Reactive astrocytes, which exhibit a correlation with the degeneration of dopaminergic neurons, are present in a considerable number during the progression of Parkinson's disease (PD). However, the underlying factors shaping astrocyte reactivity and neuroinflammation in PD remain inadequately elucidated. Here, we demonstrate that fibroblast growth factor 7 (FGF7)/FGF receptor 2 (FGFR2) autocrine signaling intensifies astrocyte reactivity and inflammation. Genetic deletion of Arrb2, β-Arrestin2 encoding gene, led to escalated astrocyte reactivity in MPTP-treated mice, which was further substantiated in astrocyte-specific Arrb2 knockdown mice. RNA sequencing profiling of Arrb2 knockout astrocytes identified Fgf7 as a critical effector of astrocyte reactivity. Subsequently, conditional knockdown of Fgf7 and its receptor Fgfr2 in astrocytes elicited advantageous effects for MPTP-treated mice by restraining the inflammatory phenotypic transition of reactive astrocytes. Furthermore, deletion of astrocytic Fgf7 mitigated MPTP-induced pathology in Arrb2 knockout mice. Mechanistically, STAT1 was distinguished as the transcription factor suppressing Fgf7 expression, while β-Arrestin2 counteracted the proteasomal degradation of STAT1 by binding to RNF220, an E3 ubiquitin ligase for STAT1. More importantly, selectively engaging dopamine D2 receptor (Drd2)/β-Arrestin2-biased signaling using the agonist UNC9995 exhibited therapeutic potential in MPTP-treated mice via moderation of astrocytic FGF7 production, thereby restoring balance in astrocyte reactivity. Collectively, our study bridges a crucial knowledge gap by elucidating the novel functions of FGF family members within the central nervous system, particularly within the context of PD. The autocrine signaling of FGF7/FGFR2 represents a novel mechanism and a potential druggable target for modulating astrocyte-derived inflammation.

Ovulatory dysfunction (OD) is one of the main causes of infertility in women of childbearing age, which not only affects their reproductive ability, but also physical and mental health. Traditional treatment strategies have limited efficacies, and the emergence of biomedicines provides a promising alternative solution via the strategies of combining engineered design with modern advanced technology. This review explores the pathophysiological characteristics and related induction mechanisms of OD, and evaluates the current cutting-edge advances in its treatments. It emphasizes the potentials of biomedicines strategies such as hydrogels, nanoparticles and extracellular vesicles in improving therapeutic precision and efficacy. By mimicking natural physiological processes, and achieving controlled drug release, these advanced drug carriers are expected to address the challenges in ovarian microenvironment reprogramming, tissue repair, and metabolic and immune regulation. Despite the promising progress, there are still challenges in terms of biomedical complexity, differences between animal models and human physiology, and the demand for intelligent drug carriers in the therapy of OD. Future researches are mainly dedicated to developing precise personalized biomedicines in OD therapy through interdisciplinary collaboration, promoting the development of reproductive regenerative medicine.

Purpose/Significance To explore and implement the automated interpretation of pediatric medical exam answers,so as to enhance the efficiency and quality of answer explanation compilation.Method/Process The paper proposes a method that combines latent semantic indexing(LSI),MC-BERT,and the CoSENT model.Initially,multiple candidate answer explanations are extracted from ref-erence documents using the LSI method and the MC-BERT model.Subsequently,the CoSENT model is employed to calculate the simi-larity between the candidate explanations and the question stems as well as the answer options.The candidate explanation with the highest similarity is then selected as the final answer explanation.Result/Conclusion The experimental results show that the method presented in this paper achieves a precision rate of 72.6％.Compared to single methods or models,it significantly improves the recall and precision of answer parsing,effectively enhances the efficiency of compiling question answer explanations,reduces the burden on educators,and pro-vides significant data support for educational research.

OBJECTIVE: This study investigated the association between household chemical use and respiratory disease (RD) in older Chinese adults. METHODS: The data were from the 2018 China Longitudinal Health and Longevity Survey (CLHLS) database, which included 12,866 participants aged ≥ 65 years. The prevalence of RD was based on self-reported medical history, and patients were divided into diseased and non-diseased groups. The frequency of household chemical usage was divided into four categories, and a total score for eight household chemical usage categories was constructed. Binary logistic regression was used to determine the relationship between the frequency of household chemical use and RD, and a restricted cubic spline was used to determine the dose-response association. RESULT: After adjusting for all covariates, regular use of repellents [odds ratios ( OR) = 1.28, 95% CI 1.06-1.55] and oil removers ( OR = 1.28, 95% CI 1.03-1.58) were associated with RD. There was a dose-response association between the total score of household chemicals usage and RD risk ( P non-linearity > 0.05, P for trend < 0.01). Using patients with the total score below 9 as a reference, the OR for patients with the total score ranging from 25 to 32 is 2.33 (95% CI 1.25-4.09). CONCLUSION Regular use of repellents and oil removers increased the risk of RD, and the dose-dependent relationship was also observed.
Humans ; China/epidemiology* ; Aged ; Male ; Female ; Respiratory Tract Diseases/chemically induced* ; Aged, 80 and over ; Household Products/adverse effects* ; Prevalence

【Objective】 To evaluate and analyze the impact of COVID-19 epidemic on inventory of red blood cells (RBCs)in local and municipal blood stations in China, and to provide reference for the management of public health emergencies. 【Methods】 Relevant data from 2018 to 2021 were collected, and the differences in the volume of qualified RBCs, the usage efficiency of inventory RBCs, the average daily distribution of RBCs,the blood distribution rate of RBCs prepared by 400 mL whole blood, the difference in the average storage days of RBCs at the time of distribution, the average daily inventory of RBCs and the time of the average daily inventory of RBCs to maintain the distribution in 24 local and municipal blood stations in China during the COVID-19 epidemic and non-epidemic periods were retrospectively analyzed. 【Results】 Compared with non-epidemic periods, the volume of qualified RBCs [(117 525.979 ±52 203.175)U] and the average daily distribution of RBCs [( 156. 468 ± 70. 186) U ] increased significantly, but the usage efficiency of inventory RBCs decreased(97.24%±0.51%) significantly (P<0.05).There was no significant difference in the blood distribution rate of RBCs prepared by 400 mL whole blood(73.88%±20.30%), the average storage days of RBCs distribution(13.040 ±3.486), the average daily stock quantity of RBCs[(2 280.542 ±1 446.538) U ] and the time of the average daily inventory of RBCs to maintain the distribution[(15.062 ±7.453) d] (P>0.5). 【Conclusion】 During the COVID-19 epidemic, the inventory management of RBCs operated well, the overall inventory remained relatively stable, the stock composition and storage period showed no significant change.

BACKGROUND: Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. METHODS: In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). RESULTS: A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. CONCLUSIONS A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.
Humans ; Female ; Breast Neoplasms/genetics* ; East Asian People ; Neoplasm Recurrence, Local/genetics* ; Breast ; Algorithms ; Chronic Disease ; Prognosis ; Tumor Microenvironment

Objective:To investigate the pseudo-CT generation from cone beam CT (CBCT) by a deep learning method for the clinical need of adaptive radiotherapy.Methods:CBCT data from 74 prostate cancer patients collected by Varian On-Board Imager and their simulated positioning CT images were used for this study. The deformable registration was implemented by MIM software. And the data were randomly divided into the training set ( n=59) and test set ( n=15). U-net, Pix2PixGAN and CycleGAN were employed to learn the mapping from CBCT to simulated positioning CT. The evaluation indexes included mean absolute error (MAE), structural similarity index (SSIM) and peak signal to noise ratio (PSNR), with the deformed CT chosen as the reference. In addition, the quality of image was analyzed separately, including soft tissue resolution, image noise and artifacts, etc. Results:The MAE of images generated by U-net, Pix2PixGAN and CycleGAN were (29.4±16.1) HU, (37.1±14.4) HU and (34.3±17.3) HU, respectively. In terms of image quality, the images generated by U-net and Pix2PixGAN had excessive blur, resulting in image distortion; while the images generated by CycleGAN retained the CBCT image structure and improved the image quality.Conclusion:CycleGAN is able to effectively improve the quality of CBCT images, and has potential to be used in adaptive radiotherapy.

Objective To explore the association between lipid profiles and left ventricular hypertrophy in a Chinese general population. Methods We conducted a retrospective observational study to investigate the relationship between lipid markers [including triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein (HDL) cholesterol, non-HDL-cholesterol, apolipoprotein A-I, apolipoprotein B, lipoprotein[a], and composite lipid profiles] and left ventricular hypertrophy. A total of 309,400 participants of two populations (one from Beijing and another from nationwide) who underwent physical examinations at different health management centers between 2009 and 2018 in China were included in the cross-sectional study. 7,475 participants who had multiple physical examinations and initially did not have left ventricular hypertrophy constituted a longitudinal cohort to analyze the association between lipid markers and the new-onset of left ventricular hypertrophy. Left ventricular hypertrophy was measured by echocardiography and defined as an end-diastolic thickness of the interventricular septum or left ventricle posterior wall > 11 mm. The Logistic regression model was used in the cross-sectional study. Cox model and Cox model with restricted cubic splines were used in the longitudinal cohort. Results In the cross-sectional study, for participants in the highest tertile of each lipid marker compared to the respective lowest, triglycerides [odds ratio (OR): 1.250, 95％CI: 1.060 to 1.474], HDL-cholesterol (OR: 0.780, 95％CI: 0.662 to 0.918), and lipoprotein(a) (OR: 1.311, 95％CI: 1.115 to 1.541) had an association with left ventricular hypertrophy. In the longitudinal cohort, for participants in the highest tertile of each lipid marker at the baseline compared to the respective lowest, triglycerides [hazard ratio (HR): 3.277, 95％CI: 1.720 to 6.244], HDL-cholesterol (HR: 0.516, 95％CI: 0.283 to 0.940), non-HDL-cholesterol (HR: 2.309, 95％CI: 1.296 to 4.112), apolipoprotein B (HR: 2.244, 95％CI: 1.251 to 4.032) showed an association with new-onset left ventricular hypertrophy. In the Cox model with forward stepwise selection, triglycerides were the only lipid markers entered into the final model. Conclusion Lipids levels, especially triglycerides, are associated with left ventricular hypertrophy. Controlling triglycerides level potentiate to be a strategy in harnessing cardiac remodeling but deserve to be further investigated.

Objective:To investigate the workflow, efficacy and safety of MR-Linac in liver malignancies.Methods:Clinical data of 15 patients with hepatocellular carcinomas (HCC) or liver metastases treated with MR-Linac between November 2019 and July 2021 were retrospectively analyzed. The workflow of MR-Linac was investigated and image identification rate was analyzed. Patients were followed up for response and toxicity assessment.Results:Fifteen patients (6 HCC, 8 liver metastases from colorectal cancer, 1 liver metastasis from breast cancer) were enrolled. A total of 21 lesions were treated, consisting of 10 patients with single lesion, 4 patients with double lesions and 1 patient with triple lesions. The median tumor size was 2.4 cm (0.8-9.8 cm). The identification rate for gross tumor volume (GTV) in MR-Linac was 13/15. Although GTV of two patients were unclearly displayed in MR-Linac images, the presence of adjacent blood vessel and bile duct assisted the precise registration. All the patients were treated with stereotactic body radiation therapy (SBRT). For HCC, the median fraction dose for GTV or planning gross tumor volume (PGTV) was 6 Gy (5-10 Gy) and the median number of fractions was 9(5-10). The median total dose was 52 Gy (50-54 Gy) and the median equivalent dose in 2 Gy fraction (EQD 2Gy) at α/ β= 10 was 72 Gy (62.5-83.3 Gy). For liver metastases, the median fraction dose for GTV or PGTV was 5 Gy (5-10 Gy) and the median number of fractions was 10(5-10). The median total dose was 50 Gy (40-50 Gy) and the median EQD 2Gy at α/ β=5 was 71.4 Gy (71.4-107.1 Gy). At 1 month after SBRT, the in-field objective response rate (ORR) was 8/13 and the disease control rate was 13/13. At 3-6 months after SBRT, the in-filed ORR was increased to 6/6. During the median follow-up of 4.0 months (0.3-11.6), 4-month local progression-free survival, progression-free survival and overall survival were 15/15, 11/15 and 15/15, respectively. Toxicities were mild and no grade 3 or higher toxicities were observed. Conclusions:MR-Linac provides a platform with high identification rates of liver lesions. Besides, the presence of adjacent blood vessel and bile duct also assists the precise registration. It is especially suitable for liver malignancies with promising local control and well tolerance.