Objective: In ovarian cancer (OvCa), tumor cell high glucocorticoid receptor (GR) has been associated with poor patient prognosis. In vitro, GR activation inhibits chemotherapyinduced OvCa cell death in association with transcriptional upregulation of genes encoding anti-apoptotic proteins. A recent randomized phase II study demonstrated improvement in progression-free survival (PFS) for heavily pre-treated OvCa patients randomized to receive therapy with a selective GR modulator (SGRM) plus chemotherapy compared to chemotherapy alone. We hypothesized that SGRM therapy would improve carboplatin response in OvCa patient-derived xenograft (PDX). Methods: Six high-grade serous (HGS) OvCa PDX models expressing GR mRNA (NR3C1) and protein were treated with chemotherapy +/− SGRM. Tumor size was measured longitudinally by peritoneal transcutaneous ultrasonography. Results: One of the 6 GR-positive PDX models showed a significant improvement in PFS with the addition of a SGRM. Interestingly, the single model with an improved PFS was least carboplatin sensitive. Possible explanations for the modest SGRM activity include the high carboplatin sensitivity of 5 of the PDX tumors and the potential that SGRMs activate the tumor invasive immune cells in patients (absent from immunocompromised mice). The level of tumor GR protein expression alone appears insufficient for predicting SGRM response. Conclusion The significant improvement in PFS shown in 1 of the 6 models after treatment with a SGRM plus chemotherapy underscores the need to determine predictive biomarkers for SGRM therapy in HGS OvCa and to better identify patient subgroups that are most likely to benefit from adding GR modulation to chemotherapy.

Objective: In ovarian cancer (OvCa), tumor cell high glucocorticoid receptor (GR) has been associated with poor patient prognosis. In vitro, GR activation inhibits chemotherapyinduced OvCa cell death in association with transcriptional upregulation of genes encoding anti-apoptotic proteins. A recent randomized phase II study demonstrated improvement in progression-free survival (PFS) for heavily pre-treated OvCa patients randomized to receive therapy with a selective GR modulator (SGRM) plus chemotherapy compared to chemotherapy alone. We hypothesized that SGRM therapy would improve carboplatin response in OvCa patient-derived xenograft (PDX). Methods: Six high-grade serous (HGS) OvCa PDX models expressing GR mRNA (NR3C1) and protein were treated with chemotherapy +/− SGRM. Tumor size was measured longitudinally by peritoneal transcutaneous ultrasonography. Results: One of the 6 GR-positive PDX models showed a significant improvement in PFS with the addition of a SGRM. Interestingly, the single model with an improved PFS was least carboplatin sensitive. Possible explanations for the modest SGRM activity include the high carboplatin sensitivity of 5 of the PDX tumors and the potential that SGRMs activate the tumor invasive immune cells in patients (absent from immunocompromised mice). The level of tumor GR protein expression alone appears insufficient for predicting SGRM response. Conclusion The significant improvement in PFS shown in 1 of the 6 models after treatment with a SGRM plus chemotherapy underscores the need to determine predictive biomarkers for SGRM therapy in HGS OvCa and to better identify patient subgroups that are most likely to benefit from adding GR modulation to chemotherapy.

Objective: In ovarian cancer (OvCa), tumor cell high glucocorticoid receptor (GR) has been associated with poor patient prognosis. In vitro, GR activation inhibits chemotherapyinduced OvCa cell death in association with transcriptional upregulation of genes encoding anti-apoptotic proteins. A recent randomized phase II study demonstrated improvement in progression-free survival (PFS) for heavily pre-treated OvCa patients randomized to receive therapy with a selective GR modulator (SGRM) plus chemotherapy compared to chemotherapy alone. We hypothesized that SGRM therapy would improve carboplatin response in OvCa patient-derived xenograft (PDX). Methods: Six high-grade serous (HGS) OvCa PDX models expressing GR mRNA (NR3C1) and protein were treated with chemotherapy +/− SGRM. Tumor size was measured longitudinally by peritoneal transcutaneous ultrasonography. Results: One of the 6 GR-positive PDX models showed a significant improvement in PFS with the addition of a SGRM. Interestingly, the single model with an improved PFS was least carboplatin sensitive. Possible explanations for the modest SGRM activity include the high carboplatin sensitivity of 5 of the PDX tumors and the potential that SGRMs activate the tumor invasive immune cells in patients (absent from immunocompromised mice). The level of tumor GR protein expression alone appears insufficient for predicting SGRM response. Conclusion The significant improvement in PFS shown in 1 of the 6 models after treatment with a SGRM plus chemotherapy underscores the need to determine predictive biomarkers for SGRM therapy in HGS OvCa and to better identify patient subgroups that are most likely to benefit from adding GR modulation to chemotherapy.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Objective To investigate the independent risk factors affecting the prognosis of chronic active antibody-mediated rejection (caAMR) after kidney transplantation. Methods A retrospective analysis was conducted on 61 patients who underwent renal biopsy and were diagnosed with caAMR. The patients were divided into caAMR group (n=41) and caAMR+TCMR group (n=20) based on the presence or absence of concurrent acute T cell-mediated rejection (TCMR). The patients were followed up for 3 years. The value of 24-hour urinary protein and estimated glomerular filtration rate (eGFR) at the time of biopsy in predicting graft loss was assessed using receiver operating characteristic (ROC) curves. The independent risk factors affecting caAMR prognosis were analyzed using the LASSO-Cox regression model. The correlation between grouping, outcomes, and Banff scores was compared using Spearman rank correlation matrix analysis. Kaplan-Meier analysis was used to evaluate the renal allograft survival rates of each subgroup. Results The 3-year renal allograft survival rates for the caAMR group and the caAMR+TCMR group were 83% and 79%, respectively. The area under the ROC curve (AUC) for predicting 3-year renal allograft loss was 0.83 ［95% confidence interval (CI) 0.70-0.97］ for eGFR and 0.78 (95% CI 0.61-0.96) for 24-hour urinary protein at the time of biopsy. LASSO-Cox regression analysis and Kaplan-Meier analysis showed that eGFR≤25.23 mL/(min·1.73 m²) and the presence of donor-specific antibody (DSA) against human leukocyte antigen (HLA) class I might be independent risk factors affecting renal allograft prognosis, with hazard ratios of 7.67 (95% CI 2.18-27.02) and 5.13 (95% CI 1.33-19.80), respectively. A strong correlation was found between the Banff chronic lesion indicators of renal interstitial fibrosis and tubular atrophy (P<0.05). Conclusions The presence of HLA class I DSA and eGFR≤25.23 mL/(min·1.73 m²) at the time of biopsy may be independent risk factors affecting the prognosis of caAMR.

Objective: To examine the association between the left behind status and health risk behaviors (HRB) among adolescents, so as to provide empirical evidence for identifying high risk groups and developing intervention measures for HRB. Methods: From October to November 2023, by using a combination of convenient sampling and cluster sampling,14 964 adolescents from 6 schools in a county level city in Hubei Province (3 junior high schools and 3 senior high schools) and 7 schools in a county level city in Hunan Province (all junior high schools) were selected as the research subjects. The adolescents were divided into non-left-behind, father absent, mother absent, and both parents absent groups based on their left behind status. A self designed adolescent HRB questionnaire was utilized to investigate the prevalence of 12 types of HRBs and their co-existence among the subjects. Multifactorial Logistic regression and unordered multinomial Logistic regression analyses were used to explore the association between the left behind status of adolescents and the occurrence of individual HRBs as well as the co-existence of multiple HRBs. Results: After controlling for gender, age, only child, and subjective socioeconomic status, the results of the multiple factor Logistic regression analysis showed that having father in absence for working was positively associated with screen use long time on school days ( OR= 1.15, 95%CI =1.05-1.26) and rest days ( OR=1.16, 95%CI =1.06-1.26); having mother in absence for working was significantly associated with increased risks of smoking ( OR=1.68, 95%CI =1.22-2.32), spending long time on screen during school days ( OR= 1.19, 95%CI =1.00-1.41)and rest days ( OR=1.36, 95%CI =1.16-1.59), skipping breakfast ( OR=1.20, 95%CI =1.03-1.39), skipping dinner ( OR=1.20, 95%CI =1.01-1.43), not eating fruit ( OR=1.34, 95%CI =1.12-1.61), and consuming sugar sweetened beverages ( OR=1.30, 95%CI =1.09-1.55); having both parents in absence for working was positively associated with screen use on rest days ( OR=1.51, 95%CI =1.38-1.65), skipping dinner ( OR=1.15, 95%CI =1.04-1.27), not eating fruit ( OR=1.80, 95%CI =1.62-1.99),and non suicidal self injury ( OR=1.16, 95%CI =1.04-1.29), and negatively associated with fast food consumption ( OR=0.72, 95%CI =0.65-0.79)(all P <0.05).The results of unordered multiclass Logistic regression analysis showed that mother absence for working was associated with an increased risk of moderate and high co-occurrence of HRBs ( OR= 1.25, 95%CI=1.06-1.47; OR=1.67, 95%CI =1.30-2.13), both parents absence for working was also positively correlated with a high cooccurrence risk of HRBs ( OR=1.29, 95%CI =1.11-1.50) (all P <0.05). Conclusion Father absence for working is only related to adolescents screen time, while adolescents with mother absence or both parents absent for working are priority groups for HRB prevention.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis* ; Saccharomyces cerevisiae/genetics* ; Triterpenes/metabolism* ; Metabolic Engineering ; Oleanolic Acid/biosynthesis* ; Ursolic Acid

The zebrafish model has attracted much attention due to its strong reproductive ability, short research cycle, and ease of maintenance. It has always been an important vertebrate model system, often used to carry out human disease research. Its motor behavior features have the advantages of being simpler, more intuitive, and quantifiable. In recent years, it has received widespread attention in the study of traditional Chinese medicine(TCM)for the treatment of sleep disorders, neurodegenerative diseases, fatigue, epilepsy, and other diseases. This paper reviews the characteristics of zebrafish motor behavior and its applications in the pharmacodynamic verification and mechanism research of TCM extracts, active ingredients, and TCM compounds, as well as in active ingredient screening and safety evaluation. The paper also analyzes its advantages and disadvantages, with the aim of improving the breadth and depth of zebrafish and its motor behavior applications in the field of TCM research.
Zebrafish/physiology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Drug Evaluation, Preclinical/methods* ; Animals ; Sleep Wake Disorders/physiopathology* ; Epilepsy/physiopathology* ; Neurodegenerative Diseases/physiopathology* ; Fatigue/physiopathology* ; Behavior, Animal/physiology* ; Motor Activity/physiology*

Three taraxerane nortriterpenoids were isolated from mastic by using various modern chromatographic separation techniques. They were identified as(5R,8R,9R,10S,11S,12R,13S,17R,18R)-28-norlupa-11,12-epoxy-14-taraxerene-3,16-dione(1),(5R,8R,9R,10S,11S,12R,13S,17S,18S)-17-hydroxy-28-norlupa-11,12-epoxy-14-taraxerene-3-one(2), and(5R,8R,9R,10R,11S,12R,13R,14S,17S,18S)-14,17-epoxy-28-norlupa-11,12-oxidotaraxerone(3) through the high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), infrared(IR), ultraviolet(UV), nuclear magnetic resonance(NMR), and single-crystal X-ray diffraction techniques as well as comparison with literature data. Compounds 1-3 were C-28 nortriterpenoids and isolated from mastic for the first time, and compounds 1-2 were new ones. In the model for RAW264.7 cell anti-inflammation induced by lipopolysaccharide(LPS), compound 1 demonstrates an inhibitory effect on nitric oxide(NO) [IC_(50)=(13.38±0.68) μmol·L~(-1)], comparable to the activity of the positive control dexamethasone [IC_(50)=(14.59±1.49) μmol·L~(-1)]. Compounds 2 and 3 exhibit weaker inhibitory effects, with IC_(50) values of(24.17±2.56) and(22.25±2.84) μmol·L~(-1), respectively.
Animals ; Mice ; Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Mastic Resin/chemistry* ; Nitric Oxide ; Molecular Structure ; Macrophages/immunology* ; RAW 264.7 Cells