A novel all-in-one target-powered entropy-driven dynamic DNA networks to regulate the activity of CRISPR/AsCas12a for enhanced DNA detection.

Background: The non-enzyme autonomous DNA nanodevices have been developed to detect various analytes through the programmability of Watson-Crick base pairing. Nevertheless, by comparison with enzymatic biosensors, the usage of enzyme-free DNA networks to create biosensors for testing low amounts of targets is still subject to the finite number of cycles. Besides, these biosensors still require the incorporation of other amplification strategies to improve the sensitivity, which complicates the detection workflow and lacks of a uniform compatible system to respond to the target in one pot.

Metabolomic characterization of COVID-19 survivors in Jilin province.

Background: The COVID-19 pandemic has escalated into a severe global public health crisis, with persistent sequelae observed in some patients post-discharge. However, metabolomic characterization of the reconvalescent remains unclear.

Methods: In this study, serum and urine samples from COVID-19 survivors (n = 16) and healthy subjects (n = 16) underwent testing via the non-targeted metabolomics approach using UPLC-MS/MS.

Evaluation of Trace Elements Levels and Construction of Auxiliary Prediction Model in Patients with Diabetes Ketoacidosis in Type 1 Diabetes.

Background: Trace elements play an important role in reflecting physical metabolic status, but have been rarely evaluated in diabetes ketoacidosis (DKA). Since clinical biochemical parameters are the first-line diagnostic data mastered by clinical doctors and DKA has a rapid progression, it is crucial to fully utilize clinical data and combine innovative parameters to assist in assessing disease progression. The aim of this study was to evaluate the levels of trace elements in DKA patients, followed by construction of predictive models combined with the laboratory parameters.

Evaluation among trace elements, clinical parameters and type 1 diabetes according to sex: A new sight of auxiliary prediction in negative insulin auto-antibodies population.

Background: Type 1 diabetes (T1D) exhibited sex-specific metabolic status including oxidative stress with dynamic change of trace elements, which emphasized the importance of the evaluation of trace elements according to sex. Besides, the most significant characteristic, insulin auto-antibodies, could not be found in all T1D patients, which needed the auxiliary prediction of clinical parameters. And it would benefit the early detection and treatment if some high-risk groups of T1D could predict and prevent the occurrence of disease through common clinical parameters.

Establishment of gender- and age-specific reference intervals for serum liver function tests among the elderly population in northeast China: a retrospective study.

Introduction: Reference intervals (RIs) for younger population may not apply to the elderly population. The aim of this study was to establish gender- and age-specific RIs for serum liver function tests among the elderly population and to compare with younger population RIs currently used in China and other countries.

Materials And Methods: This was a retrospective study, and subjects (≥ 18 year-old) were recruited from the laboratory information system (LIS) at the First Hospital of Jilin University between April 2020 and April 2021.

An indirect approach for reference intervals establishment of immunoglobulin A, G and M: the combination of laboratory database and statistics.

Immunoglobulins are affected by sex, age and region, so it is necessary to establish suitable reference intervals (RIs) for clinical diagnosis. Various statistical methods were used to calculate RIs, but there has been a lack of comparison among the methods. Research based on immunoglobulin RIs establishment with various methods would provide a methodological basis for further research.

The indirect method in the establishment of reference intervals for complement 3 and complement 4: A retrospective study.

Objective: The establishment of reference intervals (RIs) for complement 3 (C3) and complement 4 (C4) is rare, especially by indirect methods. Therefore, this study aims to establish regional RIs for C3 and C4 by an indirect method, using relevant statistical methods.

Methods: Total of 12,313 data points for C3 and 12,125 data points for C4 were obtained from the First Hospital of Jilin University's database in China and standardised using the Tukey and Box-Cox statistical methods.

A Contemporary Insight of Metabolomics Approach for Type 1 Diabetes: Potential for Novel Diagnostic Targets.

High-throughput omics has been widely applied in metabolic disease, type 1 diabetes (T1D) was one of the most typical diseases. Effective prevention and early diagnosis are very important because of infancy and persistent characteristics of T1D. The occurrence and development of T1D is a chronic and continuous process, in which the production of autoantibodies (ie serum transformation) occupies the central position.