A nomogram for predicting the risk of cancer-related cognitive impairment in breast cancer patients based on a scientific symptom model.

Cancer-related cognitive impairment is a significant clinical challenge observed in patients with breast cancer, manifesting during or after treatment. This impairment leads to deteriorations in memory, processing speed, attention, and executive functioning, which profoundly impact patients' occupational performance, daily living activities, and overall quality of life. Grounded in the Symptom Science Model 2.0, this study investigates the contributing factors to Cancer-related cognitive impairment in breast cancer patients and develops a predictive nomogram for this demographic. Employing both univariate and multivariate logistic regression analyses, this investigation delineates the predictive factors influencing outcomes in breast cancer patients. A nomogram was constructed leveraging these identified predictive factors, accompanied by internal validation through bootstrap resampling methodology (1000 bootstrap samples). The efficacy of the predictive model was assessed by employing the Hosmer-Lemeshow goodness-of-fit test and calibration curves. The prevalence of cognitive impairment in breast cancer patients was identified to be 45.83%.Multivariate logistic regression analysis identified the independent predictors of Cancer-related cognitive impairment in breast cancer patients as place of residence, educational level, chemotherapy, benefit finding, post-traumatic growth, anxiety, fear of cancer progression, and fasting blood glucose levels. these factors were integrated into the nomogram. The Hosmer-Lemeshow goodness-of-fit test demonstrated that the prediction model was appropriately calibrated (χ2 = 11.520, P = 0.174). Furthermore, the model exhibited an area under the curve of 0.955 (95% CI 0.939 to 0.971) and a sensitivity of 0.906, evidencing its robust discriminative capacity and accuracy. Utilizing the Symptom Science Model 2.0 as a framework, this study comprehensively examines the multifaceted factors influencing Cancer-related cognitive impairment in breast cancer patients, spanning five critical domains: complex symptoms, phenotypic characterization, biobehavioral factors, social determinants of health, and patient-centered experiences. A predictive nomogram model was established, demonstrating satisfactory predictive accuracy and capability. This model is capable of identifying breast cancer patients with cognitive impairments with high precision. The findings furnish empirical evidence in support of the early detection, diagnosis, and intervention strategies for high-risk breast cancer patients afflicted with Cancer-related cognitive impairment.

Microglia trigger the structural plasticity of GABAergic neurons in the hippocampal CA1 region of a lipopolysaccharide-induced neuroinflammation model.

It is well-established that microglia-mediated neuroinflammatory response involves numerous neuropsychiatric and neurodegenerative diseases. While the role of microglia in excitatory synaptic transmission has been widely investigated, the impact of innate immunity on the structural plasticity of GABAergic inhibitory synapses is not well understood. To investigate this, we established an inflammation model using lipopolysaccharide (LPS) and observed a prolonged microglial response in the hippocampal CA1 region of mice, which was associated with cognitive deficits in the open field test, Y-maze test, and novel object recognition test. Furthermore, we found an increased abundance of GABAergic interneurons and GABAergic synapse formation in the hippocampal CA1 region. The cognitive impairment caused by LPS injection could be reversed by blocking GABA receptor activity with (-)-Bicuculline methiodide. These findings suggest that the upregulation of GABAergic synapses induced by LPS-mediated microglial activation leads to cognitive dysfunction. Additionally, the depletion of microglia by PLX3397 resulted in a decrease in GABAergic interneurons and GABAergic inhibitory synapses, which blocked the cognitive decline induced by LPS. In conclusion, our findings indicate that excessive reinforcement of GABAergic inhibitory synapse formation via microglial activation contributes to LPS-induced cognitive impairment.

Genetic diversity and phylogenetic analysis of porcine reproductive and respiratory syndrome virus isolates in East China.

Porcine reproductive and respiratory syndrome virus (PRRSV) has been reported to have evolved at a high evolutionary rate and the extensive genetic variation. In this study, 44 PRRSV positive cases obtained from different provinces of China were sequenced and analyzed. Comparative analysis of partial isolates based on nsp2 sequences revealed that highly pathogenic PRRSV were the dominant viruses in China from 2008 to 2010 and some novel strains with an extra deletion of 19aa. Phylogenetic analysis based on the GP5 genes showed that the PRRSV isolates from 1996 to 2010 had a great variation and the North American genotype was further divided into six subgenotypes. No apparent relationship between the heterogeneity and the geographic origin of isolates was observed. The 44 isolates and 29 representative strains were divided into six subgenotypes. Further analysis of the GP5 protein suggested that these strains of subgenotypes I, II and III exhibited variations in the primary neutralizing epitope and almost all isolates of subgenotypes II and III had more N-linked glycosylation sites. In addition, some mutations which could mirror the viral evolution and adaptation were also observed in this study. All these results might be useful to study the genetic variation and genetic relatedness among PRRSV strains in China.