Cardiovascular diseases are the primary causes of mortality worldwide, often characterized by subtle onset and acute progression. Traditional ECG electrodes may cause skin irritation, limiting routine monitoring and early risk assessment. Relying on the advantages of non-contact monitoring, millimeter-wave radar-based cardiac monitoring combined with deep learning has become a popular research direction recently. To overcome the poor generalization of methods trained from single-source datasets, this study designed seven experimental scenarios covering wakefulness and sleep. A novel deep learning network consisting of encoder and decoder structures named PMG-SATNet was proposed. The encoder comprises a parallel multi-scale feature extraction module and a global temporal relationship modeling module to capture fine-grained local patterns and long-range dependencies. The decoder employs a temporal convolutional network augmented with a spectral attention mechanism to emphasize clinically relevant ECG frequency bands and suppress respiration and body motion interference. After being validated on the self-built dataset, PMG-SATNet outperformed baseline models in terms of Pearson correlation coefficient and root mean square error, with an improvement of 3.3% and 3.8%, and 16.4% and 23.8%, respectively. The validation results imply that PMG-SATNet is capable of recovering ECG signals from millimeter-wave radar-derived chest vibrations with high fidelity and can potentially be implemented in real-life cardiac health monitoring.

To elucidate the contributions of M-cone to the negative off-response of rat Electroretinogram (ERG) using specific drugs and spontaneous mutation rat models. The ON/OFF responses of ERG were evoked by long duration flash (200 ms) pre or post the application of 2-amino-4-phosphonobutyric acid (APB), cis-piperidine-2,3-dicarboxylic acid (PDA) or BaCl2 to the Sprague-Dawley (SD) rats. Furthermore, the ON/OFF responses of other two types of mutation rats, the middle-wavelength opsin cone dysfunction (MCD) rats and congenital stationary night blindness (CSNB) rats, were recorded. Typical scotopic and photopic ON/OFF responses were recorded in SD rats. At light offset, the OFF response showed a rapid negative deflection, then the retinal potential slowly returned to baseline from the trough of the negative off-response. The negative off-response was completely eliminated by the intravitreal injection of 400 µM APB. The amplitude of the negative off-response was reduced by the application of 5 mM PDA. However, the off component was not blocked by the application of 50 µM BaCl2. In addition, distinct differences of OFF response were found among MCD, CSNB and SD rats. The scotopic ON/OFF ERG of the MCD and CSNB rats showed no obvious negative off component at light offset, while the negative off component of photopic ON/OFF ERG was found in the CSNB rats, though with lower amplitude. The negative off-response of rat ERGs is not the off component of M-wave: a negative potential change at stimulus onset or offset. M-cone and the depolarizing bipolar cell play a central role in the signal transmission of this negative off-response.

Small-scale pedestrian detection is one of the challenges in general object detection. Factors such as complex backgrounds, long distances, and low-light conditions make the image features of small-scale pedestrians less distinct, further increasing the difficulty of detection. To address these challenges, an Enhanced Feature-Fusion YOLO network (EFF-YOLO) for small-scale pedestrian detection is proposed. Specifically, this method employs a backbone based on the FasterNet block within YOLOv8n, which is designed to enhance the extraction of spatial features while reducing redundant operation. Furthermore, the gather-and-distribute (GD) mechanism is integrated into the neck of the network to realize the aggregation and distribution of global information and multi-level features. This not only strengthens the faint features of small-scale pedestrians but also effectively suppresses complex background information, thereby improving the accuracy of small-scale pedestrians. Experimental results indicate that EFF-YOLO achieves detection accuracies of 72.5%, 72.3%, and 91% on the three public datasets COCO-person, CityPersons, and LLVIP, respectively. Moreover, the proposed method reaches a detection speed of 50.7 fps for 1920 × 1080-pixel video streams on the edge device Jetson Orin NX, marking a 15.2% improvement over the baseline network. Thus, the proposed EFF-YOLO method not only boasts high detection accuracy but also demonstrates excellent real-time performance on edge devices.

Accurate segmentation of thyroid nodules in ultrasound images is crucial for the diagnosis of thyroid cancer and preoperative planning. However, the segmentation of thyroid nodules is challenging due to their irregular shape, blurred boundary, and uneven echo texture. To address these challenges, a novel Mamba- and ResNet-based dual-branch network (MRDB) is proposed. Specifically, the visual state space block (VSSB) from Mamba and ResNet-34 are utilized to construct a dual encoder for extracting global semantics and local details, and establishing multi-dimensional feature connections. Meanwhile, an upsampling–convolution strategy is employed in the left decoder focusing on image size and detail reconstruction. A convolution–upsampling strategy is used in the right decoder to emphasize gradual feature refinement and recovery. To facilitate the interaction between local details and global context within the encoder and decoder, cross-skip connection is introduced. Additionally, a novel hybrid loss function is proposed to improve the boundary segmentation performance of thyroid nodules. Experimental results show that MRDB outperforms the state-of-the-art approaches with DSC of 90.02% and 80.6% on two public thyroid nodule datasets, TN3K and TNUI-2021, respectively. Furthermore, experiments on a third external dataset, DDTI, demonstrate that our method improves the DSC by 10.8% compared to baseline and exhibits good generalization to clinical small-scale thyroid nodule datasets. The proposed MRDB can effectively improve thyroid nodule segmentation accuracy and has great potential for clinical applications.

Electrical impedance tomography (EIT) can be used for real-time bedside monitoring of pathological changes in human brain tissue and dynamic imaging. However, EIT measurement signals are easily disturbed by noise, tremor in stroke patients, and other factors in clinical practice, which result in significant artifacts in the reconstructed images. These artifacts degrade the image quality and affect the detection of focal targets. To address this problem, we propose a multiscale 1-D residual convolutional network (MS-1DResCNN) to remove chaotic noise and interference from the conductivity distribution data and retain the target feature data, thereby improving the robustness of the reconstruction algorithm to noise and interference. The structural similarity (SSIM) and normalized mean square error (NMSE) were used to evaluate the performance of the proposed method in suppressing image reconstruction artifacts under noise-free conditions, different noise simulation levels, and varying vibration interference frequencies. The results of physical experiments showed that, under 10-Hz vibration interference, the reconstructed images using the MS-1DResCNN method improved the SSIM by 40.4%, 22.0%, 17.4%, and 11.7% and reduced the NMSE by 74.3%, 72.4%, 65.2%, and 29.5%, compared to the damped least squares (DLSs), artificial neural network (ANN), error-constraint network (Ec-Net), and U-Net methods, respectively. This method effectively improves the anti-interference ability of conditional algorithms, significantly reduces artifacts in EIT images, and makes the perturbation target clearer and more precise, thereby providing stable and reliable algorithmic support for the clinical application of EIT.

Radar is a valuable tool for noncontact vital-sign detection. Interference from respiratory harmonics presents a major challenge in radar cardiogram (RCG) extraction—mainly when the frequency of respiratory harmonics is close to or equal to that of the cardiac sub-signals. To address this problem, a respiratory harmonic suppression method employing correlation analysis and an optimized feedback notch filter is proposed, which is based on 7.29-GHz center-frequency impulse-radio ultra-wideband radar. A genetic optimization algorithm is employed to optimize the parameters of the notch filter. Performance comparison analysis is conducted on the conventional notch filter and the feedback notch filter. Contact (ECG) and non-contact (RCG) data from 10 subjects were analyzed. The results verified that the performance of the optimized feedback notch filter is much better than that of the conventional notch filter in overshoot, bandwidth, and notch depth, and the proposed method can effectively locate, identify, and suppress respiratory harmonics from the RCG band while preserving heartbeat components. Consequently, this approach markedly enhances the precision of RCG extraction. The technique shows considerable promise for deployment in diverse practical settings, including non-contact auxiliary monitoring systems in both intelligent medical environments and home healthcare.

JOURNAL/nrgr/04.03/01300535-202507000-00032/figure1/v/2024-09-09T124005Z/r/image-tiff A microgravity environment has been shown to cause ocular damage and affect visual acuity, but the underlying mechanisms remain unclear. Therefore, we established an animal model of weightlessness via tail suspension to examine the pathological changes and molecular mechanisms of retinal damage under microgravity. After 4 weeks of tail suspension, there were no notable alterations in retinal function and morphology, while after 8 weeks of tail suspension, significant reductions in retinal function were observed, and the outer nuclear layer was thinner, with abundant apoptotic cells. To investigate the mechanism underlying the degenerative changes that occurred in the outer nuclear layer of the retina, proteomics was used to analyze differentially expressed proteins in rat retinas after 8 weeks of tail suspension. The results showed that the expression levels of fibroblast growth factor 2 (also known as basic fibroblast growth factor) and glial fibrillary acidic protein, which are closely related to Müller cell activation, were significantly upregulated. In addition, Müller cell regeneration and Müller cell gliosis were observed after 4 and 8 weeks, respectively, of simulated weightlessness. These findings indicate that Müller cells play an important regulatory role in retinal outer nuclear layer degeneration during weightlessness.

目的:为了更好地提升神经电刺激的治疗效果,设计一种多模神经电刺激仪.方法:该刺激仪硬件由人机交互模块、主控单元和刺激脉冲生成模块3个部分组成.其中人机交互模块由按键输入电路和屏幕显示电路组成;主控单元选择STM32F407VET6高性能微控制器;刺激脉冲生成模块由升压电路、电极驱动电路、电极输出电路和断路监测电路组成.软件程序采用KeilC51编写,主要包括信号产生判断子程序、矩形波输出子程序和三角波/正弦波输出子程序.结果:该刺激仪能够产生与预期一致的刺激脉冲,具有稳定的波形输出特性和线性输出特性.结论:该刺激仪能够产生多种电刺激信号,且频率、幅值和脉冲宽度可调,可满足临床治疗需求.

如何早期有效筛查冠心病一直是航空医学面临的主要问题之一.笔者就目前外军常用冠心病早期筛查手段及策略进行分析,并与我军筛查体系进行比较,发现基于CT的冠状动脉钙化积分对未来心血管事件的风险预测优于功能学检查,指出利用风险分层算法对飞行人员进行差异性筛选可以显著提升筛查体系的效能,并强调了基于CT的血流储备分数和心肌核磁共振新筛查技术在飞行人员冠心病早期筛查中的应用前景.

目的 提出一种非接触辨识人与动物的生物雷达信号处理算法,以增强辨识准确性和鲁棒性.方法 采用中心频率7.29 GHz、带宽1.4 GHz的片上超宽带生物雷达系统采集人体与动物在自由空间条件下的雷达信号,经直流滤波、低通滤波、自适应滤波算法进行信号预处理后,从频率和能量角度提取增强型呼吸与心跳能量比特征.结果 人与动物辨识结果显示,与传统的呼吸与心跳能量比特征相比,本文所提的增强型呼吸与心跳能量比特征具有高准确率、高鲁棒性的特点,可以消除因个体差异而导致辨识误判的现象.结论 基于生物雷达信号提取的增强型呼吸与心跳能量比特征能更准确辨识人体和动物目标,该方法可作为非接触智能化健康监测设备的底层基础性技术,帮助其辨识目标,进而确保信号来源的准确性和可靠性,应用价值较高.

Introduction: Culturing cerebrovascular smooth muscle cells (CVSMCs) in vitro can provide a model for studying many cerebrovascular diseases. This study describes a convenient and efficient method to obtain mouse CVSMCs by enzyme digestion. Methods: Mouse circle of Willis was isolated, digested, and cultured with platelet-derived growth factor-BB (PDGF-BB) to promote CVSMC growth, and CVSMCs were identified by morphology, immunofluorescence analysis, and flow cytometry. The effect of PDGF-BB on vascular smooth muscle cell (VSMC) proliferation was evaluated by cell counting kit (CCK)-8 assay, morphological observations, Western blotting, and flow cytometry. Results: CVSMCs cultured in a PDGF-BB-free culture medium had a typical peak-to-valley growth pattern after approximately 14 days. Immunofluorescence staining and flow cytometry detected strong positive expression of the cell type-specific markers alpha-smooth muscle actin (α-SMA), smooth muscle myosin heavy chain 11 (SMMHC), smooth muscle protein 22 (SM22), calponin, and desmin. In the CCK-8 assay and Western blotting, cells incubated with PDGF-BB had significantly enhanced proliferation compared to those without PDGF-BB. Conclusion: We obtained highly purified VSMCs from the mouse circle of Willis using simple methods, providing experimental materials for studying the pathogenesis and treatment of neurovascular diseases in vitro. Moreover, the experimental efficiency improved with PDGF-BB, shortening the cell cultivation period.

We evaluated the effect of acute hypobaric hypoxia (AHH) on the hippocampal region of the brain in early-stage spontaneously hypertensive male rats. The rats were classified into a control (ground level; ~ 400 m altitude) group and an AHH experimental group placed in an animal hypobaric chamber at a simulated altitude of 5500 m for 24 h. RNA-Seq analysis of the brains and hippocampi showed that differentially expressed genes (DEGs) were primarily associated with ossification, fibrillar collagen trimer, and platelet-derived growth factor binding. The DEGs were classified into functional categories including general function prediction, translation, ribosomal structure and biogenesis, replication, recombination, and repair. Pathway enrichment analysis revealed that the DEGs were primarily associated with relaxin signaling, PI3K-Akt signaling, and amoebiasis pathways. Protein–protein interaction network analysis indicated that 48 DEGs were involved in both inflammation and energy metabolism. Further, we performed validation experiments to show that nine DEGs were closely associated with inflammation and energy metabolism, of which two ( Vegfa and Angpt2 ) and seven ( Acta2, Nfkbia, Col1a1, Edn1, Itga1, Ngfr , and Sgk1 ) genes showed up and downregulated expression, respectively. Collectively, these results indicated that inflammation and energy metabolism-associated gene expression in the hippocampus was altered in early-stage hypertension upon AHH exposure.

临床实习是医学专业本科学员获得岗位胜任力的关键环节.航空航天医学专业及相关医学岗位任职需求具有特殊性,对本科学员临床实习的教学管理工作提出了更高要求.该研究在介绍航空航天医学专业本科学员临床实习教学特殊性的基础上,通过分析空军军医大学在该专业本科学员临床实习教学管理中存在的问题,探讨改进措施,以提高临床实习教学水平及本科学员的岗位胜任力.

To explore the application of the space-time two-dimensional extended teaching in Circuit Principle.In the time dimension,depth classroom teaching is led by knowledge exploration based on problem orient,and in the space dimension,diversified combination of elements such as social hot spots,teaching modes,virtual reality information auxiliary technology,teacher-student interaction platform.Open assessment combined with standardized answer test,the whole teaching process pays attention to the academic evaluation of students'independent learning.Through two years of course teaching practice,teachers'teaching enthusiasm and students᾽competitiveness were significantly improved.This teaching method increases the attraction of classroom,teaching effect of Circuit Principle course was improved,and promoting the formation of high-quality personality of professional depth and thinking breadth.

BACKGROUND:Myocardial microvascular injury is the key event in early diabetic heart disease. The injury of myocardial microvascular endothelial cells (CMECs) is the main cause and trigger of myocardial microvascular disease. Mitochondrial calcium homeostasis plays an important role in maintaining the normal function, survival and death of endothelial cells. Considering that mitochondrial calcium uptake 1 (MICU1) is a key molecule in mitochondrial calcium regulation, this study aimed to investigate the role of MICU1 in CMECs and explore its underlying mechanisms.METHODS:To examine the role of endothelial MICU1 in diabetic cardiomyopathy (DCM), we used endothelial-specific MICU1ecKO mice to establish a diabetic mouse model and evaluate the cardiac function. In addition, MICU1 overexpression was conducted by injecting adeno-associated virus 9 carrying MICU1 (AAV9-MICU1). Transcriptome sequencing technology was used to explore underlying molecular mechanisms.RESULTS:Here, we found that MICU1 expression is decreased in CMECs of diabetic mice. Moreover, we demonstrated that endothelial cell MICU1 knockout exacerbated the levels of cardiac hypertrophy and interstitial myocardial fibrosis and led to a further reduction in left ventricular function in diabetic mice. Notably, we found that AAV9-MICU1 specifically upregulated the expression of MICU1 in CMECs of diabetic mice, which inhibited nitrification stress, inflammatory reaction, and apoptosis of the CMECs, ameliorated myocardial hypertrophy and fibrosis, and promoted cardiac function. Further mechanistic analysis suggested that MICU1 deficiency result in excessive mitochondrial calcium uptake and homeostasis imbalance which caused nitrification stress-induced endothelial damage and inflammation that disrupted myocardial microvascular endothelial barrier function and ultimately promoted DCM progression.CONCLUSIONS:Our findings demonstrate that MICU1 expression was downregulated in the CMECs of diabetic mice. Overexpression of endothelial MICU1 reduced nitrification stress induced apoptosis and inflammation by inhibiting mitochondrial calcium uptake, which improved myocardial microvascular function and inhibited DCM progression. Our findings suggest that endothelial MICU1 is a molecular intervention target for the potential treatment of DCM.

航空医疗救援是借助航空器作为交通工具,运用医学手段救助受困对象的活动,在救灾救援任务中发挥着举足轻重的作用.本文主要探讨了航空医疗救援活动中,航空特殊环境的特点及可能带来的危害;常见危重疾病的机上救治和护理要点.这有助于减少因医疗操作不当造成的损伤,从而使航空医疗救援活动安全、有序、高效地展开.

为了探索解决医学院校背景下生物医学工程专业本科电工电子类专业基础课程教学中长期存在的"注重工科基础、弱化医工理念"问题,以空军军医大学生物医学工程专业"电路原理"课程教学为研究对象,分析"电路原理"课程教学中存在的问题与不足,分别从课程教学内容整合、项目化教学内容的制定与实施、补充性实验教材建设三方面进行改革,使课程教学内容得到了全面性、系统性的完善.项目化教学的开展,有望实现"医工"特色教学,为医学院校背景下的军事生物医学工程电工电子类专业基础课程的教学改革提供有意义的借鉴和参考.

哌托生特作为一种组胺H3受体拮抗剂/反向激动剂,其明确的促觉醒作用以及低药物依赖性使其迅速成为欧美治疗成人发作性睡病的一线用药.本文通过总结组胺H3受体分布及作用特点,阐明了哌托生特的作用靶点及其产生的相关效应;并通过总结哌托生特的药物化学特点以及将其与常见抗疲劳药物成瘾性之间进行对比,展望了哌托生特在特殊环境/条件下的应用潜能.本文为哌托生特在我国特殊环境/条件下,如军事、轮班、紧急任务等方面的合理化应用提供了理论依据.

目的 探究服用10 mg扎来普隆对主观视觉功能的影响,评估服药后的安全放飞时间.方法 15名健康男性被试者,采用双盲、单模拟和自身交叉对照研究方法,交叉服用10 mg扎来普隆和安慰剂(前后相隔3 d),服药后被试者均给予了 2.5 h的睡眠时间,于服药3、4、5 h后分别进行一次主观视觉功能评估.评估内容包括视力、主观快速暗适应、夜间视力、对比敏感度、立体视觉以及临界闪光融合频率.结果 服药3 h后扎来普隆组和安慰剂组0.6 c/d空间频率下对比敏感度为(15.49±2.92)dB vs(16.51±2.03)dB(P=0.035),差异虽有统计学意义,但其结果仍在正常范围内,扎来普隆并未导致该服药时段对比敏感度异常.服药5h后主观暗适应时间为(3.63±0.85)s vs(4.37±1.14)s(P=0.038),服用扎来普隆缩短了暗适应时间;服药后3、4、5 h扎来普隆组和安慰剂组的左、右眼视力,主观暗适应、夜间视力,对比敏感度、立体视觉以及临界闪光融合频率指标均无统计学差异(P＞0.05).结论 服用10 mg扎来普隆自服药3 h起对主观视觉功能无不良影响.

目的:探索"两性一度"标准下的项目驱动式教学法在信号与系统课程中的实践应用.方法:结合学校专业实际情况,立足学科优势和科研前沿,基于生物雷达基带信号的MATLAB计算仿真开展项目驱动式教学,以学员为中心有机结合选题、课外自学与课堂教学,通过讲授项目背景、现场实物展示、演示仿真方法、师生互动讨论、课下知识拓展等教学方法进行信号与系统实践教学.结果:采用该教学模式可有效提高学员的自主学习能力和学习效果,对教员教学水平的提高也有重要的促进作用.结论:采用该教学方法可以有效提高信号与系统课程的教学效果,为"两性一度"教学改革研究提供了参考.