Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Objective To investigate the genetic carrier rate of thalassemia and its gene mutation types as well as the distribution characteristics among couples of reproductive age in Dongfang City of Hainan Province,and to provide a basis for making prevention and control strategies against thalassemia.Methods Samples were collected from 1 000 couples undergoing premarital and pregestational screenings for thalassemia in Dongfang City of Hainan Province from September 2012 to March 2013,in which the positive ones in preliminary screening were further tested by genetic diagnoses and the genotypes were retrospectively analyzed.Results Among 1 000 couples,322 spouses were diagnosed with thalassemia gene mutation and the carrying rate was 16.10％ (322/2 000).In those carriers,246 spouses were α-thalassemia and the carrying rate was 12.30％ (246/2 000),accounting for 76.40％(246/322) of all thalassemia carriers,among them,there were 197 cases of α-deficiency genotype,accounting for 61.18％ (197/322),32 carried mutated α-gene,accounting for 9.94％ (32/322),17 carried both deleted and mutated α-gene,accounting for 5.28％ (17/322);43 spouse were β-thalassemia and the carrying rate was 2.15％(43/2 000);33 spouse were both α-and β-thalassemia and the carrying rate was 1.65％ (33/2 000).In spouses diagnosed with α-thalassemia,the major genotype was-α37/αα,accounting for 19.25％ (62/322);the second ranked was-α4.2/αα,accounting for 17.70％ (57/322),and the third ranked was--SEA/αα,accounting for 8.70％ (28/322).In spouses diagnosed with β-thalassemia,the major genotype was CD41-42/N,accounting for 9.63％ (31/322).Conclusions The population carrying rate of thalassemia in Dongfang City of Hainan Province is high,and its major type is α-thalassemia.For the purpose of decreasing the birth rate of thalassemia,major,local public health department should attach great importance to thalassemia prevention,and strengthen premarital and pregestational screening for thalassemia.

OBJECTIVETo study the transport mechanism of honokiol in Caco-2 cell model.

METHODThe analysis was performed on a Kromasil 100-5 C18 column (4.5 mm x 250 mm, 5 microm) eluted with acetonitrile-water (70: 30) as mobile phase. The detection wavelength was set at 203 nm. Two-way transport of honokiol was studied by using Caco-2 cell model, and the effects of time, drug concentration, inhibitor, pH, temperature on the transport of honokiol was investigated. The drug concentrations were determined by high performance liquid chromatography(HPLC) and used to calculate the apparent permeability coefficient.

RESULTThe standard curve of honokiol was Y = 24 044X - 3 763.6 (r = 0.999 8), and the detection limit was 0.04 micromol x L(-1). In Caco-2 cell model, the transport amounts from the top side to the base side of were more than that from the base side to the top side under the same concentration. The transport amounts increased with time both in AP --> BL and BL --> AP directions. Verapamil could improve the transport amounts of AP --> BL. There were no effects of pH on the transport of AP --> BL. Both in AP --> BL and BL --> AP directions, the transport showed temperature dependence.

CONCLUSIONHonokiol is transported through the intestinal mucosa via a passive diffusion mechanism primarily, coexisting with a carrier-mediated transport, at the same time effected by P-gp.

Biological Transport ; Biphenyl Compounds ; analysis ; pharmacokinetics ; Caco-2 Cells ; Chromatography, High Pressure Liquid ; methods ; Diffusion ; Humans ; Lignans ; analysis ; pharmacokinetics ; Permeability