BACKGROUND:Many recent studies have shown a close relationship between inflammatory cytokines and osteoporosis and bone mineral density(BMD).However,the causal relationship between inflammatory cytokines and BMD has not been fully revealed. OBJECTIVE:To explore the potential causal relationship between inflammatory cytokines and BMD using a two-sample Mendelian randomization analysis. METHODS:The single nucleotide polymorphisms associated with 41 circulating inflammatory cytokines were selected from the open database of genome-wide association studies(GWAS)as instrumental variables.The GWAS data about BMD were from the Genetic Factors for Osteoporosis Consortium,involving a total of 32 735 individuals of European ancestry.Inverse variance weighting was used as the primary analysis to evaluate the causal effect.Weighted median,MR Egger regression,simple mode,and weighted mode methods were used to supplement the explanation.We used the MR-Egger intercept and MR-PRESSO method to conduct a pleiotropy test,the Cochran's Q test was used to determine whether there was heterogeneity in the results,and the leave-one-out method was used to evaluate the stability of the results.In addition,to more accurately assess the causality,the Bonferroni-corrected test was used to identify inflammatory cytokines that have a strong causal relationship with BMD. RESULTS AND CONCLUSION:(1)According to the results of the inverse variance weighting method,we found a positive causal relationship between interleukin-8 and lumbar spine BMD[β=0.075,95%confidence interval(CI):0.033-0.117,P=0.000 5),while a negative causal relationship between interleukin-17 and lumbar spine BMD(β=-0.083,95%CI:-0.152 to-0.014,P=0.018).There might be a negative causal relationship between tumor necrosis factor b and femoral neck BMD(β=-0.053,95%CI:-0.088 to-0.018,P=0.003),while a positive causal relationship between basic fibroblast growth factor and femoral neck BMD(β=0.085,95%CI:0.016-0.154,P=0.015).There might be a negative causal relationship between macrophage inflammatory protein-1a and total body BMD(β=-0.056,95%CI:-0.105 to-0.007,P=0.025).There was a negative causal relationship between interleukin-5(β=-0.019,95%CI:-0.031 to-0.006,P=0.004),stromal cell-derived factor-1a(β=-0.022,95%CI:-0.038 to-0.005,P=0.010),hepatocyte growth factor(β=-0.021,95%CI:-0.041 to-0.002,P=0.030),interleukin-4(β=-0.016,95%CI:-0.032 to-0.001,P=0.034)and heel BMD,while a positive causal relationship between nerve growth factor(β=0.019,95%CI:0.002-0.036,P=0.033),granulocyte colony-stimulating factor(β=0.011,95%CI:0.000-0.022,P=0.050),and heel BMD.Meanwhile,after the Bonferroni-corrected test,there was a strong positive causal effect between interleukin-8 and lumbar spine BMD(P=0.000 5).And consistent directional effects for all analyses were observed in MR Egger,weighted median,simple mode,and weighted mode methods.(2)Sensitivity analyses revealed no heterogeneity,pleiotropy,or outliers for the causal effect of circulating inflammatory cytokines on BMD.

To explore the effects of different exercise prescriptions on glycemic metabolism in East Asian patients with type 2 diabetes mellitus (T2DM) and to compare the differences in the impact of population characteristics and exercise components on glycemic metabolism.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

Objective To improve the efficiency and accuracy of videonystagmography calibration test results while enabling effective recognition of saccadic undershoot waveform by developing a dual-stream architecture-based deep learning model. Methods A vestibular function calibration test recognition model with cross-modal feature fusion was constructed by integrating vision transformer (ViT) and a modified ConvNeXt convolutional network. The model utilized trajectory pictures and spatial distribution maps as inputs, employed a multi-task learning framework to classify calibration data, and to directly evaluate undershoot waveform. Results The model showed outstanding performance in assessing calibration compliance. The accuracy, sensitivity, specificity of the model in left side, middle, and right side were all greater than 90%, and AUC values were all greater than 0.99, with 97.66% of optimal accuracy (middle), 98.98% of optimal sensitivity (middle), 96.87% of optimal specificity (right side), and 0.997 of AUC (right side). The model also showed promising performance in undershoot waveform recognition with 87.50% of accuracy, 89.66% of sensitivity, 85.71% of specificity, 86.67% of F1 score, and 0.931 of AUC. Conclusions The proposed method not only significantly enhances the efficiency and accuracy of calibration test results, but also provides a novel solution for undershoot waveform recognition.

Autism spectrum disorder in children (hereinafter called "childhood autism") is a prevalent neurodevelopmental condition; however, ancient Chinese medical texts did not provide detailed accounts of it. The concept of "the sovereign fire illuminates, while the ministerial fire occupies its position" was first introduced in the Plain Questions: The Great Treatise on the Origin of Heavenly Influences chapter. Subsequent medical practitioners have elaborated on this idea, identifying the sovereign fire as the master of the spirit and governing life activities, while the ministerial fire is the assisting minister that supports the functions of the zang-fu organs. When these two are in harmony, they complement each other, collectively sustaining the body′s normal physiological functions. In the context of this theory, the pathogenesis of childhood autism is attributed to the imbalance between the sovereign and ministerial fires. The root cause lies in the mutual antagonism of these two fires, resulting in the dysfunction of the spirit. Central to childhood autism onset is the dimming of the sovereign fire and a deficiency in the spirit, while the displacement of the ministerial fire and the impaired function of the five viscera contribute significantly to the progression of the condition. Effective treatment for childhood autism involves restoring these imbalances: dispelling yin-related obstructions to illuminate the sovereign fire, nourishing the spleen and kidney to nourish the ministerial fire, and regulating the liver and lung to harmonize the sovereign and ministerial fires. The ultimate goal is to integrate body and spirit, harmonize the sovereign and ministerial fires, and restore the interconnectedness between spirit and the function of the five zang viscera. This article, based on the "the sovereign fire illuminates, while the ministerial fire occupies its position" theory, provides a novel perspective and insights for understanding and treating childhood autism through the holistic principles of traditional Chinese medicine. Emphasizing the integration of body and spirit offers new insights and approaches for the clinical management of childhood autism in traditional Chinese medicine.

ObjectiveBola-like short peptides exhibit novel self-assembly properties due to the formation of peptide dimers via hydrogen bonding interactions between their C-terminals. In this configuration, hydrophilic amino acids are distributed at both terminals, making these peptides behave similarly to Bola peptides. The electrostatic repulsive interactions arising from the hydrophilic amino acids at each terminal can be neutralized, thereby greatly promoting the lateral association of β-sheets. Consequently, assemblies with significantly larger widths are typically the dominant nanostructures for Bola-like peptides. To investigate the effect of hydrophilic amino acids on the self-assembly behavior of Bola-like peptides, the peptides Ac-RI₃-CONH₂ and Ac-HI₃-CONH₂ were designed and synthesized using the Bola-like peptide Ac-KI₃-CONH₂ as a template. Their self-assembly behavior was systematically examined. MethodsAtomic force microscopy (AFM) and transmission electron microscopy (TEM) were employed to characterize the morphology and size of the assemblies. The secondary structures of the assemblies were analyzed using circular dichroism (CD) and Fourier transform infrared (FTIR) spectroscopy. Small-angle neutron scattering (SANS) was used to obtain detailed structural information at a short-length scale. Based on these experimental results, the effects of hydrophilic amino acids on the self-assembly behavior of Bola-like short peptides were systematically analyzed, and the underlying formation mechanism was explored. ResultsThe aggregation process primarily involved three steps. First, peptide dimers were formed through hydrogen bonding interactions between their C-terminals. Within these dimers, the hydrophilic amino acids K, R, and H were positioned at both terminals, enabling the peptides to self-assemble in a manner similar to Bola peptides. Next, β-sheets were formed via hydrogen bonding interactions along the peptide backbone. Finally, self-assemblies were generated through the lateral association of β-sheets. The results demonstrated that both Ac-KI₃-CONH₂ and Ac-RI₃-CONH₂ could self-assemble into double-layer nanotubes with diameters of approximately 200 nm. These nanotubes were formed by the edge fusion of helical ribbons, which initially emerged from twisted ribbons. Notably, the primary assemblies of these peptides exhibited opposite chirality: nanofibers formed by Ac-KI₃-CONH₂ displayed left-handed chirality, whereas those formed by Ac-RI₃-CONH₂ exhibited right-handed chirality. This reversal in torsional direction was primarily attributed to the different abilities of K and R to form hydrogen bonds with water. In contrast, Ac-HI₃-CONH₂ formed narrower twisted ribbons with a significantly reduced width of approximately 30 nm, which was attributed to the strong steric hindrance caused by the imidazole rings. The multilayer height of these ribbons was mainly due to the unique structure of the imidazole rings, which can function as both hydrogen bond donors and acceptors, thereby promoting aggregate growth in the vertical direction. ConclusionThe final morphology of the self-assemblies resulted from a delicate balance of various non-covalent interactions. By altering the types of hydrophilic amino acid residues in Bola-like short peptides, the relative strength of non-covalent interactions that drive assembly formation can be effectively regulated, allowing precise control over the morphology and chirality of the assemblies. This study provides a simple and effective approach for constructing diverse self-assemblies and lays a theoretical foundation for the development of functional biomaterials.

To explore the correlation between human body fat distribution and carotid athero-sclerosis.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.