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The limitations of conventional urine culture methods can be avoided by using culture-independent approaches like polymerase chain reaction (PCR) and next-generation sequencing (NGS). However, the efficacy of these approaches in this setting is still subject to contention. PRISMA-compliant searches were performed on MEDLINE/PubMed, EMBASE, Web of Sciences, and the Cochrane Database until March 2023. The included articles compared PCR or NGS to conventional urine culture for the detection of urinary tract infections (UTIs). RevMan performed meta-analysis, and the Cochrane Risk of Bias Assessment Tool assessed study quality. A total of 10 selected studies that involved 1,291 individuals were included in this meta-analysis. The study found that PCR has a 99% sensitivity and a 94% specificity for diagnosing UTIs. Furthermore, NGS was shown to have a sensitivity of 90% for identifying UTIs and a specificity of 86%. The odds ratio (OR) for PCR to detect Gram-positive bacteria is 0.50 (95% confidence interval [CI] 0.41–0.61), while the OR for NGS to detect Gram-negative bacteria is 0.23 [95% CI 0.09–0.59]. UTIs are typically caused by Gram-negative bacteria like Escherichia coli and Gram-positive bacteria like Staphylococci and Streptococci. PCR and NGS are reliable, culture-free molecular diagnostic methods that, despite being expensive, are essential for UTI diagnosis and prevention due to their high sensitivity and specificity.

The Asia–Pacific countries are highly diverse in health and economic conditions that may impact vaccine access and uptake. Our study aimed to characterize patterns of health access to DTP-based combination vaccines in 10 countries from 2019 to 2022 using the IQVIA-MIDAS database. The availability, affordability, and accessibility were compared across countries by national health and economic performance indicators using Spearman's rank correlation coefficient. Our findings showed that the three aspects of access to DTP-based vaccines varied substantially in the Asia–Pacific region, with higher levels in countries with better health and economic performance. Affected by the COVID-19 pandemic, vaccine accessibility fluctuates significantly in lower-income countries, with DTP coverage rates falling by more than 14% in the Philippines and Indonesia between 2019 and 2021. For availability and affordability, Singapore and Malaysia from high-income groups were largely affected, which may be related to health expenditure as a percentage of gross domestic product (Coefficient = 0.39, p = 0.03). Our study indicates that greater attention needs to be paid to national health expenditure and routine immunization services to improve vaccine disparities and increase the robustness and resilience of the vaccine supply chain during public health emergencies. [ABSTRACT FROM AUTHOR]

Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs—ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT—that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis. [ABSTRACT FROM AUTHOR]

Background: The prevalence of pain comorbid and anxiety/depression in clinical observations has been high, and the number of related publications has increased in recent years. Nevertheless, few studies have used bibliometric methods to analyze the scientific research on comorbid pain and depression/anxiety. The aim of this study was to systematically examine the trends in global scientific research on comorbid pain and depression/anxiety from 2012 to 2022.Methods: Papers published between 2012 and 2022 were identified in the Web of Science database. Publications that examined comorbid pain and depression/anxiety were included. The language was limited to English. CiteSpace, Excel and VOSviewer were used to analyze the volume of publications, countries, institutions, authors, cocited authors, and keywords.Results: A total of 30,290 papers met the inclusion criteria of the study. Using CiteSpace, VOSviewer and Excel, the results showed that the United States (10,614 publications), Harvard University (1195 publications), and Jensen, Mark P. (77 publications) were the most productive country, institution, and author, respectively. The hotspots and frontiers were "relationship between depression and pain", "gender differences in pain and depression/anxiety domains", "study of specific pain types with depression/anxiety", "treatment of pain combined with anxiety/depression", and "effects of COVID-19 on patients with pain combined with depression/anxiety".Conclusion: These findings indicate a growing interest in the field of comorbid pain and depression/anxiety. The research has been broad and deep, but there is still much room for growth. Furthermore, there is a need for more mature global collaborative networks as well as more high-quality research results in the future. [ABSTRACT FROM AUTHOR]

In the forming process of fiber-reinforced metal laminates (FMLs) product, the exploratory compound forming technology, including hot stamping of aluminum alloy and laying process of fiber prepreg which is named HFQ-FMLs was proposed to solve the puzzles such as weak rigidity, low strength and integration deformation with large difficulty, and the feasibility and mechanical properties of the innovative forming process were studied. Firstly, based on the modified metal volume fraction formula, the theoretical values of the mechanical properties of the HFQ-FMLs plates were calculated. Compared with the experimental results, the minimum error is 1%, proving that the HFQ-FMLs technology scheme is feasible. Secondly, three kinds of metal sheets with different heat treatments and specimens by HFQ-FMLs were carried out for the tensile tests, the mechanical properties distributions were demonstrated, and the influence regularity of the strain rate and rolling direction on the stress analysis was considered at the same time. As can be seen from the distribution of yield strength and tensile strength, the yield stress of metal sheets obtained by HFQ-FMLs technology along the 45° is superior to the raw material and can increase by 46% under strain rate = 0.01 s−1. While, because the vacuum thermal curing treatment makes the aluminum alloy happen double aging, the metal sheet strength dropped, and the jointing strength between the metal and fiber prepreg became weak too, which made the strength limit of the new material improve weakly. Thirdly, the fractured style of the FMLs under different conditions was studied qualitatively. It is helpful to achieve the development rule of defects, optimize the craft route, and avoid deformation failure. [ABSTRACT FROM AUTHOR]

Determining an optimal combination of laser process parameters can significantly improve the efficiency and quality of 40Cr13 steel surface processing. In this study, two machine learning models (ELMSS and ELMPS) were proposed to predict the processing results of surface features to optimize process parameters. The prediction accuracies of the proposed models were always higher than those of traditional back propagation (BP) and radial basis function (RBF) neural networks, and the calculation time of the proposed models was significantly reduced. In comparison, the prediction accuracy ranking for ablation depth was ELMSS (92.6%), BP (89.8%), and RBF (89.6%), and for the ablation width, it was ELMSS (98.3%), BP (97.4%), and RBF (96.1%). The material removal rate was 92.4%, 91.1%, and 89.1% for ELMSS, BP, and RBF, respectively. Finally, the prediction accuracy ranking for surface roughness was 86.8%, 80.7%, and 79.5% for ELMPS, BP, and RBF, respectively. After optimization by the genetic algorithm, the prediction accuracies of the proposed models for the depth, width, material removal rate, and surface roughness reached 94.0%, 99.0%, 93.2%, and 91.2%, respectively. With the support of ELMSS and ELMPS, the results of the surface features can be predicted before machining and the appropriate process parameters can be selected in advance. [ABSTRACT FROM AUTHOR]