early intervention of depressive symptoms among middle school students. Methods: From September to December 2023, a questionnaire survey was conducted among 1 231 students from two secondary schools in Harbin, Heilongjiang Province by a convenient sampling method. The survey included general demographic information, Childhood Trauma Questionnaire Short Form, Pittsburgh Sleep Quality Index and Short Version of Center for Epidemiological Studies Depression Scale. The Chi square test was used to analyze the differences in depressive symptom, sleep quality and childhood maltreatment among students with different demographic characteristics. Correlation analysis was conducted using Logistic regression, and interaction analysis was performed by both additive and multiplicative interaction models. Results: The detection rate of depressive symptoms among middle school students was 22.7%, and the rate for high school students (35.2%) was significantly higher than that for middle school students (17.0%) ( χ 2=50.35, P <0.01). The detection rates of depressive symptoms among middle school students with a history of childhood maltreatment and poor sleep quality were 45.8% and 44.0%, respectively. Multivariate Logistic regression analysis showed that compared to students without a history of childhood maltreatment, students with a history of childhood maltreatment had a higher risk of depressive symptoms ( OR =4.49，95% CI =3.31~ 6.09 , P <0.01);students with poor sleep quality had a higher risk of depressive symptoms than students with good sleep quality ( OR = 5.99，95% CI =4.37~8.22, P <0.01).The interaction results showed that the presence of childhood maltreatment and poor sleep quality had an additive interaction on the occurrence of depression in middle school students. Compared with students without childhood maltreatment and having good sleep quality, students with childhood maltreatment and poor sleep quality had a 22.49 times higher risk of developing depression ( OR =22.49，95% CI =14.22~35.59, P <0.01). Conclusion Depressive symptoms among middle school students are associated with childhood maltreatment and poor sleep quality, and there is an additive interaction between childhood maltreatment and poor sleep quality on the impact of depressive symptoms.

Diabetic nephropathy(DN), a prevalent microvascular complication of diabetes, has emerged as a leading cause of end-stage renal disease worldwide. Recent studies on the dual-specific phosphatase (DUSP) family have revealed a significant reduction in DUSP expression levels in renal disease, suggesting that enhancing its expression may mitigate or alleviate the symptoms associated with renal disease. The primary function of DUSP is to mediate the dephosphorylation of mitogen-activated protein kinase (MAPK), which effectively inhibits the activation of the MAPK pathway, thus playing a crucial regulatory role in the onset and progression of DN. This article aims to investigate the correlation between DN and DUSP and to summarize the current research advancements concerning DUSP in the context of DN, providing new insights and essential theoretical foundations for its diagnosis and treatment.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.