Diabetic nephropathy （DN） is one of the most common and severe microvascular complications of diabetes， with a complex pathogenesis involving immune inflammatory responses， oxidative stress， apoptosis， glomerulosclerosis， renal interstitial fibrosis， and other pathological processes. In recent years， numerous animal or cell model experiments have revealed that the transforming growth factor-β （TGF-β）/mothers against decapentaplegic homolog （Smad）， phosphoinositide 3-kinase （PI3K）/ protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， mitogen-activated protein kinase （MAPK）， AMP-activated protein kinase （AMPK）， nuclear factor-κB （NF-κB）， Janus kinase （JAK）/signal transducer and activator of transcription （STAT）， neurogenic locus notch homolog protein （Notch）， nuclear factor E₂-related factor 2 （Nrf2）， secretory glycoprotein （Wnt）/β-catenin， and other classical signaling pathways play important roles in the occurrence and development of DN. Traditional Chinese medicines， as natural drugs， possess characteristics such as multiple components， multiple targets， and few adverse reactions， demonstrating unique advantages in regulating the aforementioned signaling pathways and improving renal pathological changes. This review summarized recent research progress on the intervention of DN through the regulation of the aforementioned signaling pathways by single compounds and formulas of traditional Chinese medicine， focusing on their mechanisms of action in regulating immune inflammatory responses， inhibiting renal fibrosis， oxidative stress， improving metabolic disorders， and other aspects. The aim is to provide theoretical references for a deeper understanding of the modern pharmacological basis and clinical application of traditional Chinese medicine in the treatment of DN.

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

OBJECTIVES: To investigate the molecular mechanism underlying Leber hereditary optic neuropathy (LHON) caused by the m.3472T>C (p.Phe56Leu) mutation. METHODS: From a cohort of 1397 LHON patients, three large pedigrees (WZL122, WZ676, WZ706) carrying the m.3472T>C mutation were identified and selected for this study. Immortalized lymphoblastoid cell lines were established from peripheral blood samples obtained from two affected individuals carrying the homoplasmic m.3472T>C mutation (derived from one Han Chinese LHON pedigree) and two genetically unrelated, matched healthy controls. The MitoTool software was used to analyze the complete mitochondrial DNA sequence to determine the haplogroup background, and the conservation of the mtDNA mutation site was evaluated using the MitoMap database. The secondary structure of the ND1 protein was predicted and analyzed using online prediction software. The three-dimensional structure and molecular interaction changes of wild-type and mutant ND1 proteins were visualized and analyzed using PyMOL. Western blotting was performed to determine the expression levels of key proteins. Cellular ATP levels were measured using a chemiluminescence assay. Mitochondrial membrane potential and intracellular reactive oxygen species (ROS) levels were assessed by flow cytometry. RESULTS: mtDNA haplotype analysis showed that the subjects all belonged to the East Asian mitochondrial haplogroup D4. The m.3472T>C mutation results in the substitution of a highly conserved phenylalanine with leucine (p.Phe56Leu) in the ND1 subunit of mitochondrial complex Ⅰ, which may alter the structure and function of ND1. In lymphoblastoid cell lines carrying the m.3472T>C mutation, manifestations of mutant ND1 instability were observed, including reduced ND1 protein levels, diminished mitochondrial ATP production, decreased mitochondrial membrane potential, and increased mitochondrial ROS production. Concurrently, the expression levels of the antioxidant enzymes catalase and SOD2 were elevated (all P<0.01). These findings collectively suggest impaired complex Ⅰ function. CONCLUSIONS The m.3472T>C mutation contributes to the pathogenesis of LHON by disrupting the structural stability of the ND1 subunit in complex Ⅰ, leading to mitochondrial dysfunction.

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

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 understand the trends of the disease burden of Alzheimer's disease(AD)attributable to high body mass index(BMI)and high fasting plasma glucose(FPG)in the past 30 years and future trends in China, and to provide suggestions for the prevention and treatment of AD.Methods:Based on the Global Burden of Disease Research Database(GBD), data on AD deaths and disability adjusted life years(DALYs)attributable to high BMI and high FPG were collected from 1990 to 2021 in Chinese and global populations.The Joinpoint log-linear regression model was used to explore and compare the changing trends of AD burden in China and globally from 1990 to 2021, and a Bayesian age-period-cohort model was constructed for predictive analysis.Results:In 2021, the age-standardized mortality and DALYs rates of AD attributed to high BMI in the Chinese population were 1.256/100, 000 and 24.751/100, 000, respectively, and those attributed to high FPG were 3.636/100, 000 and 66.721/100, 000, respectively.The age-standardized rates of mortality and DALYs of females were both higher than those of males.From 1990 to 2021, the age-standardized rates of mortality and DALYs of AD attributed to high BMI increased slowly at first and then rapidly in China, the corresponding average annual percent change(AAPC)and 95% confidence interval(95% CI)were 9.87%(9.63%-10.12%), and 9.81%(9.54%-10.09%), respectively( P<0.001). The age-standardized rates of mortality and DALYs of AD caused by high FPG showed a fluctuating upward trend, with AAPC of 0.29%(95% CI: 0.17%-0.41%)and 0.53%(95% CI: 0.45%-0.61%), respectively( P<0.001). It is predicted that by 2030, the age-standardized rates of mortality and DALYs of AD attributed to high BMI and high FPG in the whole population of China will increase to 4.87/100 000 and 97.20/100 000, both lower than the global level(5.45/100 000 and 100.24/100 000). In addition to a slight decline in the age-standardized mortality rate in Chinese men, the age-standardized rates of mortality and DALYs attributed to high BMI and high FPG in Chinese women and the global population will both show an upward trend. Conclusions:The burden of AD attributed to high BMI and high FPG is relatively severe, with gender differences, and is expected to increase slightly by 2030.It is recommended that early identification of key high-risk populations of AD should be strengthened, especially for the elderly and female groups.Interventions targeting modifiable risk factors should be carried out, and effective measures should be adopted to reduce the burden of AD.

Allergen-specific Immunotherapy (AIT) is currently the only allopathic treatment capable of modifying the natural course of immunoglobulin E (IgE)-mediated allergic diseases. Currently, there is a lack of recognized clinical markers for evaluating and predicting the efficacy of AIT, and some biological markers may have some potential for application. This article will summarize the currently known indicators for evaluating and predicting the therapeutic effects of AIT, with the aim of providing assistance in evaluating and monitoring the efficacy of AIT.