Active Surveillance of Carbapenemase-Producing Organisms (CPO) Colonization With Xpert Carba-R Assay Plus Positive Patient Isolation Proves to Be Effective in CPO Containment

Background: Rapid screening of patients for colonization with carbapenemase-producing organisms (CPO), coupled with implementation of infection prevention strategies, has the potential to contain the spread of CPO.Methods: We first evaluated the performance of Xpert Carba-R assay (in comparison with other phenotypic methods) for carbapenemase detection using clinical isolates, and then used it to determine the intestinal CPO colonization in hospitalized patients. We then assessed the effectiveness of patient isolation in controlling the spread of CPO in a medical intensive care unit.Results: The Xpert Carba-R assay required the least processing time to reveal results and showed a 94.5% sensitivity and specificity in carbapenemase detection, except for IMP-8 (n = 4). During a 6-month study period, 134 patients in one ward were studied for CPO colonization and infection. Fifteen patients (11.2%) were colonized by CPO as detected by Xpert Carba-R assay, including three NDM, three IMP, and nine KPC possessing strains. The overall colonization and CPO infection rates were both 11.2% each. Isolation of patients with CPO led to a reduction in both colonization (from 28.6 to 5.6%) and infection rates (from 35.7 to 2.8%) during the study period (p < 0.05).Conclusion: Active surveillance of CPO utilizing the Xpert Carba-R assay supplemented with immediate patient isolation, proved to be an effective strategy to limit the spread of CPO in a health care setting

Inferring the Individual Psychopathologic Deficits With Structural Connectivity in a Longitudinal Cohort of Schizophrenia.

The prediction of schizophrenia-related psychopathologic deficits is exceedingly important in the fields of psychiatry and clinical practice. However, objective association of the brain structure alterations to the illness clinical symptoms is challenging. Although, schizophrenia has been characterized as a brain dysconnectivity syndrome, evidence accounting for neuroanatomical network alterations remain scarce. Moreover, the absence of generalized connectome biomarkers for the assessment of illness progression further perplexes the prediction of long-term symptom severity. In this paper, a combination of individualized prediction models with quantitative graph theoretical analysis was adopted, providing a comprehensive appreciation of the extent to which the brain network properties are affected over time in schizophrenia. Specifically, Connectome-based Prediction Models were employed on Structural Connectivity (SC) features, efficiently capturing individual network-related differences, while identifying the anatomical connectivity disturbances contributing to the prediction of psychopathological deficits. Our results demonstrated distinctions among widespread cortical circuits responsible for different domains of symptoms, indicating the complex neural mechanisms underlying schizophrenia. Furthermore, the generated models were able to significantly predict changes of symptoms using SC features at follow-up, while the preserved SC features suggested an association with improved positive and overall symptoms. Moreover, cross-sectional significant deficits were observed in network efficiency and a progressive aberration of global integration in patients compared to healthy controls, representing a group-consensus pathological map, while supporting the dysconnectivity hypothesis

Single-cell analysis reveals dysregulated inflammatory response in peripheral blood immunity in patients with acute respiratory distress syndrome

Introduction: Acute respiratory distress syndrome (ARDS) remains a major clinical challenge for patients in intensive care units. Determining the differential mechanisms underlying ARDS with different etiologies is a key goal to improve the effectiveness of ARDS therapy. Despite growing evidence that different immune cell types are involved in ARDS, the role of altered immune cell subpopulations in disease progression is unelucidated.Methods: In this study, we combined scRNA-seq and bulk-level sequencing to analyze the transcriptomes of peripheral blood mononuclear cells from healthy volunteers and patients with septic ARDS (sep-ARDS) and pneumonic ARDS (PNE-ARDS).Results: Our data revealed differential alterations at the cellular and molecular levels and within biological signaling pathways in ARDS with different etiologies. The dynamics of neutrophils, macrophages (Macs), classical dendritic cells (cDCs), myeloid-derived suppressive cells (MDSCs), and CD8+ T cells varied significantly among groups of different samples, with neutrophils and cDCs at higher, and Macs at significantly lower, amounts in the patients with sep-ARDS. Furthermore, MDSCs were highly enriched only in the sep-ARDS patients, whereas a higher abundance of CD8+ T cells was observed in patients with PNE-ARDS. In addition, these cell subpopulations were found to be significantly involved in apoptosis, inflammatory, and immune-related pathways. In particular, a significant enhancement of the oxidative stress response was observed in the neutrophil subpopulation.Conclusion: Our study shows that the composition of cells involved in the main peripheral circulation differs in patients with ARDS with different etiologies. Studying the role and mechanism of action of these cells during ARDS will provide new opportunities for the treatment of this condition

Nonlinear Analysis of Diastolic Heart Sounds Based on EMD and Correlation Dimension

Recent studies have applied nonlinear analysis methods for heart sounds to diagnose coronary artery disease (CAD). Coronary artery occlusion may cause diastolic heart murmurs, so analysis of diastolic heart murmurs has important significance to noninvasive diagnosis of CAD. Heart sound signal is typical nonlinear and non-stationary time series, nonlinear analysis method - correlation dimension can effectively describe the nonlinear characteristics of heart sound signals, but the analysis of the correlation dimension shows that trend terms in the heart sound signals may lead to erroneous results. Empirical mode decomposition (EMD) is adaptive to remove trend for non-stationary signal, so a method combining EMD and correlation dimension was proposed for nonlinear analysis of diastolic heart sound signals. The EMD method was applied to reconstruct heart sound signals after removing trend, and the correlation dimension for reconstructed heart sound signals was used as characteristics to distinguish between normal heart sound signals and CAD heart sound signals. The diastolic heart sounds of 15 normal people and 15 patients with CAD were analyzed in the experiment, and the results showed that the proposed method can effectively distinguish between normal people and patients with CAD

Nature-resembled nanostructures for energy storage/conversion applications

Nature-inspired nanomaterial is one of the well-investigated nanostructures with favorable properties exhibiting high surface area, more active sites, and tailorable porosity. In energy storage systems, nature-inspired nanomaterials have been highly anticipated to obtain the desired properties. Such nanostructures of nature-inspired nanomaterials include porous carbon, metal oxides/sulfides/phosphides/selenides/hydroxides, and others that have shown exemplary performance in electrochemical energy storage devices. However, the growing studies of nature-inspired nanomaterials have not fully been explored and summarized for numerous applications. This review reports the development of nature-inspired nanomaterials from different applications. Notably, we report the current methodologies and challenges for obtaining nature-inspired nanomaterials for supercapacitors, different types of batteries, catalysis, and substrates. The review ends with addressing the challenges and future perspectives of nature-inspired nanostructures toward their commercialization in electrochemical energy storage and conversion systems

Emergence of ST463 exoU-Positive, Imipenem-Nonsusceptible Pseudomonas aeruginosa Isolates in China

ABSTRACT This study investigated the resistance mechanisms and the distribution and proportions of virulence genes, including exoU, in 182 imipenem-nonsusceptible Pseudomonas aeruginosa (INS-PA) strains collected from China in 2019. There was no obvious prevalent sequence type or concentrated evolutionary multilocus sequence typing (MLST) type on the INS-PA phylogenetic tree in China. All of the INS-PA isolates harbored β-lactamases with/without other antimicrobial mechanisms, such as gross disruption of oprD and overexpression of efflux genes. Compared with exoU-negative isolates, exoU-positive isolates (25.3%, 46/182) presented higher virulence in A549 cell cytotoxicity assays. The southeast region of China had the highest proportion (52.2%, 24/46) of exoU-positive strains. The most frequent exoU-positive strains belonged to sequence type 463 (ST463) (23.9%, 11/46) and presented multiple resistance mechanisms and higher virulence in the Galleria mellonella infection model. The complex resistance mechanisms in INS-PA and the emergence of ST463 exoU-positive, multidrug-resistant P. aeruginosa strains in southeast China indicated a challenge that might lead to clinical treatment failure and higher mortality. IMPORTANCE This study investigates the resistance mechanisms and distribution and proportions of virulence genes of imipenem-nonsusceptible Pseudomonas aeruginosa (INS-PA) isolates in China in 2019. Harboring PDC and OXA-50-like genes is discovered as the most prevalent resistance mechanism in INS-PA, and the virulence of exoU-positive INS-PA isolates was significantly higher than that of exoU-negative INS-PA isolates. There was an emergence of ST463 exoU-positive INS-PA isolates in Zhejiang, China, most of which presented multidrug resistance and hypervirulence

Causal Associations between Serum Urea and Cancer: A Mendelian Randomization Study

Urea is largely derived from the urea cycle reactions through hepatic detoxification of free ammonia and cleared by urination, and the serum urea level is a crucial medical indicator for measuring the kidney function in patients with nephropathy; however, investigative revelations pointing to the serum urea level as a risk factor for cancer are very scarce, and relevant studies are restricted by potential biases. We aimed to explore the causal relationships of the serum urea level with cancer development by focusing on renal cell carcinoma (RCC) using the Mendelian randomization (MR) analyses. Summary estimates were collected from the inverse-variance weighted (IVW) method based on six single nucleotide polymorphisms (SNPs). The selected SNPs related to the serum urea were obtained from a large genome-wide association study (GWAS) of 13,312 European participants. The summary statistics of RCC were also available from public databases (IARC, n = 5219 cases, n = 8011 controls). Sensitivity analyses included the weighted median and MR-Egger methods. Serum urea was inversely associated with RCC in females (effect = 1.93; 95% CI: 1.24 to 3.01; p = 0.004) but exhibited null association with RCC in males, breast cancer (BRCA) in both genders and prostate cancer (PCa) in males. Similar conclusions were also drawn from the weighted median and MR-Egger. These findings reveal an intriguing link between serum urea and cancer risks for the very first time. Without ambiguity, the serum urea is causatively related to RCC specifically in females, although the mechanism(s) by which urea is involved in RCC development remains to be experimentally/clinically investigated. Our studies may well provide novel insights for RCC diagnosis, intervention and/or therapy