SLAS Technology最新文献

{"title":"Movable optical sensor for automatic detection and monitoring of liquid-liquid interfaces.","authors":"Rodrigo Moreno, Jonas Jensen, Shahbaz Tareq Bandesha, Simone Peters, Andres Faina, Kasper Stoy","doi":"10.1016/j.slast.2025.100335","DOIUrl":"10.1016/j.slast.2025.100335","url":null,"abstract":"<p><p>Liquid-liquid extraction (LLE) is an essential operation in many laboratory experiments. However, most automatic LLE devices concentrate on detecting the liquid-liquid interface at one moment in the process, usually at separation, and pay little attention to the state of the liquids as they settle. In this paper, we present an LLE device with a moving optical sensor and light source that move along a vessel instead of the mixture moving relative to the sensor. Analyzing the patterns of light intensity with explainable automatic detection algorithms, the interface can be detected at different positions in the vessel with an error below 2 mm and monitored during the settling process. The device is tested using a mixture of clear oil and water and two extraction steps in a battery interface material synthesis process. Results show that the setup is able to detect interfaces at different positions along the vessel, even with changes in diameter. By monitoring the settling process, we also found that the biggest change in the signal detected occurs around the liquid-liquid interface position, and we also use this information to corroborate it. The recording of sensor measurements at different positions over time can be used to detect different properties of the liquids, which improves control over the process and could also alleviate reproducibility problems in areas of chemistry in which it is costly to repeat procedures.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100335"},"PeriodicalIF":3.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144776907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Ovarian Microvascular Structure in PCOS Patients Based on High-resolution Ultrasound Imaging Technology.","authors":"Xianyi Chen, Guoxu Lv, Jian Lv, Ruoyu Wang, Jinyi Zhu, Hongying Kuang","doi":"10.1016/j.slast.2025.100356","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100356","url":null,"abstract":"<p><p>Polycystic Ovary Syndrome (PCOS) patients often have ovarian microcirculatory disorders. Traditional color Doppler imaging of microvascular is not sensitive enough and is prone to missed detection or artifact interference. This study is based on a high-frequency probe combined with SMI (Superb Microvascular Imaging) and ultrasound contrast imaging to achieve high signal-to-noise ratio acquisition and dynamic quantification of low-speed blood flow in microvascular, filling the gap in existing technology. This study sets low-pass filtering and low PRF (Pulse Repetition Frequency) to enhance the detection of low-speed flow signals in microvascular. SMI and CEUS (Contrast-Enhanced Ultrasound) sequences are collected in sequence, and the time points are calibrated synchronously on the same section to achieve multimodal image fusion. The ovarian area is semi-automatically segmented based on the U-Net model, and the ROI (Region of Interest) containing the vascular structure is extracted. The vascular density, average diameter, and number of branches are calculated using self-developed image analysis software, and the feature vector is derived. The CEUS time-intensity curve is fitted with a double exponential, and dynamic perfusion parameters such as peak time and perfusion half-life are extracted for microcirculation evaluation and hemodynamic analysis. The experiment shows that in the 10 ovarian ROIs analyzed, the vascular density ranges from 5.43% to 8.45%; the average diameter is 5.88 to 6.52 pixels; the branch number consistency difference rate is less than 3%. The perfusion half-life is distributed between 21.8 and 25.1 seconds, and the peak time of the PCOS group is delayed by 0.5 seconds compared with the normal group, indicating that there are significant differences in their microvascular structure and perfusion function.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100356"},"PeriodicalIF":3.7,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Driven Transcriptomic Biomarker Discovery for Early Identification of Pediatric Deterioration in Acute Care.","authors":"Qing Wang, Lina Sun, Wei Meng, Chen Chen","doi":"10.1016/j.slast.2025.100357","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100357","url":null,"abstract":"<p><p>Early detection of juvenile clinical deterioration in acute care settings remains a significant problem in modern healthcare. This paper presents an AI-powered predictive analytics platform that combines transcriptome biomarker signals with structured vital signs, laboratory data, and unstructured clinical notes to improve early warning capabilities. The system uses ClinicalBERT to extract insights from clinical narratives, XGBoost to analyze tabular clinical information, and long short-term memory (LSTM) networks to simulate temporal dynamics. A meta-classifier combines multimodal data to produce real-time risk ratings for clinical deterioration. The performance evaluation utilizing five-fold cross-validation showed great accuracy, with an AUROC of 0.91, AUPRC of 0.83, and an average early warning lead time of 5.6 hours. Predictive markers included higher lactate levels, heart rate patterns, SpO₂ variability, and transcriptome signals indicating systemic inflammatory activation. Ablation investigations proved the importance of multimodal data fusion in increasing prediction robustness. The suggested strategy provides a scalable, interpretable, and high-performing hospital integration system that enables biomarker-informed, precision-based pediatric intervention options.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100357"},"PeriodicalIF":3.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145208410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Early Detection of Bronchopulmonary Dysplasia (BPD) in Preterm Infants Using Doppler Ultrasound Technology\" [SLAS Technology Volume 31, April 2025, 100249].","authors":"Pin Wang, Lihong Duan, Congxin Sun, Yu Chen, Yanyan Peng, Guihong Chen, Lixia Wu, Yan Li","doi":"10.1016/j.slast.2025.100354","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100354","url":null,"abstract":"","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100354"},"PeriodicalIF":3.7,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The RoboSeed facilitates automated extraction of cereal mature embryos","authors":"R. Berenstein ,&nbsp;V. Bloch ,&nbsp;A. Beery ,&nbsp;M.R. Prusty ,&nbsp;J. Awwad ,&nbsp;O. Amir-Segev ,&nbsp;S. Miterani ,&nbsp;M. Barak ,&nbsp;G. Lidor ,&nbsp;E. Fridman","doi":"10.1016/j.slast.2025.100355","DOIUrl":"10.1016/j.slast.2025.100355","url":null,"abstract":"<div><div>To overcome a critical bottleneck in plant biotechnology workflows, a semiautomated system RoboSeed was developed to extract mature embryos from cereal grains such as barley. In contrast to the commonly used manual extraction, the robot employs a precision-controlled pressing rod which applies mechanical force along an optimal trajectory and angle to detach intact embryos. A custom image-processing pipeline determines grain orientation and morphology, enabling precise rod alignment at the optimal force application point. Validation experiments using two barley cultivars (Noga and Golden Promise) and soaking duration of 10 and 20 h revealed optimal force application point relative location in the range 0.5–0.6, achieving maximum extraction success rates of 56.2 % (Noga) and 36 % (GP) after 20 h soaking. RoboSeed operated with a median cycle time of 20.9 s per extraction, translating to 37.2 s per successful embryo, compared to 27.9 s with expert manual extraction. While current throughput is lower than conventional methods, RoboSeed offers significant advantages in consistency, reduced reliance on operator skill, and potential for scaling. Future improvements include full automation of grain singulation, robotic arms for post-extraction handling, and expanded testing across additional genotypes. RoboSeed’s modular design provides a robust foundation for scalable, high-throughput embryo extraction, with potential to accelerate cereal transformation, gene mapping studies, and tissue culture-based research.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"35 ","pages":"Article 100355"},"PeriodicalIF":3.7,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145139404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of high-resolution magnetic resonance imaging (MRI) in the evaluation of acupuncture effects in traditional Chinese medicine","authors":"Yujiao Zhang ,&nbsp;Zijiao Yang ,&nbsp;Shuhua Huang ,&nbsp;Sujiao Sun ,&nbsp;Zhuxian Liang","doi":"10.1016/j.slast.2025.100349","DOIUrl":"10.1016/j.slast.2025.100349","url":null,"abstract":"<div><div>In the evaluation of acupuncture effects in traditional Chinese medicine (TCM), the unclear interpretation of microscopic mechanisms and the difficulty in verifying acupoint specificity due to insufficient resolution of MRI (Magnetic Resonance Imaging) are the main reasons for the difficulty. This paper adopts 7T ultra-high field MRI combined with dynamic ASL (arterial spin labeling) technology, taking advantage of its high spatial resolution and quantitative blood perfusion imaging, to achieve dynamic visualization of microcirculation at acupuncture points in patients with ulcerative colitis. Ulcerative colitis is an ideal site to verify the feasibility of this method because its lesion site is clear and easy to correspond with the body surface acupoint. This paper establishes a high-resolution imaging protocol based on 7T magnetic resonance imaging, adopts 0.5mm spatial resolution, and optimizes scanning parameters to adapt to the microstructural imaging requirements of the acupoint area. This paper introduces pCASL (pseudo-continuous arterial spin labeling) technology, sets the labeling duration and perfusion delay time, captures the changes in perfusion volume before and after acupuncture over time, and obtains a dynamic perfusion sequence. This paper adopts umbilical moxibustion therapy, selects specific meridian acupoints, sets a standard acupuncture stimulation scheme (needle insertion depth, frequency, and needle retention time), and simultaneously performs MRI scanning to achieve real-time acupuncture imaging acquisition. The acquired multi-time point images can be rigidly registered and mapped with standard templates, the blood flow intensity change curve of the acupuncture-related area can be extracted, and the time-perfusion function can be constructed to analyze the local response pattern. The experimental results show that the ΔCBF (Delta Cerebral Blood Flow) of 7T-ASL at Shenque, Tianshu and Zhongwan are 0.15, 0.12 and 0.18 respectively, and it has high sensitivity in capturing tiny blood flow changes under sub-millimeter resolution. The SNR (Signal-to-Noise Ratio) at Shenque, Tianshu and Zhongwan are 22, 25 and 24 respectively, and the CNR (Contrast-to-Noise Ratio) is 6.2, 6.5 and 6.7 respectively, which has significant advantages in the spatial identification of sensitive areas of neural regulation and the identification of perfusion response. The average rising rate, peak time and recovery time in all acupoints were 2.44%/s, 7.2s and 11.5s respectively, and the acupuncture effect took effect faster in local areas.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"35 ","pages":"Article 100349"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive Evaluation Model and High-Resolution Medical Images in Sports Injury Rehabilitation under Bone Density Changes.","authors":"Wenping Li, Zhiming Gu","doi":"10.1016/j.slast.2025.100350","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100350","url":null,"abstract":"<p><p>In the study of bone density changes and sports injury rehabilitation, traditional image processing technology lacks accuracy in analysis, rehabilitation assessment methods lack quantitative and systematic analysis, and interdisciplinary comprehensive evaluation is lacking. This paper constructs an innovative cognitive assessment model that combines bone density changes, sports injury rehabilitation, and high-resolution medical image analysis. It uses high-resolution CT (Computed Tomography) images and X-ray images to extract bone density data. It uses image processing technology to remove noise, enhance, and standardize, providing accurate bone density values for subsequent input. GCN (Graph Convolutional Network) can be used to automatically identify and classify images of sports injury sites, extract features of the injured area, record and analyze the patient's physical activities during the rehabilitation stage, and evaluate the recovery process of sports injuries in real time. Combining bone density data with sports injury imaging features, XGBoost (Extreme Gradient Boosting) is used to build a cognitive evaluation model, which conducts a comprehensive analysis of multi-dimensional data and provides personalized rehabilitation evaluation. It can integrate technologies from fields such as medicine, engineering, and computer science to establish an interdisciplinary comprehensive evaluation system, achieve multi-angle and multi-dimensional analysis, and ensure the comprehensiveness and accuracy of the model. The experimental results show that the MAE (Mean Absolute Error) of the GCN in this paper is 0.131 in 10 different injury sites, and the average MSE (Mean Squared Error) is about 0.032, which has higher image analysis accuracy. The average accuracy and R² of XGBoost in six different samples are about 0.87 and 0.91, respectively, and the prediction effect of the cognitive evaluation model is apparent.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100350"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a Nomogram Prediction Model for Screening of Serum Markers for Lower Extremity Vasculopathy Secondary to Type 2 Diabetes Mellitus.","authors":"Jingjing Yang, Jinyan Chen, Lanying Shen","doi":"10.1016/j.slast.2025.100352","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100352","url":null,"abstract":"<p><strong>Objective: </strong>To screen serum markers for secondary lower extremity angiopathy (LEAD) in patients with type 2 diabetes mellitus (T2DM) and construct a nomogram prediction model accordingly.</p><p><strong>Methods: </strong>The clinical data of 200 T2DM patients admitted to the hospital from December 2022 to October 2024 were retrospectively collected. It was also divided into modeling group (n=160) and internal validation group (n=40) in a 4:1 ratio by using the leave-out method. As the external validation group, clinical data from 100 T2DM patients who were admitted to other hospitals within the same time period were also gathered. Combined with previous reports of collecting serum marker data related to LEAD secondary to T2DM, key serum markers were screened using LASSO regression. Moreover, multifactorial analysis helped to clarify independent risk factors, and a nomogram prediction model was built and tested for accuracy.</p><p><strong>Results: </strong>The incidence of LEAD in 200 T2DM patients in the hospital was 21.00% (42/200). A total of 14 variables were screened by LASSO regression analysis. After multifactorial analysis, it was found that disease duration, history of alcohol consumption, mean platelet volume, fasting blood glucose, fibrinogen, high-sensitivity C-reactive protein, insulin-like growth factor 1, nucleotide binding oligomerization domain like receptor protein 3 were independent risk factors for LEAD secondary to T2DM.The results of model validation showed AUCs of 0.971, 0.900, and 0.959 for the modeling cohort, internal validation cohort, and external validation cohort, respectively. The Hosmer-Lemeshow test was χ²=6.607, 7.962, and 6.585 (p>0.05). Positive net benefits were obtained by intervening with patients using a nomogram model within the high-risk threshold of 0 to 0.9.</p><p><strong>Conclusion: </strong>In this study, eight risk factors associated with LEAD secondary to T2DM are screened by LASSO regression and multifactorial analysis, and a nomogram prediction model is constructed.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100352"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low code, high impact: Application of low-code platforms to enable and democratize the development of laboratory digitalization and automation applications","authors":"Jonas Austerjost ,&nbsp;Elias Knöchelmann ,&nbsp;Thomas Kruse ,&nbsp;Janina Kilian ,&nbsp;Bastian Quaas ,&nbsp;Michael W. Olszowy","doi":"10.1016/j.slast.2025.100353","DOIUrl":"10.1016/j.slast.2025.100353","url":null,"abstract":"<div><div>Conventionally, the initialization of new prototypes and concepts in laboratory automation and life science software applications has required close collaboration between hardware and software experts, as well as lab personnel such as biologists, chemists, biotechnologists, or process engineers. This setup - still common today - often means that the ideas and requests of lab personnel must be translated into software applications by software developers, which frequently results in long development times. Low-Code Development Platforms (LCDPs) seek to address this challenge by providing a way to accelerate application development by reducing dependence on traditional software development methods, empowering lab personnel to build applications without writing extensive amount of code. By offering a visual, drag-and-drop interface, lab personnel can actively participate in the software development process. This helps democratize application creation and can lead to the quick setup of software solutions tailored to laboratory needs.</div><div>This study demonstrates the implementation of four different use cases in a bioprocessing laboratory environment using an open-source LCDP and commercially available upstream and downstream equipment. The LCDP facilitated the integration and control of different device types with varying communication protocols also enabling dashboarding, monitoring and data processing capabilities. This methodology highlights the suitability of LCDPs for rapidly prototyping and evaluating laboratory and bioprocess automation pipelines, potentially expediting the development of biotechnological production processes and products. All developed components are made available through a publicly accessible repository, facilitating reuse and further development by the scientific community.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"35 ","pages":"Article 100353"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-step purification and formulation of antibody-drug conjugates using a miniaturized tangential flow filtration system","authors":"Muhammad Sajed ,&nbsp;Zahoor Khan ,&nbsp;Muhammad Usman Ashraf ,&nbsp;Hafsa Iftikhar ,&nbsp;Talha Bin Rahat ,&nbsp;Samia Falak ,&nbsp;Salman Fozail ,&nbsp;Quiterie Gue ,&nbsp;Raul Pardo ,&nbsp;Lance Ramsey ,&nbsp;Muhammad Saqib Shahzad","doi":"10.1016/j.slast.2025.100351","DOIUrl":"10.1016/j.slast.2025.100351","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"35 ","pages":"Article 100351"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}