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Single-step purification and formulation of antibody-drug conjugates using a miniaturized tangential flow filtration system 使用小型切向流过滤系统的抗体-药物偶联物单步纯化和配方

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-09-19 DOI: 10.1016/j.slast.2025.100351

Muhammad Sajed , Zahoor Khan , Muhammad Usman Ashraf , Hafsa Iftikhar , Talha Bin Rahat , Samia Falak , Salman Fozail , Quiterie Gue , Raul Pardo , Lance Ramsey , Muhammad Saqib Shahzad

Antibody-drug conjugates (ADCs) are a promising therapeutic modality that enables the delivery of cytotoxic drugs to the target cells that express the corresponding antigen. However, the purification of ADCs while ensuring product safety, homogeneity, and stability is a challenging task due to their complex and fragile structure. Size exclusion chromatography (SEC), the conventional method for ADC purification, is time-consuming as it requires multiple column washes and equilibration steps. Moreover, subsequent formulation of ADCs, typically using dead-end filtration (DEF), further complicates the production workflow. We compared SEC+DEF with the µPulse®, a miniaturized and automated tangential flow filtration system, for purification and formulation of ADCs. Quality analysis revealed that both approaches were equally gentle as comparable drug-to-antibody ratios (DARs) and monomer purities were observed in the purified samples. Most importantly, both methods exhibited equivalent cleanup efficiency with a 99.8% reduction in free linker-drug concentration. The endotoxin loads comprised 0.11 EU mg^-1 for the µPulse and 0.07 EU mg^-1 for SEC+DEF, ensuring validation of the safe application of purified ADCs in living systems. However, the µPulse performed purification and formulation of ADCs simultaneously as compared to SEC+DEF, which required multiple manual interventions. Our results indicate that the µPulse is a gentle, single-step, and walk-away approach for the purification of ADCs.

抗体-药物偶联物（adc）是一种很有前途的治疗方式，可以将细胞毒性药物传递到表达相应抗原的靶细胞。然而，由于adc结构复杂和脆弱，在保证产品安全性、均匀性和稳定性的同时进行纯化是一项具有挑战性的任务。粒径排除色谱法（SEC）是ADC的常规纯化方法，由于需要多次清洗柱和平衡步骤，因此非常耗时。此外，adc的后续配方通常使用终端过滤（DEF），这进一步复杂化了生产流程。我们将SEC+DEF与µPulse®进行了比较，µPulse®是一种小型化、自动化的切向流过滤系统，用于adc的纯化和配方。质量分析表明，这两种方法都同样温和，因为在纯化的样品中观察到类似的药物-抗体比率（dar）和单体纯度。最重要的是，两种方法的清除效率相当，游离连接剂浓度降低99.8%。µPulse的内毒素负荷为0.11 EU mg-1， SEC+DEF的内毒素负荷为0.07 EU mg-1，确保了纯化adc在生命系统中的安全应用。然而，与SEC+DEF相比，µPulse可以同时进行adc的纯化和配制，后者需要多次人工干预。我们的研究结果表明，µPulse是一种温和的、单步的、走开的adc纯化方法。

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引用次数: 0

IoT-based approach for diabetes patient monitoring using machine learning 基于物联网的糖尿病患者机器学习监测方法

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-09-13 DOI: 10.1016/j.slast.2025.100348

Sarra Ayouni , Muhammad Hamza Khan , Muhammad Ibrahim , Mohamed Maddeh , Nadeem Sarwar , Nazik Alturki

This study presents an IoT-based framework for real-time diabetes monitoring and management, addressing key limitations identified in previous studies by integrating four datasets: BVH Dataset, PIMA Diabetes Dataset, Simulated Dataset, and an Integrated Dataset. The proposed approach ensures diverse demographic representation and a wide range of features including real-time vital signs (e.g., oxygen saturation, pulse rate, temperature) and subjective variables (e.g., skin color, moisture, consciousness level). Advanced preprocessing techniques, including Kalman Filtering for noise reduction, KNN imputation for addressing missing data, and SMOTE-ENN for improving data quality and class balance, were employed. These methods resulted in a 25 % improvement in Recall and a 20 % increase in the F1-score, demonstrating the model's effectiveness and robustness.

By applying PCA and SHAP for feature engineering, high-impact features were identified, enabling the tuning of models such as Random Forest, SVM, and Logistic Regression, which achieved an accuracy of 97 % and an F1-score of 0.98. A novel triage system, integrated with edge and cloud computing, classifies health status in real-time (Green, Yellow, Red, Black), reducing latency by 35 %. The proposed system sets a new benchmark for scalable, individualized diabetes care in IoT-based healthcare solutions, demonstrating significant improvements in accuracy, response time, and feature incorporation compared to prior works.

本研究提出了一个基于物联网的糖尿病实时监测和管理框架，通过整合四个数据集：BVH数据集、PIMA糖尿病数据集、模拟数据集和集成数据集，解决了先前研究中发现的关键局限性。所提出的方法确保了多样化的人口统计学表征和广泛的特征，包括实时生命体征（例如，氧饱和度、脉搏率、温度）和主观变量（例如，肤色、湿度、意识水平）。采用了先进的预处理技术，包括用于降噪的卡尔曼滤波，用于寻寻缺失数据的KNN输入，以及用于提高数据质量和类平衡的SMOTE-ENN。这些方法使召回率提高了25%，f1得分提高了20%，证明了模型的有效性和稳健性。通过应用PCA和SHAP进行特征工程，识别出高影响特征，实现随机森林、支持向量机和Logistic回归等模型的调优，准确率达到97%，f1得分为0.98。一种新型的分类系统，集成了边缘和云计算，实时分类健康状态（绿色、黄色、红色、黑色），减少了35%的延迟。该系统为基于物联网的医疗保健解决方案中可扩展的个性化糖尿病护理设定了新的基准，与之前的工作相比，在准确性、响应时间和功能整合方面有了显着改善。

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引用次数: 0

High-throughput cytokine detection platform for evaluation of chemical induced microglial activation 评价化学诱导的小胶质细胞活化的高通量细胞因子检测平台。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-09-10 DOI: 10.1016/j.slast.2025.100347

Shu Yang , Kelly E. Carstens , Ibukunoluwa Ipaye , Xing Chen , Helena T. Hogberg , Nicole Kleinstreuer , Thomas B. Knudsen , Menghang Xia

Environmental chemical exposure, such as pesticides and heavy metals, may contribute to neurodegenerative disorders through neuroinflammation. This study aims to identify suitable in vitro microglial models for assessing cytokine responses to potential neurotoxicants, particularly focusing on human induced pluripotent stem cell-derived microglia (hiMG). In this study, we evaluated the cytokine secretion profiles of four microglial cell types—hiMG, HMC3, IM-HM, and BV2—upon stimulation with lipopolysaccharides (LPS) using cytokine arrays. Our findings showed cytokine response patterns in hiMG cells that most closely resemble in vivo conditions, with significant increases in interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) levels, the latter being uniquely expressed after LPS treatment. Consequently, we developed a homogeneous time-resolved fluorescence (HTRF) assay platform in a 1536-well plate format for high-throughput screening of environmental chemicals using hiMG cells. After LPS treatment, the assay window for secretion of IL-6 and TNF-α increased 3.71-fold and 2.62-fold over the vehicle control group, respectively, with respective EC₅₀ values of approximately 50 ng/mL and 90 ng/mL for IL-6 and TNF-α. We also assessed the response activity of hiMG to other stimuli, including interferon gamma and various catecholamine compounds, and nine environmental chemicals with evidence of cytokine-inducing potential in other in vitro assays. While all nine tested agents stimulated IL-6 and TNF-α production, three compounds (e.g., picoxystrobin) showed significant stimulation of both cytokines. This study establishes a reliable high-throughput platform for detecting inflammatory effects of environmental toxicants in a microglial cell assay, contributing valuable insights into their neuroinflammatory potential and possible implications for neurodegenerative disorders.

环境中的化学物质暴露，如杀虫剂和重金属，可能通过神经炎症导致神经退行性疾病。本研究旨在确定合适的体外小胶质细胞模型，以评估细胞因子对潜在神经毒物的反应，特别是关注人诱导多能干细胞来源的小胶质细胞（hiMG）。在这项研究中，我们使用细胞因子阵列评估了四种小胶质细胞类型（himg, HMC3， IM-HM和bv2）在脂多糖（LPS）刺激下的细胞因子分泌谱。我们的研究结果显示，细胞因子在hiMG细胞中的反应模式与体内条件最相似，白细胞介素6 （IL-6）和肿瘤坏死因子α (TNF-α)水平显著升高，后者在LPS处理后唯一表达。因此，我们开发了1536孔板格式的均匀时间分辨荧光（htf）检测平台，用于使用hiMG细胞进行高通量筛选环境化学物质。LPS处理后，IL-6和TNF-α分泌的测定窗口分别比对照增加了3.71倍和2.62倍，IL-6和TNF-α的EC50值分别约为50 ng/mL和90 ng/mL。我们还评估了hiMG对其他刺激的反应活性，包括干扰素γ和各种儿茶酚胺化合物，以及在其他体外实验中具有细胞因子诱导潜力的九种环境化学物质。虽然所有九种被测试的药物都能刺激IL-6和TNF-α的产生，但三种化合物（如皮氧嘧啶）对这两种细胞因子都有显著的刺激作用。本研究建立了一个可靠的高通量平台，用于在小胶质细胞试验中检测环境毒物的炎症效应，为其神经炎症潜力和神经退行性疾病的可能含义提供了有价值的见解。

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引用次数: 0

Staining Triad: A fully automated and zero-waste flow cytometry staining system fostering the 3R to 4R transition 三合一染色：一个全自动和零浪费的流式细胞术染色系统，促进3R到4R的过渡。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-27 DOI: 10.1016/j.slast.2025.100345

Santosh Dhule , Eric Corriveau , Christopher Lepsy , Sophie Tourdot

Despite significant advances in instrumentation and robotics, the automation of cell staining in flow cytometry remains largely unaddressed. While sample acquisition in flow cytometry has been fully automated, sample staining continues to be a predominantly manual process—requiring substantial time, labor, and cost. Additionally, the repetitive nature of manual staining introduces monotony and increases the likelihood of human error. The Staining Triad presented here achieves full automation of the staining process, requiring only the input of samples and reagents, with no manual intervention. Staining performed using the Staining Triad showed a comparable biomarker profile to that of conventional manual staining. The modular and adaptable system design enables the flexibility to tailor throughput and accommodate assay-specific requirements, thereby extending its applicability to plate-based ligand binding assays. Moreover, the system eliminates the need for pipette tips, exemplifying a sophisticated and sustainable solution that enhances laboratory efficiency while reducing human error and the primary source of plastic waste in flow cytometry staining. Although 3R initiatives (Reduce, Reuse, Recycle) have helped decrease laboratory plastic waste volumes, substantial amounts are still incinerated or end up in landfills, where they persist in the environment for decades. This limitation underscores the need to incorporate a fourth R—"Remove/Replace"—into sustainability strategies. As flow cytometry becomes increasingly integral across various biotechnology disciplines, it is imperative to streamline associated workflows to accelerate drug discovery while preserving the environment that sustains life.

尽管在仪器和机器人技术方面取得了重大进展，但流式细胞术中细胞染色的自动化在很大程度上仍未得到解决。虽然流式细胞术中的样品采集已经完全自动化，但样品染色仍然是一个主要的人工过程-需要大量的时间，劳动力和成本。此外，手工染色的重复性引入了单调性，增加了人为错误的可能性。这里介绍的染色三合一实现了染色过程的完全自动化，只需要输入样品和试剂，无需人工干预。使用染色三合一进行的染色显示出与传统手工染色相当的生物标志物特征。模块化和适应性强的系统设计提供了灵活性，以定制吞吐量和适应分析特定的要求，从而扩展其适用于基于板的配体结合分析。此外，该系统消除了对移液头的需求，体现了一个复杂和可持续的解决方案，提高了实验室效率，同时减少了人为错误和流式细胞术染色中塑料废物的主要来源。尽管3R倡议（减少、再利用、再循环）帮助减少了实验室塑料废物的数量，但仍有大量塑料被焚烧或最终进入垃圾填埋场，在那里它们在环境中存留了几十年。这一限制强调了将第四个R——“移除/替换”——纳入可持续发展战略的必要性。随着流式细胞术在各种生物技术学科中越来越不可或缺，简化相关工作流程以加速药物发现，同时保护维持生命的环境势在必行。

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引用次数: 0

Application of 3D printing imaging technology in the treatment of bronchopleural fistula with individual customized bronchial occluder 3D打印成像技术在个性化支气管封堵器治疗支气管胸膜瘘中的应用

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-27 DOI: 10.1016/j.slast.2025.100344

Zelin Xiao , Jianqi Gao , Hui Zhang , Linyao Wang

Background

Bronchopleural fistula (BPF) is a common and severe complication in thoracic surgery, characterized by its complex nature and high mortality rate. Bronchial occluder is one of the effective methods for the interventional treatment of BPF under bronchoscopy.

Objective

This work was to evaluate the adoption and efficacy of individualized bronchial occluder designed with the assistance of 3D printing technology in the treatment of BPF.

Material and Methods

This single-center, retrospective study included 60 patients (35 males and 25 females, aged 40–78 years, without severe dysfunction of major organs or history of mental disorders) diagnosed with BPF between January 2020 and December 2023, who received different treatment and were divided into the Control Group (CG, receiving thoracotomy treatment), Therapy group-I (TG-I, receiving septal occluder treatment), and Therapy group-II (TG-II, receiving treatment with 3D-printed individualized bronchial occluder). Serum levels of high-sensitivity C-reactive protein (hs-CRP) and procalcitonin (PCT) were measured by enzyme-linked immunosorbent assay preoperatively and at 1, 4, and 12 weeks postoperatively. Daytime cough scores were assessed according to guidelines, pain scores were evaluated using a visual analog scale, clinical efficacy was determined based on consensus criteria, and complications were recorded. Quantitative variables were compared using one-way ANOVA with Bonferroni correction, while categorical variables were analyzed by chi-square or Fisher’s exact test.

Results

the overall clinical efficacy was higher in TG-I and TG-II versus CG, with TG-II showing a greatly higher efficacy after twelve weeks of treatment (P < 0.05). Relative to CG, both TG-I and TG-II demonstrated lower serum levels of hs-CRP and PCT, markedly reduced cough and pain symptom scores, and markedly lower complication rates (P < 0.05). Additionally, TG-II resulted in notably lower serum inflammatory markers, cough and pain symptom scores, and complication rates versus TG-I (P < 0.05).

Conclusion

The 3D-printed personalized occluder (TG-II) significantly reduced postoperative inflammatory responses and alleviated cough-associated pain, demonstrating superior short-term efficacy and safety compared to conventional treatment (CG) and commercially available occluders (TG-I). This approach offers distinct advantages for the personalized precision treatment of BPF. However, further clinical studies are required to validate its potential as an alternative to surgical repair.

背景：支气管胸膜瘘（BPF）是胸外科手术中常见且严重的并发症，其性质复杂，死亡率高。支气管闭塞术是支气管镜下介入治疗BPF的有效方法之一。目的：评价3D打印技术辅助设计的个体化支气管封堵器在BPF治疗中的应用及疗效。材料和方法：本单中心回顾性研究纳入2020年1月至2023年12月诊断为BPF的患者60例（男35例，女25例，年龄40-78岁，无严重主要器官功能障碍或精神障碍史），接受不同治疗，分为对照组（CG，接受开胸治疗）、治疗组i （TG-I，接受间隔闭塞治疗）和治疗组ii (TG-II，接受3d打印个性化支气管封堵器治疗)。术前、术后1、4、12周采用酶联免疫吸附法测定血清高敏c反应蛋白（hs-CRP）和降钙素原（PCT）水平。根据指南评估日间咳嗽评分，使用视觉模拟量表评估疼痛评分，根据共识标准确定临床疗效，并记录并发症。定量变量比较采用Bonferroni校正的单因素方差分析，分类变量分析采用卡方或Fisher精确检验。结果：与CG相比，TG-I和TG-II的总体临床疗效更高，其中TG-II在治疗12周后的疗效明显更高(p结论：3d打印个性化封口器（TG-II）显著降低了术后炎症反应，缓解了咳嗽相关疼痛，与常规治疗（CG）和市售封口器（TG-I）相比，具有更优越的短期疗效和安全性。这种方法为BPF的个性化精确治疗提供了明显的优势。然而，需要进一步的临床研究来验证其作为手术修复替代方案的潜力。

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引用次数: 0

Bio-inspired computing and Machine learning analytics for future-oriented mental well-being 面向未来的心理健康的生物启发计算和机器学习分析。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-14 DOI: 10.1016/j.slast.2025.100343

Chinmay Chakraborty , Bhuvan Unhelkar , Saïd Mahmoudi

引用次数: 0

Life sciences and artificial intelligence 生命科学与人工智能。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-11 DOI: 10.1016/j.slast.2025.100342

Kerstin Thurow

引用次数: 0

Life sciences and society – an alphabetical journey 生命科学与社会——按字母顺序排列的旅程。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-10 DOI: 10.1016/j.slast.2025.100341

Kerstin Thurow

引用次数: 0

Self-supervised disc and cup segmentation via non-local deformable convolution and adaptive transformer 基于非局部可变形卷积和自适应变压器的自监督圆盘杯分割。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-09 DOI: 10.1016/j.slast.2025.100338

Wenbo Zhao , Yu Wang

Optic disc and cup segmentation is a crucial subfield of computer vision, playing a pivotal role in automated pathological image analysis. It enables precise, efficient, and automated diagnosis of ocular conditions, significantly aiding clinicians in real-world medical applications. However, due to the scarcity of medical segmentation data and the insufficient integration of global contextual information, the segmentation accuracy remains suboptimal. This issue becomes particularly pronounced in optic disc and cup cases with complex anatomical structures and ambiguous boundaries. In order to address these limitations, this paper introduces a self-supervised training strategy integrated with a newly designed network architecture to improve segmentation accuracy. Specifically,we initially propose a non-local dual deformable convolutional block,which aims to capture the irregular image patterns(

i . e .

boundary). Secondly,we modify the traditional vision transformer and design an adaptive K-Nearest Neighbors(KNN) transformation block to extract the global semantic context from images. Finally,an initialization strategy based on self-supervised training is proposed to reduce the burden on the network on labeled data. Comprehensive experimental evaluations demonstrate the effectiveness of our proposed method, which outperforms previous networks and achieves state-of-the-art performance,with IOU scores of 0.9577 for the optic disc and 0.8399 for the optic cup on the REFUGE dataset.

视盘杯分割是计算机视觉的一个重要分支，在病理图像自动分析中起着举足轻重的作用。它能够精确、高效和自动地诊断眼部疾病，极大地帮助临床医生在现实世界的医疗应用。然而，由于医学分割数据的缺乏和对全局上下文信息的整合不足，分割精度仍然不理想。这个问题变得特别明显视盘和杯病例复杂的解剖结构和模糊的边界。为了解决这些限制，本文引入了一种与新设计的网络架构相结合的自监督训练策略，以提高分割精度。具体来说，我们最初提出了一种非局部对偶可变形卷积块，其目的是捕获不规则的图像模式(即。边界)。其次，对传统的视觉变换进行改进，设计自适应k近邻变换块，从图像中提取全局语义上下文；最后，提出了一种基于自监督训练的初始化策略，以减轻网络对标记数据的负担。综合实验评估证明了我们提出的方法的有效性，该方法优于以前的网络，并达到了最先进的性能，在REFUGE数据集上视盘的IOU得分为0.9577，光学杯的IOU得分为0.8399。

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引用次数: 0

Life sciences discovery and technology highlights 生命科学发现和技术亮点。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology

Pub Date : 2025-08-06 DOI: 10.1016/j.slast.2025.100340

Tal Murthy , Jamien Lim

引用次数: 0

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