Development and validation of a nomogram predictive model for cognitive impairment in cerebral small vessel disease: a comprehensive retrospective analysis.

Background: Cerebral small vessel disease (CSVD) is a common neurodegenerative condition in the elderly, closely associated with cognitive impairment. Early identification of individuals with CSVD who are at a higher risk of developing cognitive impairment is crucial for timely intervention and improving patient outcomes. Objective: The aim of this study is to construct a predictive model utilizing LASSO regression and binary logistic regression, with the objective of precisely forecasting the risk of cognitive impairment in patients with CSVD. Methods: The study utilized LASSO regression for feature selection and logistic regression for model construction in a cohort of CSVD patients. The model's validity was assessed through calibration curves and decision curve analysis (DCA). Results: A nomogram was developed to predict cognitive impairment, incorporating hypertension, CSVD burden, apolipoprotein A1 (ApoA1) levels, and age. The model exhibited high accuracy with AUC values of 0.866 and 0.852 for the training and validation sets, respectively. Calibration curves confirmed the model's reliability, and DCA highlighted its clinical utility. The model's sensitivity and specificity were 75.3 and 79.7% for the training set, and 76.9 and 74.0% for the validation set. Conclusion: This study successfully demonstrates the application of machine learning in developing a reliable predictive model for cognitive impairment in CSVD. The model's high accuracy and robust predictive capability provide a crucial tool for the early detection and intervention of cognitive impairment in patients with CSVD, potentially improving outcomes for this specific condition.

Copper-catalyzed enantioselective diyne cyclization via C(sp2)-O bond cleavage.

The functionalization of etheric C-O bonds via C-O bond cleavage is an attractive strategy for the construction of C-C and C-X bonds in organic synthesis. However, these reactions mainly involve C(sp3)-O bond cleavage, and a catalyst-controlled highly enantioselective version is extremely challenging. Here, we report a copper-catalyzed asymmetric cascade cyclization via C(sp2)-O bond cleavage, allowing the divergent and atom-economic synthesis of a range of chromeno[3,4-c]pyrroles bearing a triaryl oxa-quaternary carbon stereocenter in high yields and enantioselectivities. Importantly, this protocol not only represents the first [1,2]-Stevens-type rearrangement via C(sp2)-O bond cleavage, but also constitutes the first example of [1,2]-aryl migration reactions via vinyl cations.

Increasing hotspots density for high-sensitivity SERS detection by assembling array of Ag nanocubes.

Trace analysis has great promise in the fields of disease diagnosis and environment protection. Surface-enhanced Raman scattering (SERS) has wide range of utilization due to its reliable fingerprint detection. However, the sensitivity of SERS still needs to be enhanced. Raman scattering of target molecules around hotspots, the area with extremely strong electromagnetic field, can be highly amplified. Therefore, to increase the density of hotspots is one of the major approaches for enhancing the detection sensitivity of target molecules. In this paper, an ordered array of Ag nanocubes was assembled on a thiol modified silicon substrate as a SERS substrate, which provided high-density hotspots. The detection sensitivity is demonstrated by the limit of detection, which is down to 10-6 nM with Rhodamine 6G as probe molecule. The wide linear range (10-7-10-13 M) and low relative standard deviation (<6.48%) indicate the good reproducibility of the substrate. Furthermore, the substrate can be used for the detection of dye molecules in lake water. This method provides an approach for increasing hotspots of SERS substrate, which could be a promising method to achieve good reproducibility and high sensitivity.

[Small RNA molecules and regulation of spermatogenesis].

Small RNA molecules (small RNAs) have recently emerged as important regulators of gene expression at the post-transcriptional or translation level. Significant progress has recently been made in utilizing small RNAs to elucidate the molecular mechanisms regulating spermatogenesis. There are three major small RNAs: small interfering RNAs (siRNAs), microRNAs (miRNAs), and piwi-interacting RNAs (piRNAs). Small-RNAs have diverse biological functions in meiosis and spermatogenesis, In vitro or in vivo, use of siRNA to knockdown genes is a way to study the function of genes of interest in spermatogenesis. miRNA can be involved in the regulation of mitosis, meiosis, and postmeiosis in spermatogenesis. piRNAs are mainly involved in regulating the process of meiosis and postmeiosis, and repressing retrotransposon transposition in male germline cells. In this paper, we reviewed recent works on the synthesis, mechanism, function, and outlook of small RNAs.