Development and validation of immune-based biomarkers and deep learning models for Alzheimer's disease.

Background: Alzheimer's disease (AD) is the most common form of dementia in old age and poses a severe threat to the health and life of the elderly. However, traditional diagnostic methods and the ATN diagnostic framework have limitations in clinical practice. Developing novel biomarkers and diagnostic models is necessary to complement existing diagnostic procedures. Methods: The AD expression profile dataset GSE63060 was downloaded from the NCBI GEO public database for preprocessing. AD-related differentially expressed genes were screened using a weighted co-expression network and differential expression analysis, and functional enrichment analysis was performed. Subsequently, we screened hub genes by random forest, analyzed the correlation between hub genes and immune cells using ssGSEA, and finally built an AD diagnostic model using an artificial neural network and validated it. Results: Based on the random forest algorithm, we screened a total of seven hub genes from AD-related DEGs, based on which we confirmed that hub genes play an essential role in the immune microenvironment and successfully established a novel diagnostic model for AD using artificial neural networks, and validated its effectiveness in the publicly available datasets GSE63060 and GSE97760. Conclusion: Our study establishes a reliable model for screening and diagnosing AD that provides a theoretical basis for adding diagnostic biomarkers for the AD gene.

Effects of vegetation restoration and environmental factors on understory vascular plants in a typical karst ecosystem in southern China.

Understory vegetation is an important component in most forest ecosystems. It is very important for soil and water conservation in karst region, study on understory will provide valuable information for understanding the interaction mechanism between understory flora and karst environment. Thirty-two plots were sampled in three vegetation types along with a restoration gradient (shrubland, forest-shrub transition, and mixed-species broadleaf forest) in typical karst mountains in Southwest Guangxi, China. Overstory trees, understory vascular plants, soil nutrients, and topographic factors were recorded in each 400-m2 plot. Multivariate statistics were used, including the multi-response permutation procedure (MRPP), indicator species analysis, and canonical correlation analysis (CCA). MRPP showed understory species composition significantly differed among the three vegetation types, with the greatest difference between the shrubland and the mixed forest. Twenty-one understory species were identified as significant indicator species, with 13 species being identified as indicators of the shrubland, two of forest-shrub transition, and six of the mixed forest. Light-demanding herbaceous seed plants were common in shrubland, while shade-tolerant calcicole assembled under the mixed forest. Forward selection of CCA ordination revealed that understory plant distribution was most strongly influenced by elevation, followed by soil pH, the concentration of total potassium and exchangeable calcium, slope aspect, slope degree, and the concentration of available potassium. The result reveals that vegetation types affect understory species composition by modifying understory environments. Elevation affects the spatial distribution of vegetation and soil factors, and then the understory plants. Meanwhile, soil Ca content also plays a key role in the understory species distribution. Understory diversity increased with increasing canopy structure complexity from shrubland to mixed-species forest. Thus, it is necessary to take measures to promote natural vegetation restoration and to protect the mixed forests in degraded karst areas.

[Impacts of digging Phascolosoma esculenta on the growth of mangrove Avicennia marina seedlings: a simulation study].

Digging Phascolosoma esculenta to increase income is one of the main causes leading to the degradation of China mangroves. In order to understand the impact mechanisms of digging P. esculenta on the mangrove growth and to select indicators to evaluate the mangrove health, a simulative study was conducted to clarify the impacts of digging depth, radian, and frequency on the growth of 1-year old Avicennia marina seedlings, with the indices seedling height, basal diameter, single leaf area, specific leaf area, total biomass, and dead root dry mass measured. The results showed that digging activities decreased the increment of seedling height and basal diameter, single leaf area, specific leaf area, and total biomass significantly, and increased the dead root dry mass markedly. Digging depth and radian had obvious effects on the growth of A. marina seedlings, but digging frequency had minor effects. When the digging depth was < 5 cm, digging radian was < 240 degrees, and digging frequency was < 2 times per month, the damage to the seedlings was slighter; but when the digging depth was > 5 cm, the damage was quite serious.

Highly diastereoselective enolate addition of O-protected alpha-hydroxyacetate to (S(R))-tert-butanesulfinylimines: synthesis of taxol side chain.

The taxol side chain (S(R),2R,3S)-N-tert-butanesulfinyl-O-Boc-3-phenylisoserine benzyl ester 4c was synthesized through a lithium enolate addition of O-Boc-alpha-hydroxyacetate benzyl ester 5c to benzylidene (S(R))-tert-butanesulfinamide 6a in excellent yield and diastereoselectivity. By similar approach, a series of enantiopure 3-substituted isoserine benzyl esters 4 useful for the semi-syntheses of taxol derivatives were also prepared in high to excellent yields and diastereoselectivities. The diastereoselective addition mechanism was discussed on the basis of the experimental observation.