Metagenomic next-generation sequencing of bronchoalveolar lavage fluid assists in the diagnosis of pathogens associated with lower respiratory tract infections in children

Worldwide, lower respiratory tract infections (LRTI) are an important cause of hospitalization in children. Due to the relative limitations of traditional pathogen detection methods, new detection methods are needed. The purpose of this study was to evaluate the value of metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) samples for diagnosing children with LRTI based on the interpretation of sequencing results. A total of 211 children with LRTI admitted to the First Affiliated Hospital of Guangzhou Medical University from May 2019 to December 2020 were enrolled. The diagnostic performance of mNGS versus traditional methods for detecting pathogens was compared. The positive rate for the BALF mNGS analysis reached 95.48% (95% confidence interval [CI] 92.39% to 98.57%), which was superior to the culture method (44.07%, 95% CI 36.68% to 51.45%). For the detection of specific pathogens, mNGS showed similar diagnostic performance to PCR and antigen detection, except for Streptococcus pneumoniae, for which mNGS performed better than antigen detection. S. pneumoniae, cytomegalovirus and Candida albicans were the most common bacterial, viral and fungal pathogens. Common infections in children with LRTI were bacterial, viral and mixed bacterial-viral infections. Immunocompromised children with LRTI were highly susceptible to mixed and fungal infections. The initial diagnosis was modified based on mNGS in 29.6% (37/125) of patients. Receiver operating characteristic (ROC) curve analysis was performed to predict the relationship between inflammation indicators and the type of pathogen infection. BALF mNGS improves the sensitivity of pathogen detection and provides guidance in clinical practice for diagnosing LRTI in children

Implications of C1q/TNF-related protein superfamily in patients with coronary artery disease.

The C1q complement/TNF-related protein superfamily (CTRPs) displays differential effects on the regulation of metabolic homeostasis, governing cardiovascular function. However, whether and how they may serve as predictor/pro-diagnosis factors for assessing the risks of coronary artery disease (CAD) remains controversial. Therefore, we performed a clinical study to elaborate on the implication of CTRPs (CTRP1, CTRP5, CTRP7, and CTRP15) in CAD. CTRP1 were significantly increased, whereas CTRP7 and CTRP15 levels were decreased in CAD patients compared to the non-CAD group. Significant differences in CTRP1 levels were discovered between the single- and triple-vascular-vessel lesion groups. ROC analysis revealed that CTRP7 and CTRP15 may serve as CAD markers, while CTRP1 may serve as a marker for the single-vessel lesion of CAD. CTRP1 and CTRP5 can serve as markers for the triple-vessel lesion. CTRP1 may serve as an independent risk predictor for triple-vessel lesion, whereas CTRP15 alteration may serve for a single-vessel lesion of CAD. CTRP1 may serve as a novel superior biomarker for diagnosis of severity of vessel-lesion of CAD patients. CTRP7, CTRP15 may serve as more suitable biomarker for the diagnosis of CAD patients, whereas CTRP5 may serve as an independent predictor for CAD. These findings suggest CTRPs may be the superior predictive factors for the vascular lesion of CAD and represent novel therapeutic targets against CAD

Reliability of Robotic Ultrasound Scanning for Scoliosis Assessment in Comparison with Manual Scanning

Background: Ultrasound (US) imaging for scoliosis assessment is challenging for a non-experienced operator. The robotic scanning was developed to follow a spinal curvature with deep learning and apply consistent forces to the patient' back. Methods: 23 scoliosis patients were scanned with US devices both, robotically and manually. Two human raters measured each subject's spinous process angles (SPA) on robotic and manual coronal images. Results: The robotic method showed high intra- (ICC > 0.85) and inter-rater (ICC > 0.77) reliabilities. Compared with the manual method, the robotic approach showed no significant difference (p < 0.05) when measuring coronal deformity angles. The MAD for intra-rater analysis lies within an acceptable range from 0 deg to 5 deg for a minimum of 86% and a maximum 97% of a total number of the measured angles. Conclusions: This study demonstrated that scoliosis deformity angles measured on ultrasound images obtained with robotic scanning are comparable to those obtained by manual scanning

TextDiff: Mask-Guided Residual Diffusion Models for Scene Text Image Super-Resolution

The goal of scene text image super-resolution is to reconstruct high-resolution text-line images from unrecognizable low-resolution inputs. The existing methods relying on the optimization of pixel-level loss tend to yield text edges that exhibit a notable degree of blurring, thereby exerting a substantial impact on both the readability and recognizability of the text. To address these issues, we propose TextDiff, the first diffusion-based framework tailored for scene text image super-resolution. It contains two modules: the Text Enhancement Module (TEM) and the Mask-Guided Residual Diffusion Module (MRD). The TEM generates an initial deblurred text image and a mask that encodes the spatial location of the text. The MRD is responsible for effectively sharpening the text edge by modeling the residuals between the ground-truth images and the initial deblurred images. Extensive experiments demonstrate that our TextDiff achieves state-of-the-art (SOTA) performance on public benchmark datasets and can improve the readability of scene text images. Moreover, our proposed MRD module is plug-and-play that effectively sharpens the text edges produced by SOTA methods. This enhancement not only improves the readability and recognizability of the results generated by SOTA methods but also does not require any additional joint training. Available Codes:https://github.com/Lenubolim/TextDiff

Delocalization of d-electrons induced by cation coupling in ultrathin Chevrel-phase NiMo₃S₄ nanosheets for efficient electrochemical water splitting

Chevrel-phase metal sulfides are known to be promising materials for energy conversion and storage applications. However, a detailed understanding of the intrinsic kinetic mechanisms of electrocatalytic bifunctional hydrogen and oxygen evolution reactions (HER/OER) on NiMo3S4-based Chevrel-phases is lacking. Herein, novel ultrathin self-assembled nanosheets of NiMo3S4 are coupled with transition metal atoms (M/N-NiMo3S4; where M = Co, Fe, and Cu) were formed by a facile hydrothermal approach. Notably, the Co/N-NiMo3S4 electrocatalyst exhibits excellent performance in terms of ultralow overpotentials of 78, 208, 282, and 307 mV at 10, 100, 500, and 1000 mA cm−2 for the HER; and 186, 204, and 225 mV at 50, 100, and 300 mA cm−2 for the OER, respectively. Experimental and first principle calculations demonstrate that Co atoms coupling with edge Ni atoms results in d‐electron delocalization on Co/N-NiMo3S4, signifying the efficient charge transfer to improve overall water electrolysis. In addition, an upshift in the d‐band center of Co/N-NiMo3S4 can optimize the free energies of a variety of reaction intermediates for water adsorption and dissociation; thereby facilitating the robust alkaline overall water electrolysis at 1.47 V. This work therefore greatly deepens the understanding of the bifunctional hydrogen and oxygen evolution reaction of Chevrel-phase electrocatalysts.</p

Delocalization of d-electrons induced by cation coupling in ultrathin Chevrel-phase NiMo₃S₄ nanosheets for efficient electrochemical water splitting

Chevrel-phase metal sulfides are known to be promising materials for energy conversion and storage applications. However, a detailed understanding of the intrinsic kinetic mechanisms of electrocatalytic bifunctional hydrogen and oxygen evolution reactions (HER/OER) on NiMo3S4-based Chevrel-phases is lacking. Herein, novel ultrathin self-assembled nanosheets of NiMo3S4 are coupled with transition metal atoms (M/N-NiMo3S4; where M = Co, Fe, and Cu) were formed by a facile hydrothermal approach. Notably, the Co/N-NiMo3S4 electrocatalyst exhibits excellent performance in terms of ultralow overpotentials of 78, 208, 282, and 307 mV at 10, 100, 500, and 1000 mA cm−2 for the HER; and 186, 204, and 225 mV at 50, 100, and 300 mA cm−2 for the OER, respectively. Experimental and first principle calculations demonstrate that Co atoms coupling with edge Ni atoms results in d‐electron delocalization on Co/N-NiMo3S4, signifying the efficient charge transfer to improve overall water electrolysis. In addition, an upshift in the d‐band center of Co/N-NiMo3S4 can optimize the free energies of a variety of reaction intermediates for water adsorption and dissociation; thereby facilitating the robust alkaline overall water electrolysis at 1.47 V. This work therefore greatly deepens the understanding of the bifunctional hydrogen and oxygen evolution reaction of Chevrel-phase electrocatalysts.</p

Spatiotemporal distribution of malaria and the association between its epidemic and climate factors in Hainan, China

<p>Abstract</p> <p>Background</p> <p>Hainan is one of the provinces most severely affected by malaria epidemics in China. The distribution pattern and major determinant climate factors of malaria in this region have remained obscure, making it difficult to target countermeasures for malaria surveillance and control. This study detected the spatiotemporal distribution of malaria and explored the association between malaria epidemics and climate factors in Hainan.</p> <p>Methods</p> <p>The cumulative and annual malaria incidences of each county were calculated and mapped from 1995 to 2008 to show the spatial distribution of malaria in Hainan. The annual and monthly cumulative malaria incidences of the province between 1995 and 2008 were calculated and plotted to observe the annual and seasonal fluctuation. The Cochran-Armitage trend test was employed to explore the temporal trends in the annual malaria incidences. Cross correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on malaria transmission and the auto correlation of malaria incidence. A multivariate time series analysis was conducted to construct a model of climate factors to explore the association between malaria epidemics and climate factors.</p> <p>Results</p> <p>The highest malaria incidences were mainly distributed in the central-south counties of the province. A fluctuating but distinctly declining temporal trend of annual malaria incidences was identified (Cochran-Armitage trend test <it>Z </it>= -25.14, <it>P </it>< 0.05). The peak incidence period was May to October when nearly 70% of annual malaria cases were reported. The mean temperature of the previous month, of the previous two months and the number of cases during the previous month were included in the model. The model effectively explained the association between malaria epidemics and climate factors (<it>F </it>= 85.06, <it>P </it>< 0.05, adjusted <it>R </it>²= 0.81). The autocorrelations of the fitting residuals were not significant (<it>P </it>> 0.05), indicating that the model extracted information sufficiently. There was no significant difference between the monthly predicted value and the actual value (<it>t </it>= -1.91, <it>P </it>= 0.08). The <it>R </it>²for predicting was 0.70, and the autocorrelations of the predictive residuals were not significant (<it>P </it>> 0.05), indicating that the model had a good predictive ability.</p> <p>Discussion</p> <p>Public health resource allocations should focus on the areas and months with the highest malaria risk in Hainan. Malaria epidemics can be accurately predicted by monitoring the fluctuations of the mean temperature of the previous month and of the previous two months in the area. Therefore, targeted countermeasures can be taken ahead of time, which will make malaria surveillance and control in Hainan more effective and simpler. This model was constructed using relatively long-term data and had a good fit and predictive validity, making the results more reliable than the previous report.</p> <p>Conclusions</p> <p>The spatiotemporal distribution of malaria in Hainan varied in different areas and during different years. The monthly trends in the malaria epidemics in Hainan could be predicted effectively by using the multivariate time series model. This model will make malaria surveillance simpler and the control of malaria more targeted in Hainan.</p

MiRNA-200b level in peripheral blood predicts renal interstitial injury in patients with diabetic nephropathy

Background: To uncover the diagnostic potential of peripheral blood microRNA-200b (miRNA-200b) in renal interstitial injury in diabetic nephropathy (DN) patients. Methods: A total of 50 diabetes subjects, 50 mild DN subjects, 50 moderate-severe DN subjects and 50 healthy subjects were included. Peripheral blood level of miRNA-200b in every subject was detected by reverse transcriptase-polymerase chain reaction (RT-PCR). Serum levels of renal function indicators were determined by enzyme-linked immunosorbent assay (ELISA). Meanwhile, relative levels of fibrosis damage indicators were examined by chemiluminescent immunoassay. Diagnostic potentials of miRNA200b in diabetes, mild DN and moderate-severe DN were assessed by depicting receiver operating characteristic (ROC) curves. Results: Peripheral blood level of miRNA-200b was higher in DN subjects than diabetes subjects without vascular complications, especially moderate-severe DN patients. Peripheral blood level of miRNA-200b in DN subjects was negatively correlated to relative levels of serum creatinine, urinary nitrogen, cystatin, TGF-b, CIV and PCIII. ROC curves demonstrated diagnostic potentials of miRNA-200b in mild and moderate-severe DN. Conclusions: Peripheral blood level of miRNA-200b is closely linked to the degree of renal interstitial injury in DN patients. MiRNA-200b may be a vital indicator in predicting the development of DN