Integration of single-cell sequencing with machine learning and Mendelian randomization analysis identifies the NAP1L1 gene as a predictive biomarker for Alzheimer's disease.

Background: The most effective approach to managing Alzheimer's disease (AD) lies in identifying reliable biomarkers for AD to forecast the disease in advance, followed by timely early intervention for patients. Methods: Transcriptomic data on peripheral blood mononuclear cells (PBMCs) from patients with AD and the control group were collected, and preliminary data processing was completed using standardized analytical methods. PBMCs were initially segmented into distinct subpopulations, and the divisions were progressively refined until the most significantly altered cell populations were identified. A combination of high-dimensional weighted gene co-expression analysis (hdWGCNA), cellular communication, pseudotime analysis, and single-cell regulatory network inference and clustering (SCENIC) analysis was used to conduct single-cell transcriptomics analysis and identify key gene modules from them. Genes were screened using machine learning (ML) in the key gene modules, and internal and external dataset validations were performed using multiple ML methods to test predictive performance. Finally, bidirectional Mendelian randomization (MR) analysis, regional linkage analysis, and the Steiger test were employed to analyze the key gene. Result: A significant decrease in non-classical monocytes was detected in PMBC of AD patients. Subsequent analyses revealed the inherent connection of non-classical monocytes to AD, and the NAP1L1 gene identified within its gene module appeared to exhibit some association with AD as well. Conclusion: The NAP1L1 gene is a potential predictive biomarker for AD.

Deciphering mitochondrial dysfunction: Pathophysiological mechanisms in vascular cognitive impairment.

Vascular cognitive impairment (VCI) encompasses a range of cognitive deficits arising from vascular pathology. The pathophysiological mechanisms underlying VCI remain incompletely understood; however, chronic cerebral hypoperfusion (CCH) is widely acknowledged as a principal pathological contributor. Mitochondria, crucial for cellular energy production and intracellular signaling, can lead to numerous neurological impairments when dysfunctional. Recent evidence indicates that mitochondrial dysfunction-marked by oxidative stress, disturbed calcium homeostasis, compromised mitophagy, and anomalies in mitochondrial dynamics-plays a pivotal role in VCI pathogenesis. This review offers a detailed examination of the latest insights into mitochondrial dysfunction within the VCI context, focusing on both the origins and consequences of compromised mitochondrial health. It aims to lay a robust scientific groundwork for guiding the development and refinement of mitochondrial-targeted interventions for VCI.

Adsorption of Acid Red 73 on copper dithiocarbamate precipitate-type solid wastes.

Three solid wastes, copper N,N'-bis(dithiocarboxy)piperazine ([CuBDP](n)), copper diethyldithiocarbamate (Cu(DDTC)(2)) and copper dimethyldithiocarbamate (Cu(DMTC)(2)), were prepared and tested as adsorbents to remove Acid Red 73 from wastewater. It was found that the three precipitates all could effectively adsorb the dye but their adsorption abilities were rather different. The maximum adsorption amounts of the coordination polymer precipitate [CuBDP](n) reached as high as 364mg g(-1), much greater than those of Cu(DDTC)(2) and Cu(DMTC)(2) (42.9 and 37.8mg g(-1), respectively). The investigation of adsorption models showed these adsorption processes followed the pseudo-second-order kinetic equation and the adsorption balances could be described with both Langmuir and Freundlich isotherms, but the latter seemed to be more suitable. Their adsorption nature was inferred to be physical adsorption and mainly depended on the hydrophobic interaction between these precipitates and Acid Red 73. This is the first example for the reutilization of metal dithiocarbamate precipitates as solid wastes to date.

Comparative investigation of N,N'-bis-(dithiocarboxy)piperazine and diethyldithiocarbamate as precipitants for Ni(II) in simulated wastewater.

The performances of a coordination polymerization precipitant, N,N'-bis-(dithiocarboxy)piperazine (BDP) were compared with the widely used heavy metal precipitant, diethyldithiocarbamate (DDTC), through the treatment of three kinds of nickel-containing wastewaters, NiSO(4), nickel citrate (NiCA) and Ni(2+)-dye. Results indicated that both BDP and DDTC at their stiochiometric doses could reduce 50.00 mg l(-1) free nickel(II) to lower than 1.0 mg l(-1) (discharge limit of nickel ions in China) and 10% precipitants doses increase could treat NiCA containing 50.00 mg l(-1) Ni(2+) to meet the discharge limit. But [NiBDP](n) coordination polymerization precipitates had more rapid settling speed than Ni(DDTC)(2) precipitates. It was also observed that BDP could still partly remove Reactive Brilliant Red X-3B from Ni(II)-dye integrated wastewater through the adsorption of the precipitates [NiBDP](n), in addition to precipitating Ni(II). A 1:1 stiochiometric dose of BDP/Ni(II) could decrease Ni(II) from 50.00 to 0.87 mg l(-1), and simultaneously reduce the dye from 30.00 to 19.52 mg l(-1).