Advances in molecular biotechnology have resulted in the generation of numerous potential production strains. Because every strain can be screened under various process conditions, the number of potential cultivations is multiplied. Exploiting this potential without increasing the associated timelines requires a cultivation platform that offers increased throughput and flexibility to perform various bioprocess screening protocols. Currently, there is no commercially available fully automated cultivation platform that can operate multiple microbial fed-batch processes, including at-line sampling, deep freezer off-line sample storage, and complete data handling. To enable scalable high-throughput early-stage microbial bioprocess development, a commercially available microbioreactor system and a laboratory robot are combined to develop a fully automated cultivation platform. By making numerous modifications, as well as supplementation with custom-built hardware and software, fully automated milliliter-scale microbial fed-batch cultivation, sample handling, and data storage are realized. The initial results of cultivations with two different expression systems and three different process conditions are compared using 5 L scale benchmark cultivations, which provide identical rankings of expression systems and process conditions. Thus, fully automated high-throughput cultivation, including automated centralized data storage to significantly accelerate the identification of the optimal expression systems and process conditions, offers the potential for automated early-stage bioprocess development.
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http://dx.doi.org/10.1002/biot.201800625 | DOI Listing |
Front Public Health
January 2025
Department of Ophthalmology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Introduction: Diabetic retinopathy grading plays a vital role in the diagnosis and treatment of patients. In practice, this task mainly relies on manual inspection using human visual system. However, the human visual system-based screening process is labor-intensive, time-consuming, and error-prone.
View Article and Find Full Text PDFAnal Chim Acta
February 2025
Departamento de Medio Ambiente y Agronomía, INIA-CSIC, Carretera de A Coruña km. 7.5, 28040, Madrid, Spain. Electronic address:
Background: At present, 3D printing technology is becoming increasingly popular in analytical chemistry because it enables the rapid and cost-effective manufacture of sample preparation devices, particularly in flow-based operation, opening up new opportunities for the development of automated analytical methods. In parallel, the use of miniaturized methods and sustainable solvents in sample preparation is highly recommended. Accordingly, in this work, a 3D-printed millifluidic device was designed and used for the on-line natural deep eutectic solvent (NADES)-based liquid phase microextraction (LPME) coupled to a spectrofluorometer for, as a proof of concept, the determination of thiabendazole (TBZ) in fruit juice samples.
View Article and Find Full Text PDFJ Neurosci Methods
January 2025
School of Mathematics and Statistics, Ludong University, Yantai 264025, China. Electronic address:
Background: Parkinson's disease (PD), the second most common neurodegenerative disease in the world, is usually not diagnosed until the later stages of the disease, when patients might have already missed the best treatment period. Therefore, more effective prediction methods based on artificial intelligence (AI) are needed to assist physicians in timely diagnosis.
New Methods: An explainable deep learning-based early Parkinson's disease diagnostic model, Parkinson's Integrative Diagnostic Gated Network (PIDGN), was designed by fusing Single Nucleotide Polymorphism (SNP) and brain sMRI data.
JMIR Form Res
January 2025
Department of Computer Science, Purdue University, West Lafayett, IN, United States.
Background: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care providers need to rely predominantly on verbal strategies rather than typical nonverbal cues to effectively engage patients. Hence, the typical patient engagement behaviors are now different, and health care provider training on telehealth patient engagement is unavailable or quite limited.
View Article and Find Full Text PDFDentomaxillofac Radiol
January 2025
Department of Oral and Maxillofacial Radiology, School of Dentistry, Pusan National University, Yangsan, 50612, Korea.
Objectives: This study aimed to develop an automated method for generating clearer, well-aligned panoramic views by creating an optimized three-dimensional (3D) reconstruction zone centered on the teeth. The approach focused on achieving high contrast and clarity in key dental features, including tooth roots, morphology, and periapical lesions, by applying a 3D U-Net deep learning model to generate an arch surface and align the panoramic view.
Methods: This retrospective study analyzed anonymized cone-beam CT (CBCT) scans from 312 patients (mean age 40 years; range 10-78; 41.
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