Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals ; Neurogenesis/genetics* ; Cell Cycle/genetics* ; Mice, Knockout ; Mice ; Neural Stem Cells/metabolism* ; DNA-Binding Proteins/metabolism* ; Cyclin-Dependent Kinase 6/genetics* ; Cell Proliferation ; 3' Untranslated Regions ; Cerebral Cortex/embryology* ; RNA-Binding Proteins ; Mice, Inbred C57BL

Breast cancer remains a leading cause of mortality in women worldwide.Triple-negative breast cancer(TNBC)is a particularly aggressive subtype characterized by rapid progression,poor prognosis,and lack of clear therapeutic targets.In the clinic,delineation of tumor heterogeneity and development of effective drugs continue to pose considerable challenges.Within the scope of our study,high hetero-geneity inherent to breast cancer was uncovered based on the landscape constructed from both tumor and healthy breast tissue samples.Notably,TNBC exhibited significant specificity regarding cell prolif-eration,differentiation,and disease progression.Significant associations between tumor grade,prog-nosis,and TNBC oncogenes were established via pseudotime trajectory analysis.Consequently,we further performed comprehensive characterization of the TNBC microenvironment.A crucial epithelial subcluster,E8,was identified as highly malignant and strongly associated with tumor cell proliferation in TNBC.Additionally,epithelial-mesenchymal transition(EMT)-associated fibroblast and M2 macrophage subclusters exerted an influence on E8 through cellular interactions,contributing to tumor growth.Characteristic genes in these three cluster cells could therefore serve as potential therapeutic targets for TNBC.The collective findings provided valuable insights that assisted in the screening of a series of therapeutic drugs,such as pelitinib.We further confirmed the anti-cancer effect of pelitinib in an orthotopic 4T1 tumor-bearing mouse model.Overall,our study sheds light on the unique characteristics of TNBC at single-cell resolution and the crucial cell types associated with tumor cell proliferation that may serve as potent tools in the development of effective anti-cancer drugs.

Objective Through the development of"real-time monitoring,early warning and tracking management sys-tem for infectious diseases in hospitals",real-time monitoring and early warning are realized,report cards are generated,and case tracking and management of infectious diseases are formed.Methods We selected 22 185 cases of infectious disease re-ports from April 2020 to October 2022 and 33 640 cases of infectious disease reports from November 2022 to May 2024,and com-pared the 19-month period before and after the launch of the new infectious disease early warning management system with that be-fore the launch of the original traditional infectious disease reporting management system,and compared the rate of infectious dis-ease reporting,the accuracy of infectious disease reporting,the timeliness of infectious disease reporting(time),the accuracy of infectious disease reporting,and the quality of infectious disease reporting(time),Infectious disease reporting timeliness(time),effectiveness of infectious disease tracking,and clinical medical staff's satisfaction with infectious disease reporting were compared and analyzed.Results After the use of the new hospital infectious disease early warning and tracking management sys-tem,the differences in infectious disease reporting rate,infectious disease reporting accuracy,infectious disease reporting timeli-ness,infectious disease tracking effectiveness,and clinical medical staff's satisfaction with infectious disease reporting were all sta-tistically significant(P＜0.05).Conclusion The development of"real-time monitoring,early warning and tracking management system for infectious diseases in hospitals"has significantly improved the reporting rate of infectious diseases,the accuracy of infec-tious disease reporting,the timeliness of infectious disease reporting,the effectiveness of infectious disease tracking,and the satis-faction of infectious disease reporting of clinical medical staff,and it has the characteristics of real-time,high efficiency and accura-cy,and the effect of early warning and tracking management is good,which has good value for promotion.It is characterized by re-al-time,high efficiency and accuracy,with good effect of early warning and tracking management,and has good promotion value.