SLAS Technology最新文献

{"title":"Association of the Characteristics of Brain Magnetic Resonance Imaging with Genes Related to Disease Onset in Schizophrenia Patients.","authors":"Jiantu Lin, Bo Wang, Shaoguang Chen, Fengling Cao, Jingbin Zhang, Zirong Lu","doi":"10.1016/j.slast.2025.100281","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100281","url":null,"abstract":"<p><strong>Background: </strong>Schizophrenia (SCH) is a complex neurodevelopmental disorder, whose pathogenesis is not fully elucidated. This article aims to reveal disease-specific brain structural and functional changes and their potential genetic basis by analyzing the characteristics of brain magnetic resonance imaging (MRI) in SCH patients and related gene expression patterns.</p><p><strong>Methods: </strong>Differentially expressed genes (DEGs) between SCH and healthy control (NC) groups in the GSE48072 dataset were identified and functionally analyzed, and a protein-protein interaction (PPI) network was fabricated to screen for core genes (CGs). Meanwhile, MRI data from the COBRE, the Human Connectome Project (HCP), the 1000 Functional Connectomes Project (FCP), and the Consortium for Reliability and Reproducibility (CoRR) were utilized to explore differences in brain activity patterns between SCH patients and NC group using a 3D deep aggregation network (3D DANet) machine learning approach. A correlation analysis was performed between the identified CGs and MRI imaging characteristics.</p><p><strong>Results: </strong>82 DEGs were collected from the GSE48072 dataset, primarily involved in cytotoxic granules, growth factor binding, and graft-versus-host disease pathways. The construction of the PPI network revealed KLRD1, KLRF1, CD244, GZMH, GZMA, GZMB, PRF1, and SLAMF6 as CGs. SCH patients exhibited relatively enhanced activity patterns in the frontoparietal attention network (FAN) and default mode network (DMN) across four datasets, while showing a trend of weakening in most other networks. The 3D DANet demonstrated higher accuracy, specificity, and sensitivity in brain image classification. The correlation between enhancement of the DMN and genetic abnormalities was the strongest, followed by the enhancement of the frontal and parietal attention networks. In contrast, the correlation between the weakening of the sensory-motor network and occipital network and genetic abnormalities was relatively weak. The strongest correlation was observed between MRI characteristics and the KLRD1 and CD244 genes.</p><p><strong>Conclusion: </strong>The granzyme-mediated programmed cell death signaling pathway is related to pathogenesis of SCH, and CD244 may serve as potential biological markers for diagnosing SCH. The correlation between enhancement of the DMN and genetic abnormalities was the strongest, followed by the enhancement of the frontal and parietal attention networks. In contrast, the correlation between weakening of the sensory-motor network and occipital network and genetic abnormalities was relatively weak. Additionally, the strongest correlation was observed between MRI features and the KLRD1 and CD244 genes. The use of the 3D DANet method has improved the detection precision of brain structural and functional changes in SCH patients, providing a new perspective for understanding the biological basis of the disease.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100281"},"PeriodicalIF":2.5,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755687","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":"Precision through Electric-Field Assisted Automatable High Throughput Sample Preparation of Dried Blood Spots for Neonatal Abstinence Syndrome Detection.","authors":"Ramisa Fariha, John Murphy, Nondi Walters, Emma Rothkopf, Oluwanifemi D Okoh, Nabil M Lawandy, Anubhav Tripathi","doi":"10.1016/j.slast.2025.100282","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100282","url":null,"abstract":"<p><p>In the United States, approximately 20% of pregnant women disclose opioid misuse, contributing significantly to the widespread occurrence of Neonatal Abstinence Syndrome (NAS) in neonates exposed to opioids during gestation. Current NAS diagnosis heavily relies on clinical observation of symptoms, with the Finnegan Neonatal Abstinence Scoring System (FNASS) serving as the gold standard due to challenges associated with obtaining biological specimens from newborns. This methodological constraint poses difficulties in achieving accurate quantitative assessments and implementing timely therapeutic interventions. This study introduces a pioneering approach employing a cylindrical electrode-equipped device designed for the extraction of opioids from minute Dried Blood Spot (DBS) samples, thus optimizing the diagnostic pathway for NAS. The methodology integrates Liquid Chromatography tandem Mass Spectrometry (LC-MS/MS) for precise quantification of five distinct opioids. By demonstrating the efficacy of DBS microsamples as a robust quantitative diagnostic medium, this research highlights its potential to expedite NAS detection in infants. The innovative methodology promises superior diagnostic precision and accelerated processing times compared to current protocols, thereby addressing existing NAS diagnostic limitations and advancing maternal and infant healthcare practices.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100282"},"PeriodicalIF":2.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744480","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":"Literature Highlights Column: From the Literature Life Sciences Discovery and Technology Highlights.","authors":"Tal Murthy, Jamien Lim","doi":"10.1016/j.slast.2025.100280","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100280","url":null,"abstract":"","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100280"},"PeriodicalIF":2.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744477","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":"An out-of-hours Cell Culture Autopilot proof of concept based on a modular architecture using the SiLA2 open standard.","authors":"Patrick Courtney, Raphael Lieberherr, William Speed, Ricardo Gaviria, Yordan Alipiev, Miguel van der Heijden, Oliver Peter","doi":"10.1016/j.slast.2025.100279","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100279","url":null,"abstract":"<p><p>There has been much talk and substantial progress in automated and flexible Smart lab concepts in biopharma R&D. This is acknowledged to be important in enabling the acceleration of innovation and digitization of R&D operations. However, many proposals stop short of full end-to-end automation - limiting out-of-hours operation, which is particularly important in tasks such as cell culture - or are locked to a particular vendor's offering in a dedicated system - which can limit the flexibility and shared use access so important in R&D. In this contribution we describe a proof-of-concept of a fully integrated automated adherent cell culture system based on a modular architecture that allows integration of the most recent developments on the market (cell imaging, collaborative cloud robotics, mobile robots) as well as reuse of existing legacy devices (incubators and refrigerators). This creates a \"cell culture autopilot\" for small-scale cell culture, with repetitive media exchange, confluency checking, and splitting steps which are typically labor-intensive and must take place at times outside the working day. The system is built around the open lab communication standard SiLA2 and various other open-source resources to create three ways in which the SiLA2 standard can be leveraged. This choice of connectivity options provides freedom to integrate the most appropriate device while minimizing undesired vendor-lock in. This paper provides sufficient details for the reader to access the resources to build on such a system for cell culture and other applications. We believe this to be the first report of a true vendor-agnostic system operating in a commercial environment. END abstract: This paper corresponds to the special issue on Robotics in Laboratory Automation as it describes robotics for labware transportation within a shared environment, and an automation framework supporting physical and logical interoperability.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100279"},"PeriodicalIF":2.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744474","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":"Building new model of intelligent mutual support for the elderly based on the decision support platform of the health management data center","authors":"Zewei Hu ,&nbsp;Jinxian Wang ,&nbsp;Haiwen Nie ,&nbsp;Yicheng Liu ,&nbsp;Xing Li","doi":"10.1016/j.slast.2025.100274","DOIUrl":"10.1016/j.slast.2025.100274","url":null,"abstract":"<div><div>At this stage, China is in the stage of population aging. With the continuous growth of the elderly population, the pension problem is also increasingly serious. The existing pension model has such problems as small service scope, low service level, and few types of services, which is difficult to provide good pension services for the elderly. Therefore, it is necessary to actively explore some new pension models to break this situation. Therefore, based on the analysis of the current situation of the elderly who lost their independence in the western rural areas, this paper put forward a mutual pension model. In order to optimize the model, this paper also constructed a health management data decision support platform based on Internet technology. In this paper, the platform was applied to the intelligent mutual-aid pension model to realize intelligent management of the mutual-aid pension model. At the same time, this paper also carried out further experimental research on the recommendation performance of elderly care services by combining the discriminant analysis method. From the experimental results, in terms of service recommendation time, the average test result of this method was 18.51 s, while the average test result of the traditional method was 25.18 s; In terms of recommended coverage, the average test result of this method was 88.63 %, and the average test result of the traditional method was 84.28 %; In terms of recommendation accuracy, the average test result of this method was 92.60 %, and the average test result of the traditional method was 88.56 %. To sum up, this method can effectively improve the performance of pension service recommendation, so as to provide more accurate pension services for the elderly.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100274"},"PeriodicalIF":2.5,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on biphasic blood drying method for rapid pathogen detection in bloodstream infections","authors":"Jongwon Lim ,&nbsp;Katherine Koprowski ,&nbsp;Matthew Wester ,&nbsp;Enrique Valera ,&nbsp;Rashid Bashir","doi":"10.1016/j.slast.2025.100276","DOIUrl":"10.1016/j.slast.2025.100276","url":null,"abstract":"<div><div>Rapid and accurate detection of pathogenic microorganisms in blood is critical for diagnosing life-threatening conditions such as bloodstream infections (BSIs). Current methods for the detection and identification of bacteria from large volumes of blood (5 mL) involve culture steps followed by DNA extraction/purification/concentration and Polymerase Chain Reaction (PCR)-based nucleic acid amplification. DNA extraction and amplification directly from blood samples is hampered by the complexity of the blood matrix, resulting in time-consuming and labor-intensive processes. This review delves into recent advancements in molecular diagnostics based on blood drying, coined as ‘biphasic reaction’, and highlights this new technique that attempts to overcome the limitations of traditional sample preparation and amplification processes. The biphasic blood drying method, in combination with isothermal amplification methods such as loop-mediated isothermal amplification (LAMP) or recombinase polymerase amplification (RPA), has recently been shown to improve the sensitivity of detection of bacterial, viral, and fungal pathogens from ∼1 mL of whole blood, while minimizing DNA loss and avoiding the use of extraction/purification/concentration kits. Furthermore, the biphasic approach in combination with LAMP has been shown to be a culture-free method capable of detecting bacteria in clinical samples with a sensitivity of ∼1 CFU/mL in ∼2.5 h. This represents a significant reduction in detection and identification time compared to current clinical procedures based on bacterial culture prior to PCR amplification. This review paper aims to be a guide to identify new opportunities for future advancements and applications of the biphasic technology.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100276"},"PeriodicalIF":2.5,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Medical Assessment of the Impact of Anesthesia and Sedation Depth on Cognitive Function after Gynecological Laparoscopic Surgery.","authors":"Xuerong Zhang, Xueying Yang, Qiong Zhao","doi":"10.1016/j.slast.2025.100273","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100273","url":null,"abstract":"<p><p>In recent years, the research on post operational cognitive dysfunction (POCD) has received increasing attention. Some patients may experience complications such as mental disorder and memory impairment after gynecological laparoscopic surgery, which are cognitive, social, and personality issues of postoperative patients. This article divided patients after gynecological laparoscopic surgery into three groups based on different BIS (biological index) ranges. Before clinical use, artificial intelligence was used to sort out patients' complete history records, physical examination and analyze laboratory examination results, so as to determine the anesthetic dose and depth and reduce the incidence of accidents during surgery. This article adopted a combination of midazolam propofol radiocuronium bromide general anesthesia to adjust blood targeted concentration and maintain the depth of general anesthesia for patients. Using POCD as a starting point, the occurrence of POCD after gynecological laparoscopic surgery was evaluated through preoperative and postoperative neuropsychological measurements on the 14th day, as well as MMSE (Minimal State Examination) scores, and the impact of different anesthesia depths on POCD was also explored, which can provide a theoretical basis for the prevention and treatment of POCD. The MMSE score of Group A patients on the day before anesthesia was 23.9, while the MMSE score of Group B patients on the day before anesthesia was 23.8. The application of intelligent medicine in the study of the impact of anesthesia and sedation depth on gynecological laparoscopic surgery can improve the safety of surgery and the quality of life of patients, and has an important promoting role in clinical practice. The innovation of the research in this paper lies in the use of intelligent medical technology, through neuropsychological testing and MMSE scoring, in-depth analysis of the relationship between anesthesia depth and POCD.Combined anesthesia with midazolam and propofol was used, and the depth of anesthesia was precisely adjusted according to the BIS value.The study found that shallow anesthesia (low BIS value) may reduce the incidence of POCD, which provides theoretical and practical guidance for optimizing anesthesia strategies.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100273"},"PeriodicalIF":2.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694067","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":"Innovations in otolaryngology using LLM for early detection of sleep-disordered breathing","authors":"Jin Zhou ,&nbsp;Xiaoqin Li ,&nbsp;Qianjun Xia ,&nbsp;Liangcai Yu","doi":"10.1016/j.slast.2025.100278","DOIUrl":"10.1016/j.slast.2025.100278","url":null,"abstract":"<div><div>Sleep Disordered Breathing (SDB), including conditions like Obstructive Sleep Apnea (OSA), represents a major health concern, characterized by irregular airflow during sleep due to airway obstruction. SDB can result in serious health problems. Implementation of early intervention is vital whenever patient outcomes are to be considered. This research aims to advance research on otolaryngology using Machine Learning (ML) models, and Large Language Models (LLM) for identification of SDB using Electronic Health Record (HER). The approach proposes a hybrid ML framework combining the Dynamic Seagull Search algorithm-driven Large Language model (DSS-LLM). The extensive clinical dataset is used to train the model. It includes patient demographics, medical history, sleep habits, comorbidities, and physical measurements. Data pre-processing involves handling missing values, applying NLP techniques, and normalization. Feature extraction is done using Principal Component Analysis (PCA) to reduce the dimensionality of the hyperparameters and finally for selecting the best set of predictors. The extracted features are then used to train the proposed DSS-LLM model, which incorporates the DSS algorithm to optimize the LLM classifier, improving classification accuracy and model robustness. Subsequently, the idea of LLM is introduced for its application on textual clinical records comprising physicians' reports and patients’ symptoms. The findings from an experiment suggest that the proposed model enhances the classification accuracy achieved to 98.91 %, precision attained by 98.9 %, recall achieved to 98.92 % and F-1 score attained by 98.58 % as compared to the models developed earlier. This research provides a novel solution to the screening of OSA at the pre-clinical level which involves hybrid machine learning models integrated with LLMs. This proposed framework is expected to boost clinical judgment and thereby increase better ophthalmology outcomes for patients.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100278"},"PeriodicalIF":2.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143693668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of melittin-induced acute kidney injury in different degrees in rats by contrast-enhanced ultrasound techniques","authors":"JinLian Li ,&nbsp;JianZheng Yang ,&nbsp;ShiFeng Lai ,&nbsp;QingLan He ,&nbsp;ShiYing Li ,&nbsp;LinLing Liu ,&nbsp;MingXing Li","doi":"10.1016/j.slast.2025.100275","DOIUrl":"10.1016/j.slast.2025.100275","url":null,"abstract":"<div><div>To evaluate the renal perfusion of acute kidney injury (AKI) induced by melittin in the rats using contrast-enhanced ultrasound (CEUS). Twenty-four healthy male SD rats were randomly divided into high concentration of melittin group, low concentration of melittin group and control group with 8 rats in each group. Melittin was injected through the rats' right femoral vein, to establish a rat model of AKI. Twelve hours later, CEUS and its Quantitative analysis of TIC parameters was performed. Blood samples from rats were taken to detect creatinine (Cr), right kidney was removed to perform HE staining and apoptosis markers (BAX,Bcl-2,Casepase3) assessment. The correlations among the quantitative parameters of CEUS TIC, Cr and apoptosis marker of PCR were analyzed.Results shows: 1.The quantitative parameters of CEUS TIC(Peak, TP, AUC, MTT) and apoptosis markers PCR parameters (BAX, Bcl-2, Casepase3) were significantly different among three groups (<em>p</em> &lt; 0.01);2. Correlation analysis: Within the high concentration group: There was a correlation among the quantitative parameters of CEUS TIC, cr and apoptosis marker of PCR;In the low concentration group: There was a correlation between the quantitative parameters of CEUS TIC and the parameters of apoptosis marker of PCR, but There was no correlation between Cr and the former two. CEUS can provide a sensitive,real-time,non-invasive technique to detect and evaluate the degree of AKI earlier than Cr.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100275"},"PeriodicalIF":2.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application effect of rehabilitation robots in rehabilitation of limb movement disorders based on neural network algorithms","authors":"Dongchen Han","doi":"10.1016/j.slast.2025.100277","DOIUrl":"10.1016/j.slast.2025.100277","url":null,"abstract":"<div><div>With the continuous advancement of computer technology and sensor technology, rehabilitation robots have shown great potential in the rehabilitation treatment of limb movement disorders. This paper designs a rehabilitation robot based on a neural network algorithm to improve the rehabilitation effect of patients with limb movement disorders. The robot consists of a four-axis robotic arm, a three-finger gripper, a wheeled chassis and a variety of sensors. The control program written in C language and the host computer program written in Python language realize the control of motion and force, and the neural network algorithm is used to accurately adjust the position and force. In the control system design, the back propagation algorithm is used to train the neural network, and it is optimized in combination with multiple data to ensure that the robot can accurately track and assist the patient's limb movement. In order to verify the effect of the rehabilitation robot, this paper conducted an experimental evaluation. The experimental group was patients who received rehabilitation training based on the neural network algorithm, and the control group was patients who received traditional physical therapy. Through the evaluation of multiple indicators such as the 10-meter walking test, Berg balance scale, Jebsen-Taylor hand function test and MOS SF-36 health questionnaire, the experimental results showed that the improvement of the experimental group in each test was significantly better than that of the control group. Especially in the Berg balance scale and Jebsen-Taylor hand function test, the scores of the experimental group were significantly improved, indicating that the rehabilitation robot plays an important supporting role in the rehabilitation training of patients with limb movement disorders and has broad application prospects.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100277"},"PeriodicalIF":2.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}