Xiaofei Zeng

The life cycle of genome builds spans interlocking pillars of assembly, annotation, and comparative genomics to drive biological insights. While tools exist to address each pillar separately, there is a growing need for tools to integrate different pillars of a genome project holistically. For example, comparative approaches can provide quality control of assembly or annotation; genome assembly, in turn, can help to identify artifacts that may complicate the interpretation of genome comparisons. The JCVI library is a versatile Python-based library that offers a suite of tools that excel across these pillars. Featuring a modular design, the JCVI library provides high-level utilities for tasks such as format parsing, graphics generation, and manipulation of genome assemblies and annotations. Supporting genomics algorithms like MCscan and ALLMAPS are widely employed in building genome releases, producing publication-ready figures for quality assessment and evolutionary inference. Developed and maintained collaboratively, the JCVI library emphasizes quality and reusability.

The overexpression of cyclic AMP (cAMP)-dependent protein kinase (PKA) has been reported in patients with cancer, and PKA inhibitors have been tested in clinical trials as a novel cancer therapy. The present study was designed to characterize the population distribution of extracellular activity of cAMP-dependent protein kinase (ECPKA) and its potential value as a biomarker for cancer detection and monitoring of cancer therapy. The population distribution of ECPKA activity was determined in serum samples from a Chinese population consisting of a total of 603 subjects (374 normal healthy volunteers and 229 cancer patients). The serum ECPKA was determined by a validated sensitive radioassay, and its diagnostic values (including positive and negative predictive values) were analyzed. The majority of normal subjects (>70%) have undetectable or very low levels of serum ECPKA. In contrast, the majority of cancer patients (>85%) have high levels of ECPKA. The mean ECPKA activity in the sera of cancer patients was 10.98 units/mL, 5-fold higher than that of the healthy controls (2.15 units/mL; P < 0.001). In both normal subjects and cancer patients, gender and age had no significant influence on the serum ECPKA. Among factors considered, logistic analysis revealed that the disease (cancer) is the only factor contributing to the elevation of ECPKA activity in cancer patients. In conclusion, ECPKA may function as a cancer marker for various human cancers and can be used in cancer detection and for monitoring response to therapy with other screening or diagnostic techniques.

The endothelial-to-mesenchymal transition (EMT) of glomerular vascular endothelial cells is considered to be pivotal in diabetic nephropathy (DN). The risk of DN can be decreased by losartan, but the potential molecular mechanism(s) are not fully understood. Extensive data show that the EMT occurs in proximal tubular endothelial cells resulting in an endothelial phenotype switch (fibrotic matrix accumulation), consequently enhancing the development of renal interstitial fibrosis. Here, we found that losartan significantly ameliorated DN-induced renal fibrosis progression via inhibition of the EMT in mice. In vivo experiments suggested that losartan significantly alleviated microalbuminuria and pathologic changes under high-fat diet-induced hyperglycemia stress. Immunohistochemistry indicated that losartan suppressed the EMT in glomeruli. In addition, losartan decreased oxidative stress damage and inhibited the transforming growth factor (TGF)-β1/Smad pathway. Furthermore, consistent changes were detected in vitro where losartan markedly inhibited the EMT and TGF-β1/Smad pathway induced by high glucose in glomerular endothelial cells. Together, these results suggested that losartan could alleviate the EMT in glomeruli via inhibition of oxidative stress damage and the TGF-β1/Smad signaling pathway under hyperglycemia stress.