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Development and validation of automated methods for COVID-19 PCR Master Mix preparation 开发并验证 COVID-19 PCR Master Mix 的自动制备方法。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-10-01 DOI: 10.1016/j.slast.2024.100195
Polymerase chain reaction (PCR)-based assays were widely deployed during the SARS-CoV-2 pandemic for population-scale testing. High-throughput molecular diagnostic laboratories required a high degree of process automation to cope with huge testing demands, fast turnaround times, and quality requirements. However, process developers and optimizers often neglected the critical step of preparing a PCR Master Mix. The construction of PCR Master Mix depends on operator skill during the manual pipetting of reagents. Manual procedures introduce variation, inconsistency, wastage, and potentially risks data integrity. To address this, we developed a liquid-handler-based solution for automated, traceable, and compliant PCR Master Mix preparation. Here, we show that a fully automated PCR Master Mix protocol can replace manual pipetting, even in a diagnostic environment, without affecting accuracy or precision. Ultimately, this method eliminated operator-induced wastage and improved the consistency of the quality of results.
在 SARS-CoV-2 大流行期间,基于聚合酶链反应(PCR)的检测方法被广泛用于人群规模的检测。高通量分子诊断实验室需要高度的流程自动化,以应对巨大的检测需求、快速的周转时间和质量要求。然而,流程开发人员和优化人员往往忽略了制备 PCR 混合母液这一关键步骤。PCR 混合母液的构建依赖于操作员手动移取试剂的技能。手工操作会带来差异、不一致性和浪费,并可能危及数据完整性。为了解决这个问题,我们开发了一种基于液体处理器的解决方案,用于自动、可追溯且符合要求的 PCR 混合母液制备。在这里,我们展示了全自动 PCR 混合母液制备方案可以取代人工移液,即使在诊断环境中也不会影响准确性或精确度。最终,这种方法消除了操作人员造成的浪费,提高了结果质量的一致性。
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引用次数: 0
Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease 基于人工智能后处理的糖尿病和冠心病患者冠状动脉病变的分流量保留评分探讨
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-21 DOI: 10.1016/j.slast.2024.100196
In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reservation (FFR) in patients with different levels of CHD and diabetes, this paper used AI (artificial intelligence) post-processing technology to detect CHD and FFR. In this paper, 94 patients suspected of CHD who underwent coronary arteriography (CAG) in a hospital between December 2022 and February 2023 were examined by coronary computed tomography angiography (CCTA) and FFR. Based on CCTA, AI software is used to process CCTA images, diagnose coronary plaques, coronary stenosis, corresponding stenosis of different types of plaques, and FFR values. The diagnostic performance of AI was evaluated using expert diagnosis, CAG diagnosis, and FFR examination results as the “gold standard”. According to the diagnosis results, the relationship between FFR and CHD patients with diabetes at different levels was studied. The research results showed that AI image diagnosis has high sensitivity, specificity, and accuracy, and has good diagnostic effects on coronary plaques, coronary stenosis, stenosis corresponding to different types of plaques, and FFR values. The fasting blood glucose levels and FFR values of three groups of CHD patients were statistically significant, and correlation analysis revealed a negative correlation between the two. Using AI for CCTA diagnosis can efficiently, conveniently, and accurately obtain the required data, improving clinical diagnostic efficiency and accuracy. The analysis of AI recognition results found that in patients with CHD, the FFR value of patients with diabetes decreased, and the FFR value was negatively correlated with the fasting blood glucose concentration, indicating that CHD patients may lead to myocardial ischemia in the blood supply area due to the decline of their coronary blood flow reserve.
以专家诊断结果为 "金标准",评价人工智能识别冠状动脉斑块的有效性;以CAG结果为 "金标准",评价人工智能识别CAS的有效性;以专家诊断和CAG结果为 "金标准",评价人工智能识别不同类型斑块对应的狭窄的有效性;以FFR测量结果为 "金标准",评价人工智能识别心肌缺血的有效性。在上述诊断结果的基础上,研究了FFR与糖尿病合并冠心病患者冠心病差异之间的关系,并探讨了FFR与冠心病差异之间的相关性。
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引用次数: 0
CardioGuard: AI-driven ECG authentication hybrid neural network for predictive health monitoring in telehealth systems CardioGuard:用于远程医疗系统中预测性健康监测的人工智能驱动心电图验证混合神经网络。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-20 DOI: 10.1016/j.slast.2024.100193
The increasing integration of telehealth systems underscores the importance of robust and secure methods for patient data management. Traditional authentication methods, such as passwords and PINs, are prone to breaches, underscoring the need for more secure alternatives. Therefore, there is a need for alternative approaches that provide enhanced security and user convenience. Biometric-based authentication systems uses individuals unique physical or behavioral characteristics for identification, have emerged as a promising solution. Specifically, Electrocardiogram (ECG) signals have gained attention among various biometric modalities due to their uniqueness, stability, and non-invasiveness. This paper presents CardioGaurd, a deep learning-based authentication system that leverages ECG signals—unique, stable, and non-invasive biometric markers. The proposed system uses a hybrid Convolution and Long short-term memory based model to obtain rich characteristics from the ECG signal and classify it as authentic or fake. CardioGaurd not only ensures secure access but also serves as a predictive tool by analyzing ECG patterns that could indicate early signs of cardiovascular abnormalities. This dual functionality enhances patient security and contributes to AI-driven disease prevention and early detection. Our results demonstrate that CardioGaurd offers superior performance in both security and potential predictive health insights compared to traditional models, thus supporting a shift towards more proactive and personalized telehealth solutions.
远程医疗系统的集成度越来越高,这凸显了采用稳健安全的方法管理患者数据的重要性。密码和 PIN 码等传统身份验证方法很容易被破解,因此需要更安全的替代方法。因此,需要能提供更高的安全性和用户便利性的替代方法。基于生物特征的身份验证系统利用个人独特的身体或行为特征进行身份验证,已成为一种很有前途的解决方案。具体来说,心电图(ECG)信号因其独特性、稳定性和非侵入性,在各种生物识别模式中备受关注。本文介绍的 CardioGaurd 是一种基于深度学习的身份验证系统,它利用了心电信号--独特、稳定和非侵入性的生物识别标记。该系统采用基于卷积和长短期记忆的混合模型,从心电图信号中获取丰富的特征,并对其进行真假分类。CardioGaurd 不仅能确保安全访问,还能通过分析可能预示心血管异常早期迹象的心电图模式作为预测工具。这种双重功能增强了患者的安全性,并有助于人工智能驱动的疾病预防和早期检测。我们的研究结果表明,与传统模式相比,CardioGaurd 在安全性和潜在的预测性健康洞察力方面都表现出色,从而支持向更加主动和个性化的远程医疗解决方案转变。
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引用次数: 0
Pathological correlation between eosinophils and thyroid nodules based on medical image testing 基于医学影像检测的嗜酸性粒细胞与甲状腺结节的病理相关性。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-19 DOI: 10.1016/j.slast.2024.100189
Thyroid nodule is a common thyroid disease, but the study of its pathology and pathogenesis is still limited. As a non-invasive diagnostic method, medical image examination is of great value to study the pathological correlation of thyroid nodules. The purpose of this study was to investigate the expression of eosinophils in medical image examination and the pathological correlation between eosinophils and thyroid nodules. The study analyzed the pathological reports of a group of patients with thyroid nodules examined by medical images and performed corresponding imaging scans or examinations. The imaging data is processed, including image reconstruction, data transmission and other steps, to generate images that can be diagnosed by doctors. Thyroid function and parameters of leukocyte were collected and compared.The serum levels of TT4 and fT4 were observed lower in G2 group, while thyroid stimulating hormone (TSH) was higher compared to G1 group before surgery. Compared to G2 group, eosinophils count and percentage were lower in G1group (p < 0.05) post-surgery and lower ratio of eosinophils count with lymphocyte count (ELR) were observed in G1 group patients (p < 0.05).Elevated TSH is closely related to malignant TN per surgery, while lower ELR suggesting that TN removed thoroughly. Relevant cut-off values required further study to guide the diagnosis, treatment and follow-up of TN.
甲状腺结节是一种常见的甲状腺疾病,但对其病理和发病机制的研究还很有限。医学影像检查作为一种无创诊断方法,对研究甲状腺结节的病理相关性具有重要价值。本研究旨在探讨嗜酸性粒细胞在医学影像检查中的表达以及嗜酸性粒细胞与甲状腺结节的病理相关性。研究分析了一组通过医学影像检查的甲状腺结节患者的病理报告,并进行了相应的成像扫描或检查。成像数据经过处理,包括图像重建、数据传输和其他步骤,生成可供医生诊断的图像。收集甲状腺功能和白细胞参数并进行比较。术前观察发现,G2 组的血清 TT4 和 fT4 水平较低,而促甲状腺激素(TSH)较 G1 组高。与 G2 组相比,G1 组的嗜酸性粒细胞计数和百分比较低(P<0.05)。
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引用次数: 0
Editorial: Advances in Precise Diagnostics and Personalized Medicine 社论:精确诊断和个性化医疗的进展。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-18 DOI: 10.1016/j.slast.2024.100194
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引用次数: 0
Connexin 43 controls metastatic behavior in triple negative breast cancer through TGFβ1-Smad3-intergin αV signaling axis Based on optical image diagnosis 连接蛋白 43 通过 TGFβ1-Smad3 介导的 αV 信号轴控制三阴性乳腺癌的转移行为 基于光学图像诊断的研究
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-17 DOI: 10.1016/j.slast.2024.100190

Abnormal expression of connexin 43 (Cx43) contributes to the development and progression of cancer. However, its regulation is complex and dependent on the environment. The expression of Cx43 in triple-negative cancer lesions was analyzed by immunohistochemistry and optical coherence tomography using experimental models and clinical samples. The model of TGFβ1-SMad3-in-αv signal axis was established and verified by experiments. The results show that Cx43 plays a key role in the regulation of triple-negative cancer metastasis. In vivo, over-expressed Cx43 decreased tumor volume and inhibited ITGαV, TGF-β1, Smad3 and N-cadherin expressions, but enhanced the E-cadherin. Cx43 had the lowest expression in the TNBC samples, especially in lymph node metastatic TNBC patients and had a negative correlation with ITG alpha V, TGF-β1 and Smad3.The study demonstrated Cx43 controlled metastatic behavior through TGF-β1 -Smad3-ITG αV signaling axis in MDA-MB-231 cells, providing evidence for Cx43’s function in TNBC. The optical image diagnosis method can realize the identification and quantitative evaluation of early cancer triple negative, and provide a new strategy and means for the treatment of cancer triple negative.

附件蛋白 43(Cx43)的异常表达会导致癌症的发生和发展。然而,对它的调控是复杂的,并依赖于环境。研究人员利用实验模型和临床样本,通过免疫组化和光学相干断层扫描分析了三阴性癌症病灶中 Cx43 的表达情况。建立了TGFβ1-SMad3-in-αv信号轴模型并进行了实验验证。结果表明,Cx43在调控三阴性癌转移中起着关键作用。在体内,过度表达Cx43可减少肿瘤体积,抑制ITGαV、TGF-β1、Smad3和N-cadherin的表达,但增强E-cadherin的表达。研究表明,Cx43通过TGF-β1-Smad3-ITG αV信号轴控制MDA-MB-231细胞的转移行为,为Cx43在TNBC中的功能提供了证据。该光学图像诊断方法可实现早期三阴性癌的鉴定和定量评估,为三阴性癌的治疗提供新的策略和手段。
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引用次数: 0
Optical MRI imaging based on computer vision for extracting and analyzing morphological features of renal tumors 基于计算机视觉的光学磁共振成像,用于提取和分析肾肿瘤的形态特征。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-16 DOI: 10.1016/j.slast.2024.100192

Computer vision technology is more and more widely used in the market. Target detection and feature extraction are two important auxiliary means of this technique, which are helpful to analyze target motion data. However, in the field of biology, there are some data limitations in the analysis of targets such as bacteria and tumors, which need to be further explored. Optical MRI imaging technology based on computer vision provides a new way to extract and analyze morphological features of renal tumors. In this paper, an optical MRI imaging method based on computer vision is designed and developed for the extraction and analysis of morphological features of kidney tumors. By using optical MRI imaging technology based on computer vision, the morphological characteristics of kidney tumors were extracted by analyzing the optical characteristics and MRI images of kidney tumors, and a simulation model was established to simulate the morphological characteristics of different types of kidney tumors, and feature extraction and analysis were carried out by computer algorithm. Through the analysis of the simulation model, the morphological characteristics of renal tumors were extracted and analyzed, which provided a new and non-invasive method for clinical diagnosis and treatment of renal tumors.

计算机视觉技术在市场上的应用越来越广泛。目标检测和特征提取是该技术的两种重要辅助手段,有助于分析目标运动数据。然而,在生物学领域,对细菌和肿瘤等目标的分析还存在一些数据限制,需要进一步探索。基于计算机视觉的光学核磁共振成像技术为提取和分析肾脏肿瘤的形态特征提供了一种新方法。本文设计并开发了一种基于计算机视觉的光学核磁共振成像方法,用于提取和分析肾脏肿瘤的形态特征。利用基于计算机视觉的光学核磁共振成像技术,通过分析肾脏肿瘤的光学特征和核磁共振图像,提取肾脏肿瘤的形态学特征,并建立仿真模型模拟不同类型肾脏肿瘤的形态学特征,利用计算机算法进行特征提取和分析。通过对模拟模型的分析,提取并分析了肾脏肿瘤的形态学特征,为肾脏肿瘤的临床诊断和治疗提供了一种无创的新方法。
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引用次数: 0
Experience in the diagnosis and treatment of non-invasive bilateral carotid cavernous sinus fistula based on CT image examination 根据 CT 图像检查诊断和治疗无创双侧颈动脉海绵窦瘘的经验。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-16 DOI: 10.1016/j.slast.2024.100191

Carotid cavernous fistula is a rare but clinically important vascular abnormality that is challenging to diagnose and treat. The clinical data of a patient with bilateral carotid cavernous fistula diagnosed by CT images were retrospectively analyzed. Through the analysis of CT images, the patient was accurately located and the diagnosis was confirmed. CT images can provide detailed anatomical information and accurately show the location, morphology and hemodynamic characteristics of carotid cavernous fistula. Through CT image examination, we successfully diagnosed bilateral carotid cavernous fistula patients, and can provide an important reference for surgical treatment. Therefore, CT image examination can provide accurate diagnosis and surgical planning information, and provide support for the formulation of individual treatment plans for patients. The application of this method is helpful to improve the early diagnosis rate and treatment effect of carotid cavernous fistula.

颈动脉海绵瘘是一种罕见但在临床上非常重要的血管异常,诊断和治疗都很困难。本文回顾性分析了一名通过 CT 图像诊断为双侧颈动脉海绵瘘患者的临床资料。通过对 CT 图像的分析,对患者进行了准确定位并确诊。CT 图像能提供详细的解剖信息,准确显示颈动脉海绵瘘的位置、形态和血流动力学特征。通过CT图像检查,我们成功确诊了双侧颈动脉海绵瘘患者,为手术治疗提供了重要参考。因此,CT 图像检查可以为患者提供准确的诊断和手术方案信息,为患者制定个性化治疗方案提供支持。该方法的应用有助于提高颈动脉海绵瘘的早期诊断率和治疗效果。
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引用次数: 0
Life sciences discovery and technology highlights 生命科学发现与技术亮点。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-09-13 DOI: 10.1016/j.slast.2024.100188
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引用次数: 0
Breast cancer promotes the expression of neurotransmitter receptor related gene groups and image simulation of prognosis model 乳腺癌促进神经递质受体相关基因组的表达及预后模型的图像模拟。
IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Pub Date : 2024-08-31 DOI: 10.1016/j.slast.2024.100183

Breast cancer (BC), a prevalent and severe malignancy, detrimentally affects women globally. Its prognostic implications are profoundly influenced by gene expression patterns. This study retrieved 509 BCE-associated oncogenes and 1,012 neurotransmitter receptor-related genes from the GSEA and KEGG databases, intersecting to identify 98 relevant genes. Clinical and transcriptomic expression data related to BC were downloaded from the TCGA, and differential genes were identified based on an FDR value <0.05 & |log2FC| ≥ 0.585. Univariate analysis of these genes revealed that high expression of NSF and low expression of HRAS, KIF17, and RPS6KA1 are closely associated with BC survival prognosis. A prognostic model constructed for these four genes demonstrated significant prognostic relevance for BC-TCGA patients (P < 0.001). Subsequently, an immunofunctional analysis of the BC oncogene-neurotransmitter receptor-related gene cluster revealed the involvement of immune cells such as T cells CD8, T cells CD4 memory resting, and Macrophages M2. Further analysis indicated that immune functions were primarily concentrated in APC_co_inhibition, APC_co_stimulation, CCR, and Check-point, among others. Lastly, a prognostic nomogram model was established, and ROC curve analysis revealed that the nomogram is a vital indicator for assessing BC prognosis, with 1-year, 3-year, and 5-year survival rates of 0.981, 0.897, and 0.802, respectively. This model demonstrates high calibration, clinical utility, and predictive capability, promising to offer an effective preliminary tool for clinical diagnostics.

乳腺癌(BC)是一种普遍存在的严重恶性肿瘤,对全球妇女造成了严重影响。其预后受到基因表达模式的深刻影响。本研究从 GSEA 和 KEGG 数据库中检索了 509 个与 BC 相关的癌基因和 1,012 个神经递质受体相关基因,通过交叉分析确定了 98 个相关基因。从 TCGA 下载了与 BC 相关的临床和转录组表达数据,并根据 FDR 值确定了差异基因。
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引用次数: 0
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