In recent years, sleep problems among nurses have become a prominent social focus, and sleep disorders are widespread among nurses. ICU nurses are more prone to problems such as decreased sleep quality, shorter sleep duration, and daytime sleepiness than nurses in other departments due to special and complex work environments. Sleep disorders seriously affect the physical and mental health of ICU nurses and the quality of nursing care. This paper reviews the influencing factors, interventions, and assessment tools for sleep disorders among ICU nurses in order to inform the development of effective interventions.

Objective To design a Five-Elements Music Software based on Traditional Chinese Medicine's(TCM)theory of five elements music therapy and music emotion classification.The software is intended to provide appropriate music selections tailored to the negative emotional states of cancer patients and evaluate its effectiveness in psychological rehabilitation.Methods ①Music screening and classification:Qualitative analysis was used by six experts in TCM,psychology,nursing,and musicology to screen five elements music and classify corresponding emotional categories.②Software design and development:Based on screening and classification of music materials,design and develop a"Five Elements Music Software Based on Emotion Classification".③Software application evaluation:Recruit 50 cancer patients from the"Beijing Anti Cancer Paradise"as participants to have a trial listening experience with music software,and fill out a satisfaction questionnaire to evaluate its application effect.Results This study established a music database containing 150 pieces of five-elements musical tunes and completed the classification of emotional categories.Among the included subjects,80%of the recruited objects were satisfied with the experience of the five elements music software,of which the application experience of female patients was significantly better than that of male patients,and breast cancer patients were better than other cancer patients,with a statistically significant difference(P<0.05).The five elements music Software in clinic showed comparing with other two groups after four weeks,there was a significant difference for HAMD when comparing five elements music software group and the other two groups(P<0.05).Conclusion The five-element music software designed based on emotion classification effectively meets the psychological rehabilitation needs of cancer patients.It provides appropriate music selections and convenient listening method to regulate cancer-related negative emotions,extending psychological rehabilitation from the hospital to the home.

Objective To design a Five-Elements Music Software based on Traditional Chinese Medicine's(TCM)theory of five elements music therapy and music emotion classification.The software is intended to provide appropriate music selections tailored to the negative emotional states of cancer patients and evaluate its effectiveness in psychological rehabilitation.Methods ①Music screening and classification:Qualitative analysis was used by six experts in TCM,psychology,nursing,and musicology to screen five elements music and classify corresponding emotional categories.②Software design and development:Based on screening and classification of music materials,design and develop a"Five Elements Music Software Based on Emotion Classification".③Software application evaluation:Recruit 50 cancer patients from the"Beijing Anti Cancer Paradise"as participants to have a trial listening experience with music software,and fill out a satisfaction questionnaire to evaluate its application effect.Results This study established a music database containing 150 pieces of five-elements musical tunes and completed the classification of emotional categories.Among the included subjects,80%of the recruited objects were satisfied with the experience of the five elements music software,of which the application experience of female patients was significantly better than that of male patients,and breast cancer patients were better than other cancer patients,with a statistically significant difference(P<0.05).The five elements music Software in clinic showed comparing with other two groups after four weeks,there was a significant difference for HAMD when comparing five elements music software group and the other two groups(P<0.05).Conclusion The five-element music software designed based on emotion classification effectively meets the psychological rehabilitation needs of cancer patients.It provides appropriate music selections and convenient listening method to regulate cancer-related negative emotions,extending psychological rehabilitation from the hospital to the home.

Intravascular large B cell lymphoma (IVLBCL) is a rare, aggressive subtype of diffuse large B cell lymphoma, with nasal turbinate involvement being uncommon. We report a 51-year-old woman with a 1-month history of fever of unknown origin. Laboratory findings showed cytopenia, hypertriglyceridemia, elevated ferritin, increased soluble CD25, and bone marrow hemophagocytosis. No infectious cause was identified. PET-CT revealed abnormal 18F-fluorodeoxyglucose (FDG) uptake in the nasal turbinates. Turbinate biopsy revealed tumor cells localized predominantly within vascular lumens, positive for CD20, BCL6, PAX5, and MUM1, with a Ki-67 index >60%, confirming a diagnosis of IVLBCL with hemophagocytic lymphohistiocytosis (HLH). The patient received one cycle of the DEP regimen (liposomal doxorubicin, etoposide, and methylprednisolone) for HLH, followed by five cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and consolidation with auto-HSCT, achieving sustained complete remission. IVLBCL outcomes are heterogeneous; early diagnosis and prompt treatment improve survival, and R-CHOP plus auto-HSCT may be an effective strategy.

In recent years, sleep problems among nurses have become a prominent social focus, and sleep disorders are widespread among nurses. ICU nurses are more prone to problems such as decreased sleep quality, shorter sleep duration, and daytime sleepiness than nurses in other departments due to special and complex work environments. Sleep disorders seriously affect the physical and mental health of ICU nurses and the quality of nursing care. This paper reviews the influencing factors, interventions, and assessment tools for sleep disorders among ICU nurses in order to inform the development of effective interventions.

Intravascular large B cell lymphoma (IVLBCL) is a rare, aggressive subtype of diffuse large B cell lymphoma, with nasal turbinate involvement being uncommon. We report a 51-year-old woman with a 1-month history of fever of unknown origin. Laboratory findings showed cytopenia, hypertriglyceridemia, elevated ferritin, increased soluble CD25, and bone marrow hemophagocytosis. No infectious cause was identified. PET-CT revealed abnormal 18F-fluorodeoxyglucose (FDG) uptake in the nasal turbinates. Turbinate biopsy revealed tumor cells localized predominantly within vascular lumens, positive for CD20, BCL6, PAX5, and MUM1, with a Ki-67 index >60%, confirming a diagnosis of IVLBCL with hemophagocytic lymphohistiocytosis (HLH). The patient received one cycle of the DEP regimen (liposomal doxorubicin, etoposide, and methylprednisolone) for HLH, followed by five cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and consolidation with auto-HSCT, achieving sustained complete remission. IVLBCL outcomes are heterogeneous; early diagnosis and prompt treatment improve survival, and R-CHOP plus auto-HSCT may be an effective strategy.

Objective To construct a nonparametric proportional hazards (PH) model for mixed informative interval-censored failure time data for predicting the risks in heart transplantation surgeries. Methods Based on the complexity of mixed informative interval-censored failure time data, we considered the interdependent relationship between failure time process and observation time process, constructed a nonparametric proportional hazards (PH) model to describe the nonlinear relationship between the risk factors and heart transplant surgery risks and proposed a two-step sieve estimation maximum likelihood algorithm. An estimation equation was established to estimate frailty variables using the observation process model. I-spline and B-spline were used to approximate the unknown baseline hazard function and nonparametric function, respectively, to obtain the working likelihood function in the sieve space. The partial derivative of the model parameters was used to obtain the scoring equation. The maximum likelihood estimation of the parameters was obtained by solving the scoring equation, and a function curve of the impact of risk factors on the risk of heart transplantation surgery was drawn. Results Simulation experiment suggested that the estimated values obtained by the proposed method were consistent and asymptotically effective under various settings with good fitting effects. Analysis of heart transplant surgery data showed that the donor's age had a positive linear relationship with the surgical risk. The impact of the recipient's age at disease onset increased at first and then stabilized, but increased against at an older age. The donor-recipient age difference had a positive linear relationship with the surgical risk of heart transplantation. Conclusion The nonparametric PH model established in this study can be used for predicting the risks in heart transplantation surgery and exploring the functional relationship between the surgery risks and the risk factors.

Objective To construct a nonparametric proportional hazards (PH) model for mixed informative interval-censored failure time data for predicting the risks in heart transplantation surgeries. Methods Based on the complexity of mixed informative interval-censored failure time data, we considered the interdependent relationship between failure time process and observation time process, constructed a nonparametric proportional hazards (PH) model to describe the nonlinear relationship between the risk factors and heart transplant surgery risks and proposed a two-step sieve estimation maximum likelihood algorithm. An estimation equation was established to estimate frailty variables using the observation process model. I-spline and B-spline were used to approximate the unknown baseline hazard function and nonparametric function, respectively, to obtain the working likelihood function in the sieve space. The partial derivative of the model parameters was used to obtain the scoring equation. The maximum likelihood estimation of the parameters was obtained by solving the scoring equation, and a function curve of the impact of risk factors on the risk of heart transplantation surgery was drawn. Results Simulation experiment suggested that the estimated values obtained by the proposed method were consistent and asymptotically effective under various settings with good fitting effects. Analysis of heart transplant surgery data showed that the donor's age had a positive linear relationship with the surgical risk. The impact of the recipient's age at disease onset increased at first and then stabilized, but increased against at an older age. The donor-recipient age difference had a positive linear relationship with the surgical risk of heart transplantation. Conclusion The nonparametric PH model established in this study can be used for predicting the risks in heart transplantation surgery and exploring the functional relationship between the surgery risks and the risk factors.

Objective To compare and analyze the differences between customized models and commercial universal models in the segmentation of organs-at-risk in cervical cancer,and to investigate the feasibility of customized models.Methods A retrospective analysis was conducted on 270 cervical cancer patients.Senior clinicians manually delineated organs-at-risk,including the bladder,rectum,small intestine,pelvic bone marrow,femoral heads,and kidneys.The cases were randomly selected to develop customized models,with 202 cases allocated to the training set,38 cases to the test set,and 30 cases to the validation set.The universal and customized models were used for segmentation on the test set,and the automatic segmentation results obtained by the two models were compared with manual segmentation results to assess the performance of the customized model.Results Both customized model and universal model had comparable DSC values to manual segmentation,demonstrating satisfactory delineation outcomes(DSC values ranging from 0.7 to 0.9).However,in terms of deviation of centroid and 95％Hausdorff distance,the customized model surpassed the universal model.Conclusion Compared with the universal model,the customized model offers superior accuracy in delineating the structures of organs-at-risk in cervical cancer.As the customized model is optimized based on specific datasets,it provides precise support for clinical decision-making and holds promising applications in the treatment of cervical cancer.

METTL3 and METTL14 are two components that form the core heterodimer of the main RNA m6A methyltransferase complex (MTC) that installs m6A. Surprisingly, depletion of METTL3 or METTL14 displayed distinct effects on stemness maintenance of mouse embryonic stem cell (mESC). While comparable global hypo-methylation in RNA m6A was observed in Mettl3 or Mettl14 knockout mESCs, respectively. Mettl14 knockout led to a globally decreased nascent RNA synthesis, whereas Mettl3 depletion resulted in transcription upregulation, suggesting that METTL14 might possess an m6A-independent role in gene regulation. We found that METTL14 colocalizes with the repressive H3K27me3 modification. Mechanistically, METTL14, but not METTL3, binds H3K27me3 and recruits KDM6B to induce H3K27me3 demethylation independent of METTL3. Depletion of METTL14 thus led to a global increase in H3K27me3 level along with a global gene suppression. The effects of METTL14 on regulation of H3K27me3 is essential for the transition from self-renewal to differentiation of mESCs. This work reveals a regulatory mechanism on heterochromatin by METTL14 in a manner distinct from METTL3 and independently of m6A, and critically impacts transcriptional regulation, stemness maintenance, and differentiation of mESCs.
Animals ; Mice ; Methylation ; Chromatin ; Histones/metabolism* ; RNA, Messenger/genetics* ; Methyltransferases/metabolism* ; RNA/metabolism*