Identification of key genes in sepsis by WGCNA.

When the body damages its own tissues in response to an infection, sepsis develops. Medical treatments are limited. It's important to understand the molecular mechanism behind sepsis pathogenesis and identify potential molecular treatment targets. We made two modules based on how genes work together by using WGCNA analysis. The light-green GSE131761 module and the blue GSE137342 module had the strongest links to sepsis. A gene ontology (GO) analysis showed that most of the genes in the lightgreen module were involved in the inflammatory response, specific granule, and immune receptor activity. Most of the genes in the blue module were significantly more likely to have the GO terms proteasomal protein catabolic process, ubiquitin ligase complex, and ubiquitin-like protein transferase activity. The KEGG analysis showed that the genes in module lightgreen were mostly involved in the TNF signaling pathway, while the genes in module blue were mostly involved in the Prion disease pathway. There were two hub genes that were found. In the end, ANKRD22 and VNN1 were singled out as crucial genes. This study used WGCNA to investigate sepsis-associated susceptibility modules and genes. Our study identified two modules and two key genes as essential components in sepsis etiology, which may improve our understanding of its molecular mechanisms.

[A developmental research on wild Dipsacus asper in Chongqing Wulong district].

In order to study the distribution and dynamics growth of wild Dipsacus asper resources in the Wulong district of Chongqing, 9 sample plots were selected for 12 consecutive months in the natural distribution area of the D. asper in Wulong district by using the sample line + plot survey method to conduct a field survey. The results showed that D.asper was distributed in forest edge wasteland or shrub-grassland, and growbetter with loose yellow-brownsoil or red soil, and poor with lithologic soil or impounded surface water.The growth curve of the plant height from June to July and the ground fresh weight from July to August showed a turning point, it might consume large amounts of nutrients during its flowering period, resulting in the restriction of vegetative growth.The highest temperature in the distribution area of D.asperoides in Wulong district is less than 30 °C, the minimum temperature is about 0 °C, and the rainfall is 1 241-1 392 mm. Its growth environment is no severecold in winter, no heat in summer, and abundant rainfall.The main growth stage of D.asper is from July to October, and the range of root dry rate was 0.162 5-0.239 7 in Xiangkou, 0.154 9-0.223 6 in Baima Mountain, and 0.143 7-0.203 3 Xiannv Mountain. The vegetative growth and dry matter accumulation synchronized in the main growth stage, and the accumulation rate of dry matter was faster than that of vegetative growth. The correlation analysis between indicators and root fresh weight showed that the fresh weight of the aerial part and root fresh weight had the best correlation.

Biosimilars: Key regulatory considerations and similarity assessment tools.

A biosimilar drug is defined in the US Food and Drug Administration (FDA) guidance document as a biopharmaceutical that is highly similar to an already licensed biologic product (referred to as the reference product) notwithstanding minor differences in clinically inactive components and for which there are no clinically meaningful differences in purity, potency, and safety between the two products. The development of biosimilars is a challenging, multistep process. Typically, the assessment of similarity involves comprehensive structural and functional characterization throughout the development of the biosimilar in an iterative manner and, if required by the local regulatory authority, an in vivo nonclinical evaluation, all conducted with direct comparison to the reference product. In addition, comparative clinical pharmacology studies are conducted with the reference product. The approval of biosimilars is highly regulated although varied across the globe in terms of nomenclature and the precise criteria for demonstrating similarity. Despite varied regulatory requirements, differences between the proposed biosimilar and the reference product must be supported by strong scientific evidence that these differences are not clinically meaningful. This review discusses the challenges faced by pharmaceutical companies in the development of biosimilars.

A three-component dicamba O-demethylase from Pseudomonas maltophilia, strain DI-6: purification and characterization.

Dicamba O-demethylase is a multicomponent enzyme that catalyzes the conversion of the herbicide 2-methoxy-3,6-dichlorobenzoic acid (dicamba) to 3,6-dichlorosalicylic acid (DCSA). The three components of the enzyme were purified and characterized. Oxygenase(DIC) is a homotrimer (alpha)3 with a subunit molecular mass of approximately 40 kDa. FerredoxinDIC and reductaseDIC are monomers with molecular weights of approximately 14 and 45 kDa, respectively. EPR spectroscopic analysis suggested the presence of a single [2Fe-2S](2+/1+) cluster in ferredoxinDIC and a single Rieske [2Fe-2S](2+; 1+) cluster within oxygenaseDIC. Consistent with the presence of a Rieske iron-sulfur cluster, oxygenaseDIC displayed a high reduction potential of E(m,7.0) = -21 mV whereas ferredoxinDIC exhibited a reduction potential of approximately E(m,7.0) = -171 mV. Optimal oxygenaseDIC activity in vitro depended on the addition of Fe2+. The identification of formaldehyde and DCSA as reaction products demonstrated that dicamba O-demethylase acts as a monooxygenase. Taken together, these data suggest that oxygenaseDIC is an important new member of the Rieske non-heme iron family of oxygenases.