Purpose: In this study, the neural communication patterns between hypothalamic structures and cortical areas in girls diagnosed with central precocious puberty (CPP) were explored. Endocrine profiles were incorporated to clarify the pathophysiological interactions between cerebral networks and hormonal regulation. The hypothalamus was designated as the key focus area for connectivity analysis. Methods: Fifty-seven girls (37 CPP, 20 non-CPP) were recruited from the Pediatric Development Clinic at the Second Affiliated Hospital of Anhui Medical University. The collected data included demographic information, gonadotropin-releasing hormone stimulation tests, and magnetic resonance imaging scans. Hypothalamic functional connectivity (FC) was analyzed using predefined region of interest coordinates, and correlations between hormone levels and FC values were assessed. Results: Compared to the non-CPP group, the CPP group exhibited elevated baseline follicle-stimulating hormone (FSH), baseline luteinizing hormone (LH), peak FSH, peak LH, and peak LH/FSH ratios. Patients with CPP exhibited enhanced neural synchronization linking the right lateral hypothalamic effector zone to the right superior frontal gyrus (displaying a borderline significant correlation with peak LH concentrations), concurrent with diminished functional coupling of the right lateral hypothalamic efferent to the right fusiform/supramarginal gyri. The left lateral hypothalamic projections demonstrated amplified connectivity with the right cuneus. No FC differences were observed in the medial hypothalamus. Conclusion Abnormal lateral hypothalamus FC patterns were identified in CPP girls and were particularly linked to peak LH levels. The findings offer novel insights into the neuroendocrine mechanisms underlying CPP.

Background: Visceral white adipose tissue (vWAT) inflammation is a critical pathology of obesity-caused heart damage and is closely associated with adipocyte endoplasmic reticulum (ER) dysfunction. Serine (or cysteine) peptidase inhibitor, clade A, member 3C (Serpina3c) has been identified as an adipokine with anti-vWAT inflammatory effects. However, it remains unclear whether Serpina3c deficiency promotion of vWAT inflammation involves adipocyte ER dysfunction and whether it further contributes to heart damage in obesity. Methods: Wild type and Serpina3c knockout (Serpina3c–/–) mice were fed a high-fat diet (HFD) for 12 weeks. An adeno-associated virus (AAV) was injected locally into epididymal white adipose tissue (eWAT) of Serpina3c–/– mice to induce eWAT-adipocyte- specific overexpression of Serpina3c (AAV-Serpina3c) or knockdown of hypoxia-inducible factor 1α (AAV-shHIF1α). In vitro experiments were performed in 3T3-L1 adipocytes. Results: Serpina3c–/– mice exhibited more severe eWAT, serum and heart inflammation after HFD feeding. Consistently, these adverse phenotypes were mitigated in AAV-Serpina3c and AAV-shHIF1α mice. Mechanistically, ER oxidoreductase 1α (Ero1α) and protein disulfide isomerase (PDI) family members PDIA3 and PDIA4 were found to be target genes of HIF1α. In the obese mice, Serpina3c deficiency caused adipocyte more hypertrophy, and activated HIF1α-Ero1α/PDI mediated ER overoxidation and ER stress in eWAT. Subsequently, this led to increased adipocyte apoptosis and chemokine production and decreased adiponectin expression, which promoted macrophage infiltration and M1 polarization in eWAT, thus exacerbating eWAT inflammation and ultimately facilitating serum and distal heart inflammation. Conclusion These findings indicate that Serpina3c is a significant regulator of adipocyte ER redox homeostasis, thus highlighting Serpina3c as a potential therapeutic target for obesity-related eWAT inflammation and heart damage.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Objective To investigate the status of management of iodinated contrast media(ICM)extravasation in Henan Province,as well as nurses' knowledge and influencing factors,in order to provide a basis for optimizing management strategies.Methods A self-designed questionnaire was applied,employing convenience sampling,to survey nursing administrators and nurses in the radiology departments of 55 tertiary hospitals across 16 regions of Henan Province,from December 2024 to January 2025.Multiple linear regression analysis was conducted to explore the factors influencing nurses' knowledge.Results A total of 55 nursing administrators and 64 nurses participated,with a valid questionnaire response rate of 100％.The survey results reveal that only 5.45％of radiology depart-ments utilized high-pressure central venous catheters,and 32.73％employed vascular visualization techniques.When setting the high-pressure injection speed for ICM,only 54.55％of radiology departments required an assessment of the type and model of intravenous access.Additionally,only 9.09％of radiology departments mandated an observa-tion for 2 to 4 hours following ICM extravasation.Furthermore,only 50.91％of radiology departments had estab-lished an information system for ICM use.The nurses' knowledge score regarding the prevention and management of ICM extravasation was(90.00±17.59),influenced by years of experience in radiology and professional titles(P＜0.05).Conclusion The prevention and management measures for ICM in radiology departments in Henan Province need further improvement.Nursing administrators should optimize management strategies,improve relevant training systems,and continuously enhance nurses' knowledge and practical abilities.

Plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in the environment are important"fingerprint"nuclides in the study of nuclear activity traceability.The content of plutonium isotopes in the environmental metrics is usually very low,and the measurement of these isotopes,especially 238Pu,using mass spectrometry is seriously interfered with by the coexisting 238U.The analysis of several plutonium isotopes in soil usually requires combination of multiple measurement techniques,which leads to a long analysis time and large uncertainty in the isotope ratio.In this work,the hydrous titanium oxide(HTiO)precipitated by the hydrolysis of titanium oxydichloride(TiOCl2)under near-neutral condition was used to preconcentrate plutonium from the soil digestion solution,and the highly efficient decontamination of 238U in the sample was achieved by TK200 resin column chromatography with a decontamination factor of 108.Simulation resuts of density functional theory(DFT)showed that NH3 was considered as a promising reaction gas to eliminate the interference of 238U from 238Pu measurement using mass spectrometry due to the significant discrepancy of the chemical reactivity of U+and Pu+with the reactive gas NH3.Experiments confirmed that by optimizing the flow rates of collision gas(He)and reaction gas(NH3),the interference of 238U could be effectively suppressed,and the decontamination factor of 238U was 104.Combined with chemical separation,the overall decontamination factor of 238U could reach 1012 by using the developed method.By combining chemical separation and tandem quadrupole inductively coupled plasmon-mass spectrometry(ICP-MS/MS)measurement,the simultaneous determination of four ultra-trace plutonium isotopes in soil was realized,and the detection limit of plutonium isotopes was at the femtogram level.Analysis of the international standard reference materials(NIST-SRM-4357 and IAEA-384)showed that the established method could be successfully used for the accurate analysis of ultra-trace four plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in soil samples.

Background and aims:Primary sclerosing cholangitis(PSC)is an autoimmune liver disease characterized by complex pathogenesis and limited available therapeutic options.The mechanisms underlying the development and progression of PSCs remain unclear.Liver X receptor beta(LXR-β)is recognized to modulate lipid metabolism and immune response,but its specific involvement in the PSC has not been elucidated.Here,we explored the role and mechanism of LXR-β in PSC induced by 3,5-diethoxycarbonyl-1,4-dihydro-2,4,6-collidine(DDC).Methods:CRISPR-Cas9 technology was applied to generate Abcb4(coding MDR2,next named as Mdr2),Nr1h2(coding LXR-β,next named as Lxrβ),and Rag2(coding RAG2)knockout mice.DDC was used to induce PSC.Hematoxylin and eosin and Sirius red staining were used to assess the extent of hepatic injury and fibrosis.Flow cytometry was used to observe immune cell subsets.Results:We observed a declining trend in hepatic Lxrβ in the PSC model.Unexpectedly,Lxrβ knockout failed to modulate DDC-induced PSC pathogenesis.Concomitantly,assessment of the influence of Rag2 deficiency on PSC progression revealed the absence of aggravated or alleviated hepatic injury or fibrosis in the Rag2-/-DDC mice.However,Lxrβ depletion intensified DDC-induced PSC in the Rag2-/-mice,with more abundant infiltrative inflammatory cells and more severe liver fibrosis.Compared with Rag2-/-DDC mice,Lxrβ-/-Rag2-/-DDC mice had higher serum ALT and AST levels and mRNA expression of proinflammatory and profibrotic genes.Flow cytometry showed that LXR-β deficiency resulted in a diminished population of hepatic innate immune cells.Conclusion:This study indicated innate immune cell LXR-β deficiency can exacerbate hepatic injury and fibrosis in murine models of PSC suggesting that LXR-β may regulate the function of innate immunity in the fibrotic advancement of PSC.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Education is a crucial element in the development of acupuncture as a discipline, providing essential talent support for its future advancement. A structured interview was conducted with renowned acupuncture expert Professor ZHAO Jiping, focusing on key topics such as the core of acupuncture education, the connotation and development of acupuncture textbooks, and acupuncture teaching models. Through in-depth discussion, the current problems in acupuncture education were analyzed, and possible solutions were explored, aiming to offer ideas for the innovative development of acupuncture education.
Acupuncture/trends* ; Humans ; Acupuncture Therapy ; China