Objective This study aimed to explore the experience and needs of dignity-conserving care of disabled elderly people in nursing homes,and to provide a basis for formulating a quality evaluation system for dignity-conserving care.Methods This descriptive qualitative study,involving a semi-structured in-depth interview of 13 disabled elderly people based on purposive sampling,was conducted from August to November 2022 at a nursing home in Hangzhou.Based on the harmony nursing theory,the directional content analysis method was performed in order to summarize and extract themes from the interview texts.Results The dignity-conserving care experience and needs of disabled elderly people were extracted and classified into 5 themes,including physical safety(physical health maintenance,privacy protection,hygiene and image maintenance),psychological health(psychological counseling,psychological support),social communication(well communication environment,harmonious way of communication),spiritual culture(self-realization,respect for faith),needs of dignity-conserving care(individualized health needs,activity participation needs,dignified communication needs,spiritual needs of respecting the elderly).Conclusion When conducting the dignity-conserving care,nursing homes should pay attention to the physical health of the disabled elderly,actively maintain the image and privacy of the disabled elderly people,pay attention to the needs of psychological health,provide psychological counseling and support,strengthen the construction of barrier-free environments and cultural environments,build mutual respect way of communication,fully respect the religious beliefs of disabled elderly people,promote the realization of self-value of disabled elderly people,broaden the channels of personalized service and activity participation,strengthen the interaction of the dignity and spirit of the respect for the elderly of nursing homes,comprehensively improve the quality of dignity-conserving care in nursing homes.

Objective:To develop and validate a nomogram for predicting the 1-and 3-year survival rates of patients receiving peritoneal dialysis.Methods:Patients who underwent peritoneal dialysis for the first time in Zhujiang hospital from January 1, 2010 to December 31, 2017 were enrolled. The patients from January 1, 2014 to December 31, 2017 were enrolled in a training dataset. Baseline clinical data were collected and the primary endpoint was all-cause death. Cox proportional hazard regression models were used to analyze risk factors affecting the survival rates. Nomograms were generated using the R rms package. The Harrell' concordance index (C-index), receiver operating characteristic curve and calibration curve were used to verify the performance of the model. Patients who underwent peritoneal dialysis from January 1, 2010 to December 31, 2013 were then selected to validate the external predictive accuracy of the prediction models.Results:The prediction cohort enrolled 457 patients, with a median follow-up time of 27.67(18.37, 39.22) months, and 64 patients (14.00%) died during follow-up. The 1-and 3-year cumulative survival rates were 96.4% and 83.0%. Multivariate analysis showed that aging (every 1 year old increase, HR=1.07, 95% CI 1.04-1.09, P<0.001), stroke ( HR=3.63, 95% CI 1.93-6.85, P<0.001), higher cholesterol (every 1 mmol/L increase, HR=1.51, 95% CI 1.20-1.89, P<0.001), higher neutrophil-to-lymphocyte ratio (every 1 increase, HR=1.12, 95% CI 1.05-1.20, P=0.001), and lower albumin ( HR=0.89, 95% CI 0.82-0.95, P=0.001) were independent risk factors affecting the survival rates of PD patients. The C-index of the prediction cohort and the validation cohort were 0.815(95% CI 0.765-0.865) and 0.804(95% CI 0.744-0.864, respectively). Both internally and externally verified calibration curves showed that the predicted results were close to the actual survival rates. Conclusion:Based on age, blood total cholesterol level, stroke history, and NLR, the prognosis prediction model of peritoneal dialysis patients established with nomogram can help predict the 1-year and 3-year survival rates of peritoneal dialysis patients.

Kidney is one of the most important organs of the body and the mammalian kidney development is essential for kidney unit formation. The key process of kidney development is metanephric development, where mesenchymal-epithelial transition (MET) plays a crucial role. Here we investigated the biological function of PPP3CA in metanephric mesenchyme (MM) cells. qRT-PCR and Western blotting were used to detect PPP3CA and MET makers expression in mK3, mK4 cells respectively at mRNA and protein level. Subsequently, PPP3CA was stably knocked down via lentivirus infection in mK4 cells. Flow cytometry, EdU/CCK-8 assay, wound healing assay were conducted to clarify the regulation of PPP3CA on cell apoptosis, proliferation and migration respectively. PPP3CA was expressed higher in epithelial-like mK4 cells than mesenchyme-like mK3 cells. Thus, PPP3CA was silenced in mK4 cells and PPP3CA deficiency promoted E-cadherin expression, cell apoptosis. Moreover, PPP3CA knock down attenuated cell proliferation and cell migration in mK4 cell. The underlying mechanism was associated with the dephosphorylation of PPP3CA on ERK1/2. Taken together, our results indicated that PPP3CA mediated MET process and cell behaviors of MM cells, providing new foundation for analyzing potential regulator in kidney development process.
Animals ; Apoptosis/genetics* ; Cell Line ; Cell Line, Tumor ; Cell Movement/genetics* ; Cell Proliferation/genetics* ; Epithelial-Mesenchymal Transition/genetics* ; Gene Silencing ; Mesenchymal Stem Cells/cytology* ; Mesoderm ; Mice

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.