Development and validation of a nomogram for predicting severe respiratory syncytial virus-associated bronchiolitis.

BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of bronchiolitis and is related to the severity of the disease. This study aimed to develop and validate a nomogram for predicting severe bronchiolitis in infants and young children with RSV infection. METHODS: A total of 325 children with RSV-associated bronchiolitis were enrolled, including 125 severe cases and 200 mild cases. A prediction model was built on 227 cases and validated on 98 cases, which were divided by random sampling in R software. Relevant clinical, laboratory and imaging data were collected. Multivariate logistic regression models were used to determine optimal predictors and to construct nomograms. The performance of the nomogram was evaluated by the area under the characteristic curve (AUC), calibration ability and decision curve analysis (DCA). RESULTS: There were 137 (60.4%) mild and 90 (39.6%) severe RSV-associated bronchiolitis cases in the training group (n = 227) and 63 (64.3%) mild and 35 (35.7%) severe cases in the validation group (n = 98). Multivariate logistic regression analysis identified 5 variables as significant predictive factors to construct the nomogram for predicting severe RSV-associated bronchiolitis, including preterm birth (OR = 3.80; 95% CI, 1.39-10.39; P = 0.009), weight at admission (OR = 0.76; 95% CI, 0.63-0.91; P = 0.003), breathing rate (OR = 1.11; 95% CI, 1.05-1.18; P = 0.001), lymphocyte percentage (OR = 0.97; 95% CI, 0.95-0.99; P = 0.001) and outpatient use of glucocorticoids (OR = 2.27; 95% CI, 1.05-4.9; P = 0.038). The AUC value of the nomogram was 0.784 (95% CI, 0.722-0.846) in the training set and 0.832 (95% CI, 0.741-0.923) in the validation set, which showed a good fit. The calibration plot and Hosmer‒Lemeshow test indicated that the predicted probability had good consistency with the actual probability both in the training group (P = 0.817) and validation group (P = 0.290). The DCA curve shows that the nomogram has good clinical value. CONCLUSION: A nomogram for predicting severe RSV-associated bronchiolitis in the early clinical stage was established and validated, which can help physicians identify severe RSV-associated bronchiolitis and then choose reasonable treatment.

Prediction of State of Health of Lithium-Ion Battery Using Health Index Informed Attention Model.

State-of-health (SOH) is a measure of a battery's capacity in comparison to its rated capacity. Despite numerous data-driven algorithms being developed to estimate battery SOH, they are often ineffective in handling time series data, as they are unable to utilize the most significant portion of a time series while predicting SOH. Furthermore, current data-driven algorithms are often unable to learn a health index, which is a measurement of the battery's health condition, to capture capacity degradation and regeneration. To address these issues, we first present an optimization model to obtain a health index of a battery, which accurately captures the battery's degradation trajectory and improves SOH prediction accuracy. Additionally, we introduce an attention-based deep learning algorithm, where an attention matrix, referring to the significance level of a time series, is developed to enable the predictive model to use the most significant portion of a time series for SOH prediction. Our numerical results demonstrate that the presented algorithm provides an effective health index and can precisely predict the SOH of a battery.

Clinical Evaluation of Metagenomic Next-Generation Sequencing for the detection of pathogens in BALF in severe community acquired pneumonia.

BACKGROUND: Rapid and accurate identification of pathogens is very important for the treatment of Severe community-acquired pneumonia (SCAP) in children. Metagenomic Next-generation sequencing (mNGS) has been applied in the detection of pathogenic bacteria in recent years, while the overall evaluation the application of SCAP in children is lacking. METHODS: In our study, 84 cases of SCAP were enrolled. Bronchoalveolar lavage fluid (BALF) samples were analysed using mNGS; and sputum, blood, and BALF samples were analysed using conventional technology (CT). RESULTS: Among the 84 children, 41 were boys, and 43 were girls, with an average age ranging from 2 months to 14 years. The pathogen detection rate of mNGS was higher than that of CT (83.3% [70/84] vs. 63.1% [53/84], P = 0.003). The mNGS was much greater than that of the CT in detecting Streptococcus pneumoniae (89.2% [25/29] vs. 44.8% [13/29], P = 0.001) and Haemophilus influenzae (91.7% [11/12] vs. 33.3% [4/12], P < 0.005). The mNGS also showed superior fungal detection performance compared with that of the CT (81.8% [9/11] vs. 18.2% [2/11], P = 0.004). The mNGS test can detect viruses, such as bocavirus, rhinovirus, and human metapneumovirus, which are not frequently recognised using CT. However, the mNGS detection rate was lower than that of the CT (52.4% [11/21] vs. 95.2% [20/21], P = 0.004) for Mycoplasma pneumoniae (MP). The detection rate of mNGS for mixed infection was greater than that of the CT, although statistical significance was not observed (26.3% [20/39] vs. 21.1% [16/39], P > 0.005). Treatment for 26 (31.0%) children was changed based on mNGS results, and their symptoms were reduced; nine patients had their antibiotic modified, five had antibiotics added, nine had their antifungal medication, and seven had their antiviral medication. CONCLUSION: mNGS has unique advantages in the detection of SCAP pathogens in children, especially S. pneumoniae, H. influenzae, and fungi. However, the detection rate of MP using mNGS was lower than that of the CT. Additionally, mNGS can detect pathogens that are not generally covered by CT, which is extremely important for the modification of the treatment strategy.

Convolutional Long-Short Term Memory Network with Multi-Head Attention Mechanism for Traffic Flow Prediction.

Accurate predictive modeling of traffic flow is critically important as it allows transportation users to make wise decisions to circumvent traffic congestion regions. The advanced development of sensing technology makes big data more affordable and accessible, meaning that data-driven methods have been increasingly adopted for traffic flow prediction. Although numerous data-driven methods have been introduced for traffic flow predictions, existing data-driven methods cannot consider the correlation of the extracted high-dimensional features and cannot use the most relevant part of the traffic flow data to make predictions. To address these issues, this work proposes a decoder convolutional LSTM network, where the convolutional operation is used to consider the correlation of the high-dimensional features, and the LSTM network is used to consider the temporal correlation of traffic flow data. Moreover, the multi-head attention mechanism is introduced to use the most relevant portion of the traffic data to make predictions so that the prediction performance can be improved. A traffic flow dataset collected from the Caltrans Performance Measurement System (PeMS) database is used to demonstrate the effectiveness of the proposed method.

Clinical evaluation of metagenomic next-generation sequencing for detecting pathogens in bronchoalveolar lavage fluid collected from children with community-acquired pneumonia.

This study is to evaluate the usefulness of pathogen detection using metagenomic next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) specimens from children with community-acquired pneumonia (CAP). We retrospectively collected BALF specimens from 121 children with CAP at Tianjin Children's Hospital from February 2021 to December 2021. The diagnostic performances of mNGS and conventional tests (CT) (culture and targeted polymerase chain reaction tests) were compared, using composite diagnosis as the reference standard. The results of mNGS and CT were compared based on pathogenic and non-pathogenic organisms. Pathogen profiles and co-infections between the mild CAP and severe CAP groups were also analyzed. The overall positive coincidence rate was 86.78% (105/121) for mNGS and 66.94% (81/121) for CT. The proportion of patients diagnosed using mNGS plus CT increased to 99.18%. Among the patients, 17.36% were confirmed only by mNGS; Streptococcus pneumoniae accounted for 52.38% and 23.8% of the patients were co-infected. Moreover, Bordetella pertussis and Human bocavirus (HBoV) were detected only using mNGS. Mycoplasma pneumoniae, which was identified in 89 (73.55%) of 121 children with CAP, was the most frequent pathogen detected using mNGS. The infection rate of M. pneumoniae in the severe CAP group was significantly higher than that in the mild CAP group (P = 0.007). The symptoms of single bacterial infections (except for mycoplasma) were milder than those of mycoplasma infections. mNGS identified more bacterial infections when compared to the CT methods and was able to identify co-infections which were initially missed on CT. Additionally, it was able to identify pathogens that were beyond the scope of the CT methods. The mNGS method is a powerful supplement to clinical diagnostic tools in respiratory infections, as it can increase the precision of diagnosis and guide the use of antibiotics.

Prevalence of Intracranial Aneurysm in Patients with Aortopathy: A Systematic Review with Meta-Analyses.

BACKGROUND AND PURPOSE: Patients with aortic disease might have an increased risk of intracranial aneurysm (IA). We conducted this research to assess the prevalence of IA in patients with aortopathy, considering the impact of gender, age, and cardiovascular risk factors. METHODS: We searched PubMed and Scopus from inception to August 2019 for epidemiological studies reporting the prevalence of IA in patients with aortopathy. Random-effect meta-analyses were performed to calculate the overall prevalence, and the effect of risk factors on the prevalence was also evaluated. Anatomical location of IAs in patients suffered from distinct aortic disease was extracted and further analyzed. RESULTS: Thirteen cross-sectional studies involving 4,041 participants were included in this systematic review. We reported an estimated prevalence of 12% (95% confidence interval [CI], 9% to 14%) of IA in patients with aortopathy. The pooled prevalence of IA in patients with bicuspid aortic valve, coarctation of the aorta, aortic aneurysm, and aortic dissection was 8% (95% CI, 6% to 10%), 10% (95% CI, 7% to 14%), 12% (95% CI, 9% to 15%), and 23% (95% CI, 12% to 34%), respectively. Gender (female) and smoking are risk factors related to an increased risk of IA. The anatomical distribution of IAs was heterogeneously between participants with different aortic disease. CONCLUSIONS: According to current epidemiological evidence, the prevalence of IA in patients with aortic disease is quadrupled compared to that in the general population, which suggests that an early IA screening should be considered among patients with aortic disease for timely diagnosis and treatment of IA.

Transapical septal myectomy in the beating heart via a minimally invasive approach: a feasibility study in swine.

OBJECTIVES: The aim of this study was to establish an original transapical septal myectomy procedure that can be performed in the beating heart via a minimally invasive approach for the treatment of hypertrophic obstructive cardiomyopathy. METHODS: We designed an original intracardiac septum resection device to conduct off-pump septal myectomy in swine. A subxiphoid minithoracotomy was performed to access the apex of the heart. This resection device was inserted into the left ventricular outflow tract of the heart via the apex. The basal anteroseptal myocardium beneath the right aortic cusp was identified using a combination of transoesophageal and transthoracic echocardiography and then resected and collected by the device. RESULTS: Six consecutive operations were successfully and accurately performed using the custom-made device under echocardiographic guidance. All pigs survived and appeared to be normal until planned euthanasia 1 week after operation. A 300-700 mg portion of the septal myocardium was resected from the normal swine heart. Echocardiography and electrocardiogram revealed no abnormalities after resection. One exception was the fifth pig, in which mild annular regurgitation of the aortic valve occurred after repetitive resection. Postmortem necropsy demonstrated that all resections were correctly located at the basal anteroseptal septum beneath the right aortic cusp. CONCLUSIONS: Our study provides the first proof-of-concept evidence for a novel beating heart transapical septal myectomy procedure, which showed promising translational potential for the treatment of hypertrophic obstructive cardiomyopathy. This procedure would probably reduce operative risks and improve outcomes and reduce the demanding expertise required to perform conventional surgical myectomy.

The behaviour of water on the surface of kaolinite with an oscillating electric field.

A quantitative understanding of oscillating electric field effects on the behaviour of water on the surface of kaolinite is vital for research in the field of clay-water systems. The behaviour of water molecules on the (0 0 1) and (0 0 -1) surfaces of kaolinite are systematically investigated in the absence or presence of an oscillating electric field using molecular dynamics simulations. The simulated results demonstrate that the applied oscillating electric fields parallel to kaolinite surface contribute to decreased amounts of adsorbed water molecules on the (0 0 1) surface of kaolinite. The oscillating electric field performs an inconspicuous effect on the adsorption of water on the (0 0 -1) surface of kaolinite. The behaviour of water on the surface of kaolinite will be impacted more severely by oscillating electric fields. Our results demonstrate that water molecules will rotate following the directions of the applied fields, which causes the decrease of hydrogen bonds, and thus, the weaker water-kaolinite interactions due to the applied field drive water molecules away from kaolinite surfaces. These results are of significance to understand the mechanisms of the oscillating electric fields affecting the behaviour of clay-water systems.

Ultraflexible Transparent Film Heater Made of Ag Nanowire/PVA Composite for Rapid-Response Thermotherapy Pads.

Ultraflexible transparent film heaters have been fabricated by embedding conductive silver (Ag) nanowires into a thin poly(vinyl alcohol) film (AgNW/PVA). A cold-pressing method was used to rationally adjust the sheet resistance of the composite films and thus the heating powers of the AgNW/PVA film heaters at certain biases. The film heaters have a favorable optical transmittance (93.1% at 26 Ω/sq) and an outstanding mechanical flexibility (no visible change in sheet resistance after 10 000 bending cycles and at a radius of curvature ≤1 mm). The film heaters have an environmental endurance, and there is no significant performance degradation after being kept at high temperature (80 °C) and high humidity (45 °C, 80% humidity) for half a year. The efficient Joule heating can increase the temperature of the film heaters (20 Ω/sq) to 74 °C in ∼20 s at a bias of 5 V. The fast-heating characteristics at low voltages (a few volts) associated with its transparent and flexibility properties make the poly(dimethylsiloxane)/AgNW/PVA composite film a potential candidate in medical thermotherapy pads.

Insight into the nanomechanical properties under indentation of ß-Si3N4 nano-thin layers in the basal plane using molecular dynamics simulation.

Molecular dynamics simulations were performed to clarify the nanomechanical responses of ß-Si3N4 nano-thin layers in the basal plane for indenters of various radii, different indentation velocities and at different temperatures. It was found that the maximum loading stress and indenter displacement both increase with increasing radius of the indenter. A large number of N(6h)-Si bond-breaking defects and one N(2c)-Si bond-breaking defects are responsible for the initiation of fracturing. With increasing loading velocity, the maximum loading stresses show almost no change; however, a high loading velocity can shorten the displacement of the indenter and contributes to the formation of new N(2c)-Si bond-breaking defects. Thermal fluctuations can decrease the mechanical properties of the thin layer. The maximum loading stresses and indenter displacements are sensitive to both the radius of the indenter and the loading temperature.

Investigation of Nanomechanical Properties of ß-Si3N4 Thin Layers in a Prismatic Plane under Tension: A Molecular Dynamics Study.

We report molecular dynamics simulations of the nanomechanical properties and fracture mechanisms of ß-Si3N4 thin layers in a prismatic plane under uniaxial tension. It is found that the thin layers in the y loading direction display a linear stress-strain relationship at ε < 0.021, and afterward, the stress increases nonlinearly with the strain until fracture occurs. However, for the z direction, the linear response is located at ε < 0.051. The calculated fracture stresses and strains of the thin layers increase with strain rates both in both directions. The thin layers exhibit the higher Young's modulus of 0.345 TPa in the z direction, higher than that in the y direction. The origins of crack derive from N(2c-1)-Si and N(6h-1)-Si bonds for the y and z loading directions, respectively.