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Abstract Background Legionellosis remains a public health problem. The most common diagnostic method to detect Legionella pneumophila (L. pneumophila) is culture. Polymerase chain reaction (PCR) is a fast and accurate method for this detection in environmental samples. Methods Four databases were searched for studies that evaluated the detection efficiency of PCR in L. pneumophila. The quality evaluation was conducted using Review Manager 5.3. We used Meta-DiSc 1.4 software and the Stata 15.0 software to create forest plots, a meta-regression, a bivariate boxplot and a Deeks’ funnel plot. Results A total of 18 four-fold tables from 16 studies were analysed. The overall pooled sensitivity and specificity of PCR was 94% and 72%, respectively. The positive likelihood ratio (RLR) and negative likelihood ratio (NLR) was 2.73 and 0.12, respectively. The result of the diagnostic odds ratio (DOR) was 22.85 and the area under the curve (AUC) was 0.7884. Conclusion Establishing a laboratory diagnostic tool for L. pneumophila detection is important for epidemiological studies. In this work, PCR demonstrated a promising diagnostic accuracy for L. pneumophila.

Background There are no clear conclusions as to whether inflammatory proteins and plasma metabolites influence erectile dysfunction (ED). Aim In this research, we used Mendelian randomization (MR) analysis to discover a causal relationship between inflammatory proteins, plasma metabolites, and ED. Methods Raw data with ED, inflammatory proteins, and plasma metabolites were obtained from the MRC IEU OpenGWAS and FinnGen database. After a series of screenings, the remaining single nucleotide polymorphisms were selected as instrumental variables or MR analysis to assess the relationship between genetically predicted inflammatory proteins or plasma metabolites and the pathogenesis of ED. Outcomes The relationship between inflammatory factors and ED was fully analyzed and elaborated. Results In the inverse variance–weighted method, there exists a significant causal relationship between 4 types of genetically predicted inflammatory proteins and 50 types of plasma metabolites with the incidence of ED. The primary discovery is that 3 inflammatory proteins, fibroblast growth factor 5, interleukin-22 receptor subunit alpha-1, and protein S100-A12, can impact the risk of ED through plasma metabolites. Clinical Implications ED metabolites and inflammatory proteins are also closely associated with cardiovascular diseases, warranting further exploration. Strengths and Limitations Our analysis is based on a European population, limiting its generalizability, the genome-wide association study dataset for ED has a relatively small number of cases, and we hope for larger genome-wide association study datasets for future validation. Conclusion This study has identified that inflammatory proteins can influence ED through plasma metabolites. [ABSTRACT FROM AUTHOR]

As a novel signal control method, signal Cooperative Control with traffic Supply and Demand (CCSD) is superior to the traditional control methods and could satisfy the control requirements under all traffic conditions. However, the optimization solution of CCSD cannot meet the real-time control requirement for its exhaustive search. To overcome the problem, in this paper, the optimization problem of CCSD is reconstructed by the time-varying traffic supply and demand, and the problem is reduced as a problem of space search. Then, the krill herd (KH) algorithm is introduced and employed to realize the fast solution of CCSD (named KH-CCSD). During the process of optimization, the search space representation and fitness function for the KH algorithm are constructed to satisfy the solution of CCSD. The optimal signal timing plan is obtained by an iterated search of krill swarm in a multi-dimensional time-varying space cooperatively constrained by traffic supplies and demands. The convergence and effectiveness of KH-CCSD are validated by comparing experiments, in which the convergence of KH-CCSD is tested by different initializations and KH-CCSD is compared with the Webster method and capacity-aware back-pressure (CABP) control under unsaturated, saturated, and oversaturated conditions. The experiments results show that KH-CCSD performs a fast convergence and KH-CCSD is superior to the Webster method and CABP. As a result, KH-CCSD could satisfy the application of CCSD under all traffic conditions.

Traffic signal control is widely used at intersection to improve its operation efficiency. However, the existing signal control systems cannot satisfy the control requirements under unsaturated, saturated, and oversaturated conditions, which will induce queue spillover, even network deadlock. A signal Cooperative Control method with traffic Supply and Demand (CCSD) on a single intersection is put forward to maximize the efficiency and avoid queue spillover by the cooperation between traffic supply and demand. A general CCSD control framework is constructed by the control relationship description and discrete-time statespace equations. Furthermore, the uniform matrix description of CCSD is put forward under the framework to fast solve the problem by matrix calculation. An artificial intelligence planning model on CCSD is established by an objective function compromising between throughput and fairness to satisfy the control requirements under dynamic unknown traffic environment. CCSD is compared with the Webster method and capacity-aware back-pressure (CABP) control in the experiments by both the simulation data and investigation data under unsaturated, saturated, and oversaturated conditions. The results show that CCSD is superior to CABP control and the Webster method in the throughput, the number of stops, and stop time, and can avoid the queue spillover. Accordingly, CCSD can be used to improve the efficiency and avoid queue spillover at intersection under all traffic conditions.

Aims: To describe the experiences and perceptions of acute myocardial infarction (AMI) patients with a prolonged decision‐making phase of treatment‐seeking. Background: Previous attempts to reduce the treatment‐seeking time of AMI have been less than optimal. Due to the coronavirus disease 2019 (COVID‐19) pandemic, the situation of prehospital delay is possibly worse. Decisions to seek treatment are influenced by multiple factors and need individualised interventions. Understanding patients' external and internal experiences and psychological perceptions is essential. Design: Meta‐synthesis. Data sources: We searched PubMed, Embase, Cochrane Library, Web of Science, Scopus and four Chinese databases from inception to April 2022. Methods: We screened the retrieved articles with predetermined inclusion and exclusion criteria, and reviewed articles using Thomas and Harden's (BMC Medical Research Methodology, 2008 8, 45) qualitative thematic synthesis approach. The Joanna Briggs Institute critical appraisal tool for qualitative research was used to assess the quality of studies. Results: Twenty‐one studies were included, identifying four themes and nine sub‐themes. The four primary themes were difficulty recognising and attributing symptoms, attempt to act, unwillingness to change and self‐sacrifice. Conclusion: Deciding to seek treatment is a complex social and psychological process, which needs comprehensive interventions considering personal and sociocultural factors and factors related to the COVID‐19 pandemic. Implications for the profession and/or patient care: Details of interventions for decisions to seek treatment in AMI patients need to be further designed and evaluated. Impact: Results would help healthcare professionals to implement individualised management of decision‐making of treatment‐seeking among AMI patients, and improve medical records of patients' prehospital experiences. Reporting Method: The Preferred Reporting Items for Systematic Reviews 2020 checklist was used to report the findings. Patient or Public Contribution: Two AMI patients contributed to the data synthesis by giving simple feedback about the final themes. [ABSTRACT FROM AUTHOR]

Conductive bridge random access memories (CBRAMs) usually involve active Ag or Cu metals, where the formation of metal filaments accounts for the low resistance state. For the application of neuromorphic computation, it is highly desirable to develop artificial neurons and synapses, which utilize the complicated volatile or nonvolatile resistive switching phenomena, respectively. This can be achieved by controlling the morphology and stability of the filaments, which requires a deep understanding of the filament formation and disruption mechanisms. Using ab initio calculations, we explored the physical mechanism behind various Ag filament morphologies and growth modes, using GeSe, ZrO2, SiO2, and a-Si as the examples. The roles of Ag and Ag+ stability inside the dielectric, the migration barrier of Ag+, and the Ag+ solvation effect have been investigated in detail. A comprehensive model has been proposed, which in particular could explain the diverse Ag filament morphology experimentally observed in sputtered SiO2 and PECVD SiO2. Our theoretical approach can serve as a pre-screening method in designing new solid-state electrolyte materials of CBRAM, aiming at new functionalities in neuromorphic computation or in-memory logic computing. [ABSTRACT FROM AUTHOR]

Background: Here, we describe an innovative oncoplastic technique for small to medium volume breasts with a tumor in the lower quadrant and this technique could provide sufficient tissue to avoid visible defects after tumor removal and help reshape the natural shape of the breast. Methods: A detailed procedure for the folding flap technique is described step by step. Then, the results of a retrospective analysis of patients treated using this technique, including complications and disease recurrence rate, between January 2017 and November 2021 are reported. Aesthetic outcomes were evaluated on a 5-point scale proposed by the Paris Breast Center. Results: A total of 52 patients underwent surgery with the folding flap technique, The average operation time was 98.4 min (range, 75–120 min), and the mean bleeding volume was 56.5 mL (range, 20–100 mL). A margin-positive result was confirmed in 1 patient who underwent re-excision. Short-term postoperative complications were observed in 7 patients, including 4 with fat liquefaction, 2 with seroma, and 1 with skin redness and swelling. No flap necrosis was observed. The median follow-up time was 28.6 months (range, 9–58 months), and 2 patients experienced local recurrence. The mean aesthetic score was 4.7 points, with 36 patients scoring 5 points and 26 patients scoring 4 points, respectively. Conclusions: The folding flap technique, as an innovative and favorable oncoplastic technique for treating small- to medium-volume breasts with a tumor in the lower quadrant, could retain sufficient tissue to fill the residual cavity after the operation while improving the aesthetic outcome of the breast. [ABSTRACT FROM AUTHOR]

Molecular analysis facilitates the prediction of overall survival (OS) of breast cancer and decision-making of the treatment plan. The current study was designed to identify new prognostic genes for breast cancer and construct an effective prognostic signature with integrated bioinformatics analysis. Differentially expressed genes in breast cancer samples from The Cancer Genome Atlas (TCGA) dataset were filtered by univariate Cox regression analysis. The prognostic model was optimized by the Akaike information criterion and further validated using the TCGA dataset (n = 1014) and Gene Expression Omnibus (GEO) dataset (n = 307). The correlation between the risk score and clinical information was assessed by univariate and multivariate Cox regression analyses. Functional pathways in relation to high-risk and low-risk groups were analyzed using gene set enrichment analysis (GSEA). Four prognostic genes (EXOC6, GPC6, PCK2, and NFATC2) were screened and used to construct a prognostic model, which showed robust performance in classifying the high-risk and low-risk groups. The risk score was significantly related to clinical features and OS. We identified 19 functional pathways significantly associated with the risk score. This study constructed a new prognostic model with a high prediction performance for breast cancer. The four-gene prognostic signature could serve as an effective tool to predict prognosis and assist the management of breast cancer patients. [ABSTRACT FROM AUTHOR]

This study evaluated the effect of enarodustat on cardiac repolarization in healthy subjects. Enarodustat (20 and 150 mg [supratherapeutic dose]), placebo, and moxifloxacin (positive control, 400 mg) were administered orally to males and females (N = 54) in a crossover fashion. Continuous 12‐lead Holter electrocardiogram (ECG) data were obtained before and after dosing, and blood samples were obtained for pharmacokinetic assessments of enarodustat, its circulating metabolite (R)‐M2, and moxifloxacin. Central tendency analysis was performed for relevant ECG parameters, the relationship between individual‐corrected interval from beginning of the QRS complex to end of the T wave in the frontal plane (QTcI, the primary end point) and plasma concentrations of enarodustat and (R)‐M2 were assessed, and ECG waveforms were evaluated for morphological changes. The supratherapeutic dose resulted in 7‐ and 9‐fold higher geometric mean maximum concentrations for enarodustat and (R)‐M2, respectively, than the 20 mg dose. Based on time point analysis, the upper bound of the 2‐sided 90% confidence interval (CI) for QTcI did not exceed 10 milliseconds at any of the time points for either dose. Based on QTcI‐concentration analysis, the slopes for enarodustat and (R)‐M2 were not statistically different than 0, and the upper bounds of the 2‐sided 90% CI for QTcI at the geometric mean maximum concentrations for the supratherapeutic dose were 1.97 and 1.68 milliseconds for enarodustat and (R)‐M2, respectively. The lower bound of the 2‐sided 90% CI for moxifloxacin was ≥5 milliseconds, demonstrating assay sensitivity. The study demonstrated no clinically relevant effect of enarodustat and (R)‐M2 on cardiac repolarization. There was no evidence of any clinically significant effect on the PR interval and QRS duration, and ECG waveforms showed no new clinically relevant morphological changes. [ABSTRACT FROM AUTHOR]

Background. The purpose of this study was to investigate the regulatory mechanisms of ceRNAs in breast cancer (BC) and construct a new five-mRNA prognostic signature. Methods. The ceRNA network was constructed by different RNAs screened by the edgeR package. The BC prognostic signature was built based on the Cox regression analysis. The log-rank method was used to analyse the survival rate of BC patients with different risk scores. The expression of the 5 genes was verified by the GSE81540 dataset and CPTAC database. Results. A total of 41 BC-adjacent tissues and 473 BC tissues were included in this study. A total of 2,966 differentially expressed lncRNAs, 5,370 differentially expressed mRNAs, and 359 differentially expressed miRNAs were screened. The ceRNA network was constructed using 13 lncRNAs, 267 mRNAs, and 35 miRNAs. Kaplan-Meier (K-M) methods showed that two lncRNAs (AC037487.1 and MIR22HG) are related to prognosis. Five mRNAs (VPS28, COL17A1, HSF1, PUF60, and SMOC1) in the ceRNA network were used to establish a prognostic signature. Survival analysis showed that the prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p = 0.0022). ROC analysis showed that this signature has a good diagnostic ability (AUC = 0.77). Compared with clinical features, this signature was also an independent prognostic factor (HR: 1.206, 95% CI 1.108−1.311; p < 0.001). External verification results showed that the expression of the 5 mRNAs differed between the normal and tumour groups at the chip and protein levels (p < 0.001). Conclusions. These ceRNAs may play a key role in the development of BC, and the new 5-mRNA prognostic signature can improve the prediction of survival for BC patients. [ABSTRACT FROM AUTHOR]

Fungal laccases have shown great potential in industrial and environmental applications. They are generally produced as laccase isoenzymes. Thus, to further study the properties of different laccase isoenzymes and their performance in bio-remediation is essential for a deep understanding of laccase function and application. In this study, three Pleurotus ostreatus HAUCC 162 laccase isoenzymes were heterologously expressed, and the effects of different inhibitors, metal ions, and organic solvents on the activity of recombinant laccases were evaluated. In the dye decolorization test, LACC6 showed the highest ability to remove Malachite green (MG), Remazol Brilliant Blue R (RBBR), Bromophenol blue (BB), and Methyl orange (MO) among the three recombinant laccases. Removal rates within 24 h were 91.5%, 84.9%, 79.1%, and 73.1% for MG (100 mg/L), RBBR (100 mg/L), BB (100 mg/L), and MO (100 mg/L), respectively. The MG and RBBR transformation pathways were proposed by using High Performance Liquid Chromatography-Mass Spectrometry (LC–MS) analysis. Based on the results of this work, the production of recombinant LACC6 or improving the portion of LACC6 in the crude extracellular laccase may advance synthetic dye removal. Image 10788 • Three Pleurotus ostreatus HAUCC 162 laccase isoenzymes were heterologously expressed. • Effect of inhibitors, metal ions and organic solvents on laccases were evaluated. • Recombinant LACC6 showed higher decolorization efficiency than LACC9 and LACC10. • Transformation pathways of MG and RBBR were analyzed using LC-MS. [ABSTRACT FROM AUTHOR]

Memristors with small size, fast speed, low power, CMOS compatibility and nonvolatile modulation of device resistance are promising candidates for the next-generation data storage and in-memory logic computing paradigm. In comparison to the binary logics enabled by memristor devices, multi-valued logics can provide higher computation efficiency with simple operation scheme, reduced circuit complexity, and smaller chip area. In this contribution, we demonstrate that all the 27 univariate ternary logic operations can be realized with a single ZnO three-state resistive switching memristor in at most three steps. The nonvolatile modulation characteristics of the memristor allow the read step to be independent of the logic operation and capacitate logic-in-memory applications. The present methodology could be beneficial for constructing future high-performance computation architectures. [ABSTRACT FROM AUTHOR]

In-memory computing based on memristive logic is considered as a prospective non von Neumann computing paradigm. In this letter, we systematically analyze the four-variable logic method and map it into the operation of two anti-serial complementary memristors in the crossbar array architecture. Arbitrary Boolean logic can be implemented within three cycles with the experimental evidence of reconfigurable NAND, NOR, and XOR logic using Pt/HfO2/TiN devices. Taking advantage of the functional flexibility, a parallel 1-bit full adder that can be realized in 8 cycles within a $\textsf {4}\times \textsf {3}$ array has been designed and verified in simulation. [ABSTRACT FROM AUTHOR]