Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.

Background: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.

Methods: This was a model development study. The data source was the Nashville Biosciences Lp(a) data set, which includes clinical data from the Vanderbilt University Health System.

Review of Attributes and Outcomes of Hospitalized Patients with Alcohol Withdrawal.

Background: Alcohol abuse leads to millions of hospital admissions each year in the United States. Alcohol withdrawal syndrome (AWS) is associated with several serious complications, including seizures, delirium tremens, and death. Benzodiazepines have been the mainstay of treatment for hospitalized patients with alcohol withdrawal.

Niosomal Encapsulation of Anti-Cancer Peptides: A Revolutionary Strategy in Cancer Therapy.

Cancer treatment has evolved significantly over the years, incorporating a range of modalities including surgery, radiation, chemotherapy, and immunotherapy. However, challenges such as drug resistance, systemic toxicity, and poor targeting necessitate innovative approaches. Peptides have gained attention in cancer therapy due to their specificity, potency, and ability to modulate various biological pathways.

Proteomics Reveals Distinctive Host Cell Protein Expression Patterns in Fed-Batch and Perfusion Cell Culture Processes.

Chinese hamster ovary (CHO) cells are widely used to produce recombinant proteins, including monoclonal antibodies (mAbs), through various process modes. While fed-batch (FB) processes have been the standard, a shift toward high-density perfusion processes is being driven by increased productivity, flexible facility footprints, and lower costs. Ensuring the clearance of process-related impurities, such as host cell proteins (HCPs), is crucial in biologics manufacturing.