Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study.

Background: This study aimed to identify pathogens and factors that predict the outcome of severe COVID-19 by utilizing metagenomic next-generation sequencing (mNGS) technology. Methods: We retrospectively analyzed data from 56 severe COVID-19 patients admitted to our hospital between December 2022 and March 2023. We analyzed the pathogen types and strains detected through mNGS and conventional microbiological testing and collected general patient information. Results: In this study, 42 pathogens were detected using mNGS and conventional microbiological testing. mNGS had a significantly higher detection rate of 90.48% compared to 71.43% for conventional testing (P=0.026). A total of 196 strains were detected using both methods, with a significantly higher detection rate of 70.92% for mNGS compared to 49.49% for conventional testing (P=0.000). The 56 patients were divided into a survival group (33 cases) and a death group (23 cases) based on clinical outcomes. The survival group had significantly lower age, number of pathogens detected by mNGS, number of pathogens detected by conventional testing, APACHE-II score, SOFA score, high-sensitivity troponin, creatine kinase-MB subtype, and lactate dehydrogenase compared to the death group (P<0.05). Multivariate logistic regression analysis showed that these factors were risk factors for mortality in severe COVID-19 patients (P<0.05). In contrast, ROC curve analysis revealed that these factors had diagnostic values for mortality, with AUC values ranging from 0.657 to 0.963. The combined diagnosis of these indicators had an AUC of 0.924. Conclusions: The use of mNGS technology can significantly enhance the detection of pathogens in severe cases of COVID-19 and also has a solid ability to predict clinical outcomes.

Risk factors for cervical instability in rheumatoid arthritis: a meta-analysis.

Introduction: The aim of the study was to evaluate the risk factors for cervical instability in rheumatoid arthritis (RA). Material and methods: Computer searches were conducted in PubMed, Embase, Cochrane Library, the China National Knowledge Infrastructure (CNKI) database, the Wan Fang database, the Chinese Scientific Journal Databases (VIP) database, and the Chinese Biomedical Literature database (CBM) from their establishment until November 2022. Results: A total of 8 articles were included in this study, including 1 cross-sectional study, 5 case-control studies, and 2 cohort study, including 3078 patients with RA. Meta-analysis results showed that: male sex (OR = 1.70, 95% CI: 1.19-2.42), course of disease (OR = 1.72, 95% CI: 1.29-2.28), long-term glucocorticosteroid use (OR = 2.84, 95% CI: 1.97-2.40), Steinbrocker staging (OR = 2.30, 95% CI: 1.61-3.28), disability at baseline (OR = 24.57, 95% CI: 5.51-109.60), peripheral joint destruction (OR = 2.24, 95% CI: 1.56-3.21), Steinbrocker stage I-IV progression to disability (OR = 20.08, 95% CI: 4.18-96.53), and previous joint surgery (OR = 1.54, 95% CI: 1.06-2.26) are the main risk factors for cervical instability in RA. Conclusions: There are many risk factors for cervical instability in RA. In clinical practice, special attention should be paid to patients who are male, have a longer course of disease, have long-term glucocorticosteroid use, have previous joint surgery, have peripheral joint damage, and develop disability in Steinbrocker stage I-IV. Attention should be paid to the high-risk groups mentioned above, and effective measures such as early screening and full monitoring should be taken to prevent the occurrence of cervical instability in RA.

Analysis of Performance Degradation in Lithium-Ion Batteries Based on a Lumped Particle Diffusion Model.

The analysis of performance degradation in lithium-ion batteries plays a crucial role in achieving accurate and efficient fault diagnosis as well as safety management. This paper proposes a method for studying the degradation pattern of lithium-ion batteries and establishing the structure-activity relationship between internal and external parameters by employing a lumped particle diffusion model. To simulate real-world operating conditions, a cycle life test was conducted with the constant current-constant voltage (CC-CV) charge mode and the discharge mode under New European Driving Cycle (NEDC) working condition. The test aimed to analyze the variations in the external macroscopic characteristic parameters of the battery. Building upon this analysis, a lumped particle diffusion model was constructed, and the model parameters were identified using the Levenberg-Marquardt (L-M) algorithm. Subsequently, the ohmic, activation, and concentration losses of the battery under different aging conditions were determined, revealing the internal state evolution during the degradation process of lithium-ion batteries. The findings indicate that the lumped particle diffusion model provides a comprehensive explanation of the internal mechanisms contributing to the performance degradation of lithium-ion batteries. Moreover, the proposed method offers a novel perspective for the real-time quantitative analysis of lithium-ion battery performance degradation.

A sensitive sensing system based on fluorescence dipeptide nanoparticles for sulfadimethoxine determination.

Various types of fluorescent nanoparticles have been proposed for the detection of veterinary drug residues in food. However, structure-induced fluorescence nanoparticles with biodegradability and the capacity to conjugate with molecular recognition elements are lacking. Here, a biodegradable tryptophan-phenylalanine dipeptide-based nanomaterial was assembled and modified with a sulfadimethoxine aptamer (TPNPs@aptamer). Then, a novel and efficient fluorescence sensing strategy, based on TPNPs@aptamer and BHQ1-labeled single-stranded DNA (BHQ1@cDNA), was developed for sulfadimethoxine determination. Under optimal conditions, the fluorescence was linear in the range of 0-200 ng/mL sulfadimethoxine with a detection limit of 1.47 ng/mL (S/N = 3). Satisfactory recoveries of standard additions were found between 92.88 % and 114.15 % for water and milk samples with a relative standard deviation less than 5.0 %, suggesting that the proposed fluorescence sensing strategy can be applied reliably in sulfadimethoxine analysis of liquid foods.

A reliable upconversion nanoparticle-based immunochromatographic assay for the highly sensitive determination of olaquindox in fish muscle and water samples.

Olaquindox residues in food from its illegal use has received great attention. Here, an immunoassay strategy integrating an upconversion nanoparticle (UCNP)-based immunochromatographic strip with a fluorescence reader was proposed for the highly selective and sensitive detection of olaquindox. Polyacrylic acid-functionalized UCNPs were synthesized using a simple ligand exchange process and combined with an olaquindox polyclonal antibody to form a fluorescent probe. This approach achieved a sensitive response and specific recognition of olaquindox. A convenient upconversion fluorescence reader was introduced to implement accurate and sensitive quantitative analysis of olaquindox based on the fluorescence intensity of control and test lines on a strip. Under optimal conditions, the method demonstrated a favorable linear range (0-50 ng/mL) and sensitive detection (1.42 ng/mL, S/N = 3). This method was applied successfully to determine olaquindox in fish muscle and water samples, and results were consistent with an HPLC approach, and considered a promising strategy for monitoring olaquindox residuals.

A Systematic Review and Meta-Analysis of the Efficacy of Uterine Artery Embolization in the Treatment of Endometriosis.

Objective: To compare the efficacy of uterine artery embolization (UAE) with traditional methods for treating endometriosis. Methods: The randomized controlled trials of uterine artery embolization and other medical treatments for endometriosis in PubMed, Embase, Web of Science, Cochrane Library, China Journal Full-Text Database, Wanfang Database, VIP Database, and China Biomedical Literature Database were retrieved by computer. The search time was up to June 2022. The quality of articles was evaluated by Cochrane ROB 2.0, and meta-analysis was performed by Stata15.1 software. Results: 7 studies were finally included. Meta-analysis showed that the serum CA125 level after uterine artery embolization was significantly lower than that in the control group (SMD = -0.85, 95%CI (-1.12, -0.59)], and the postoperative visual analogue scale (VAS) of dysmenorrhea was significantly lower than that in the control group (SMD = -1.86, 95%CI (-2.21, -1.50)) There was no significant difference in the effective rate, FSH level, E2 level, and LH level between the two groups. Conclusion: UAE can effectively reduce the VAS score of dysmenorrhea and serum CA125 level for treating endometriosis. However, due to the limitation of the quality of included articles, more large sample size and high quality RCTs are needed to provide stronger evidence-based medicine evidence for clinical practice.