For a long time, adipose tissue has been considered an inert tissue involved in fat accumulation [...].
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TAD-SIE: sample size estimation for clinical randomized controlled trials using a Trend-Adaptive Design with a Synthetic-Intervention-Based Estimator.
Trials
January 2025
Department of Electrical and Computer Engineering, Princeton University, Princeton, 08544, NJ, USA.
Background: Phase-3 clinical trials provide the highest level of evidence on drug safety and effectiveness needed for market approval by implementing large randomized controlled trials (RCTs). However, 30-40% of these trials fail mainly because such studies have inadequate sample sizes, stemming from the inability to obtain accurate initial estimates of average treatment effect parameters.
Methods: To remove this obstacle from the drug development cycle, we present a new algorithm called Trend-Adaptive Design with a Synthetic-Intervention-Based Estimator (TAD-SIE) that powers a parallel-group trial, a standard RCT design, by leveraging a state-of-the-art hypothesis testing strategy and a novel trend-adaptive design (TAD).
Optimization of the intron sequences combined with the CMV promoter increases recombinant protein expression in CHO cells.
Sci Rep
January 2025
International Joint Research Laboratory for Recombinant Pharmaceutical Protein Expression System of Henan, Xinxiang Medical University, Xinxiang, China.
To meet the requirements of the biopharmaceutical industry, improving the yield of recombination therapeutic protein (RTP) from Chinese hamster ovary (CHO) cells is necessary. The human cytomegalovirus (CMV) promoter is widely used for RTP expression in CHO cells. To further improve RTP production, we truncated the human CMV intron and further evaluated the effect of four synthetic introns, including ctEF-1α first, EF-1α first, chimeric, and β-globin introns combined with the CMV promoter on recombinant expression levels in transient and stably recombinant CHO cells.
View Article and Find Full Text PDFBone Tissue Engineering: From Biomaterials to Clinical Trials.
Adv Exp Med Biol
January 2025
Department of Stem Cells & Regenerative Medicine, Centre for Interdisciplinary Research, D Y Patil Education Society (Deemed to be University), Kolhapur, India.
Bone tissue engineering is a promising field that aims to rebuild the bone tissue using biomaterials, cells, and signaling molecules. Materials like natural and synthetic polymers, inorganic materials, and composite materials are used to create scaffolds that mimic the hierarchical microstructure of bone. Stem cells, particularly mesenchymal stem cells (MSCs), play a crucial role in bone tissue engineering by promoting tissue regeneration and modulating the immune response.
View Article and Find Full Text PDFC-terminal amides mark proteins for degradation via SCF-FBXO31.
Nature
January 2025
Institute of Molecular Health Sciences, Department of Biology, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland.
During normal cellular homeostasis, unfolded and mislocalized proteins are recognized and removed, preventing the build-up of toxic byproducts. When protein homeostasis is perturbed during ageing, neurodegeneration or cellular stress, proteins can accumulate several forms of chemical damage through reactive metabolites. Such modifications have been proposed to trigger the selective removal of chemically marked proteins; however, identifying modifications that are sufficient to induce protein degradation has remained challenging.
View Article and Find Full Text PDFApolipoprotein B100 acts as a tumor suppressor in ovarian cancer via lipid/ER stress axis-induced blockade of autophagy.
Acta Pharmacol Sin
January 2025
Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China.
Ovarian cancer presents a significant treatment challenge due to its insidious nature and high malignancy. As autophagy is a vital cellular process for maintaining homeostasis, targeting the autophagic pathway has emerged as an avenue for cancer therapy. In the present study, we identify apolipoprotein B100 (ApoB100), a key modulator of lipid metabolism, as a potential prognostic biomarker of ovarian cancer.
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