In-line prediction of viability and viable cell density through machine learning-based soft sensor modeling and an integrated systems approach: An industrially relevant PAT case study.

The biopharmaceutical industry is shifting toward employing digital analytical tools for improved understanding of systems biology data and production of quality products. The implementation of these technologies can streamline the manufacturing process by enabling faster responses, reducing manual measurements, and building continuous and automated capabilities. This study discusses the use of soft sensor models for prediction of viability and viable cell density (VCD) in CHO cell culture processes by using in-line optical density and permittivity sensors.

The genome sequence of the Common Wainscot moth, Linnaeus, 1758.

We present a genome assembly from an individual male (the Common Wainscot moth; Arthropoda; Insecta; Lepidoptera; Noctuidae). The genome sequence has a total length of 719.10 megabases.

How Dermatologists Can Aid Nondermatologic Professionals Using the App: Case Analysis.

We found that third-party apps such as Figure 1 were used predominantly by nondermatologist medical personnel for collaboration in medical decision-making related to dermatologic conditions conducted with other health care providers. This finding calls attention to the need for more readily available resources for nondermatologist health care providers encountering patients with skin-related conditions, with the added benefits of trained dermatologists being allies on such medical app platforms, and the platform allowing for recognition of instances when additional consultation or referral to trained dermatologists for more complex cases is appropriate.

The Association of Where Patients with Prostate Cancer Live and Receive Care on Racial Treatment Inequities.

Black individuals are less likely to be treated for prostate cancer even though they are more than twice as likely to die compared to White individuals. The complex causes of these inequities are influenced by social and structural factors, including racism, which contribute to the differential delivery of care. This study investigates how factors related to the location of where individuals live and receive care affect treatment inequities for prostate cancer between Black and White individuals.