SLAS Technology最新文献

This study presents an interactive visualization-based Model-Based Systems Engineering (MBSE) technique that is especially designed to handle requirements analysis and design issues in joint test settings. Standardized operational requirement description, test requirement analysis, test design, and first test system plan generation are the four primary phases that make up the technique. This method provides a more thorough and approachable depiction of both operational and test requirements by utilizing interactive visualization techniques. This makes it possible for test staff to more accurately and efficiently develop, visualize, and improve test plans. The methodology's efficacy in augmenting the capabilities of joint testing platforms is demonstrated through a thorough case study of a joint test. Higher levels of accuracy and dependability in test results are eventually a result of this approach's strong support for requirements analysis, test design, and the general execution and assessment of joint tests inside complex systems.

At GSK, we have implemented custom integrated robotics platforms housed in bespoke biosafety enclosures to augment our capabilities in advanced cellular screening. Here we present and discuss the impact of one such system, the Cellular Automated Screening Platform (CASPer). We evaluate the benefits of implementing specific processes on CASPer that include increasing the throughput of safety screening assays and improving data integrity when testing complex in vitro 3D primary human hepatocyte models. This article provides an overview of the platforms installed and offers insight into their utilisation by presenting example workflows and quality control solutions which have been implemented. We offer perspective on the advantages of such custom integrated systems and their limitations in cellular screening for early drug discovery.

The vaginal microbiota plays an important role in reproductive health, especially in the process of artificial insemination. The imbalance of microbiota may affect pregnancy outcomes. Therefore, this study aims to explore the composition of vaginal microbiota and its impact on artificial insemination pregnancy outcomes, combined with microscopic images and PCR fluorescence methods, in order to provide scientific basis for improving the pregnancy outcomes of husband sperm artificial insemination. This study included female patients who underwent artificial insemination with husband's sperm and collected reproductive tract samples. By observing the microbial community morphology in the sample under a microscope and analyzing microbial DNA using PCR fluorescence method, the microbial ecological status is evaluated. Among women with successful pregnancy, the proportion of beneficial bacteria (such as lactic acid bacteria) is higher, while the abundance of pathogenic bacteria is significantly reduced. Specific microbial markers detected by PCR fluorescence method are positively correlated with pregnancy rate. Therefore, the microecological state of the female reproductive tract has a significant impact on the pregnancy outcome of artificial insemination. Maintaining a good microecological balance, especially increasing the proportion of beneficial bacteria, can help improve the success rate of artificial insemination.

Nitroreductase (NTR) plays a critical role in the oxygen-deficient environment of anoxic tumor cells, and its identification is crucial for the diagnosis and treatment of cancer. This research introduces an innovative Surface Enhanced Raman Scattering (SERS) probe, created by attaching p-nitrothiophenol (p-NTP) to gold nanoparticles (Au NPs). This probe leverages the specific enzymatic reaction of NTR in hypoxic status, utilizing decreased NADH. The enzymatic activity of NTR transforms nitroaromatic compounds into aromatic amines, which is then reflected as a measurable shift in the SERS signal of the probe. This novel approach allows for the accurate quantification of NTR, with the sensitivity reaching a detection threshold of less than 0.02 μg/mL. The probe's non-toxic nature and superior biocompatibility facilitate its use for direct SERS investigations in A549 cells under reduced oxygen levels. We also applied this method to xenograft model. The results demonstrate a marked increase in NTR levels in tumor cells and tumor tissues in hypoxic conditions, highlighting the significance of this nanoprobe in enhancing cancer diagnostics, helping medical doctors making treatment decisions more swiftly and effectively.

Automated liquid handlers are fundamental in modern life science laboratories, yet their high costs and large footprints often limit accessibility for smaller labs. This study presents an innovative approach to decentralizing a liquid handling system by converting a low-cost 3D printer into a customizable and accurate liquid handler. The Personal Automated Liquid Handler (PALH) system, costing ∼$400, incorporates a single-channel pipet, custom 3D-printed components, and open-source software for personalized workflows, allowing researchers to build and modify the system for specific experimental needs. The PALH system was evaluated through common life science assays, including preparing real-time PCR samples, end-point PCR with novel pipet-based downstream purification, and genomic DNA extraction from peripheral whole blood. In real-time PCR experiments targeting the YWHAZ gene, the PALH system demonstrated comparable performance to manual preparation across DNA quantities (1 pg to 100 ng). For end-point PCR, the PALH successfully amplified and purified 204 bp and 406 bp amplicons from a pUC19 vector, yielding concentrations similar to manual methods (5.43 ± 0.85 ng/µL vs. 2.10 ± 0.16 ng/µL for 204 bp; 3.74 ± 2.13 ng/µL vs. 1.51 ± 0.15 ng/µL for 406 bp, respectively). In genomic DNA extraction from whole blood, the PALH system achieved comparable DNA yields to manual extraction (49.52 ± 3.13 ng/µL vs. 48.62 ± 5.9 ng/µL), although at higher purity (260/280 ratio of 1.83 ± 0.07 vs. 1.92 ± 0.03), although both are at acceptable ranges. The open-source nature of the PALH system hopefully encourages further community-driven improvements and protocol sharing, fostering innovation and collaboration within the scientific community. As laboratory automation advances, the PALH system could be crucial in democratizing access to high-quality automated liquid handling, particularly in resource-limited settings.

Objective: The purpose of this research is to determine if Doppler ultrasonography technology may be used to forecast the onset of bronchopulmonary dysplasia (BPD) in premature babies in the early postnatal stage.

Methods: On days 3, 7, 14, and 28 after delivery, Doppler ultrasonography exams were performed on a prospective cohort of 170 preterm newborns. Measurements were made of parameters such right ventricular output (RVO), systolic-to-diastolic ratio (S/D ratio), pulmonary artery acceleration time (PAAT), and velocity time integral (VTI). The predictive value of these indicators was evaluated using Kaplan-Meier survival analysis and multivariate logistic regression.

Results: The severity of BPD was substantially correlated with all assessed Doppler ultrasound parameters (P<0.05). With an area under the curve (AUC) of 0.76, PAAT in particular demonstrated a reasonable capacity for prediction. A considerably greater cumulative incidence was found by Kaplan-Meier survival analysis.

Conclusion: In conclusion, Doppler ultrasonography technology is a useful technique for identifying BPD in premature babies early on. High-risk babies can be efficiently identified by PAAT and VTI in particular, allowing for prompt intervention and possibly better results.

Comprehensive Genomic Profiling (CGP) has emerged as a progressive standard of care for the understanding clinical oncology and treatment of solid tumors (Conroy, Pabla et al. 2021). By identifying actionable mutations through next-generation sequencing of solid tumors CGP enables targeted therapy decisions. Formalin-fixed paraffin-embedded tissues are notoriously difficult samples in respect to reliably extracting high-quality nucleic acids and sufficient genetic material to meet sequencing input requirements. In this work we present an automated solution for upstream sample processing of solid tumors to enable high throughput and scalable CGP workflows by eliminating bottlenecks and enhancing results. The Sonication STAR automated DNA and RNA methods from FFPE Tissues was created as a collaboration between Hamilton Company, Covaris, and Labcorp and it offers the potential reduction in quantity not sufficient (QNS) samples and sequencing performance improvements resulting in a 16% increase in fully reported tumor profiles for patients. This automated approach offers potential saving in workflow costs, improved efficiency, and a reduction in re-extraction and re-sequencing of tumors.

Mild cognitive impairment (MCI) is an intermediate state between normal aging and dementia, and its symptoms include easy forgetting, distraction, and mental deterioration. This directly affects the patient's motor function, daily living ability, and social adaptability, and brings many difficulties to the patient's reintegration into society. Therefore, clinical research on MCI is very necessary. The purpose of this paper is to study the efficacy of acupuncture and moxibustion in the treatment of MCI based on VR virtual reality technology. This paper firstly expounds the application prospect of VR virtual reality rehabilitation training and virtual scene intervention in MCI patients. It then introduces the characteristics of acupuncture and the acupuncture points of scalp acupuncture and eye acupuncture. This paper then establishes the algorithm model of the VR virtual reality rehabilitation training system, which lays a solid foundation for the design of the subsequent rehabilitation training system. This paper then conducts clinical experiments and analysis on the treatment of mild cognitive impairment, which establishes a treatment group and a control group for comparative experiments. The experimental results showed that the combined effect size OR=2.74 of the meta-analysis, the combined effect size test statistic Z=3.38, WMD=2.42, and the 95% CI was (1.98, 3.06). It indicated that the treatment group had better efficacy. The MMSE score and MoCA score of the treatment group after treatment and training increased by 28.68% and 15.36%, respectively, and the scores were higher than those of the control group. Therefore, the use of VR virtual reality technology combined with acupuncture is of great significance for the rehabilitation and treatment of patients with mild cognitive impairment.

With the continuous progress of medical technology, traditional medicine bottle identification and management methods have problems such as low efficiency and large errors, and innovative solutions are urgently needed. Due to its high sensitivity and rapid response characteristics, this study aims to develop a robot system for intravenous infusion based on nanophotonics sensing to realize accurate identification, grasping and opening of medicine bottles in a dynamic environment, so as to improve the safety and efficiency of intravenous infusion. In this paper, an intelligent robot system with nanophotonics sensor is designed, which uses nanomaterials to produce high sensitivity sensor, so as to realize the information recognition of medicine bottle labels. The robot arm is set up to grasp and open the medicine bottle automatically through visual recognition system and feedback control algorithm. We conducted several rounds of experiments in a simulated environment to evaluate the recognition rate, grab success rate, and opening speed of the system. The experimental results show that the recognition system based on nano photonic sensor in bottle of accuracy and grab the success rate is higher, open time is greatly shortened, compared with traditional methods, the new system in recognition and operation were showed a significant advantage. The study demonstrates the potential of nanophotonics sensing technology in intravenous infusion robots. By optimizing the process of bottle recognition, grasping and opening, the system not only improves the safety and efficiency of medical operations, but is also expected to play a role in future medical automation. Future work will focus on further perfecting the system integration and optimization algorithm, so as to adapt to more complex clinical environment.