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In order to satisfy timeliness requirements arising from environmental sensing applications, age of information (AoI) was proposed to characterise the freshness of the received updates. In this paper, we consider a wireless powered relay aided communication network (WPRCN), in which a relay wirelessly powered by a hybrid-access point (H-AP) receives environmental monitoring information update from a sensor and forwards it to the H-AP. The long-term average AoI is studied since the decision correctness depends on the update timely uploaded by the relay. The wireless powered relay adopts either a decode-and-forward (DF) or an amplify and forward (AF) protocols, respectively, subject to the energy causality. We also consider the decoding cost of DF protocol owing to the relay’s limited energy storage. Since the expression of the average AoI is non-elementary, we propose a Taylor approximation based algorithm to obtain its integral. We optimise the transmit power/the equivalent average power consumption of the relay for the sake of minimising the average AoI in the whole WPRCN with different forwarding protocols. Our simulation results demonstrate the accuracy of the theoretical analysis, while the average AoI of the WPRCN is optimised by our power allocation scheme at the relay. The proposed algorithm is verified to achieve great approximation effect.

Purpose:Community-acquire pneumonia (CAP) is one of the leading causes of death among adults worldwide and one of the world's most burdened diseases. Previous studies have suggested that viral pneumonia, especially severe influenza virus pneumonia, tends to be superinfected with Aspergillus. But the clinical features and prognostics in viral CAP patients with detection of Aspergillus in the early onset of the disease were unclear. Methods: We conducted a multicenter prospective observational cohort study in China of CAP patients. Adult patients with CAP in 6 hospitals from January 2017 to October 2018 were enrolled. Lower respiratory tract specimens (including sputum and alveolar lavage fluid) were collected within 72 hours after admission. Molecular biology techniques were used to conduct comprehensive pathogenic testing on collected specimens, including bacteria, atypical pathogens, viruses and fungi. A unified electronic medical record website system was used to collect patient clinical data. Results:A total of 382 adult CAP patients were enrolled. The positive rate of virus was 38% (145/382), and Aspergillus was 11.0% (16/145) in viral CAP. The mortality of Aspergillus-positive patients (25%, 4/16) was significantly higher than that of Aspergillus-negative patients (5.4%, 7/129) in viral CAP (P=0.021). In multivariable Logistic regression models, positive Aspergillus at admission significantly increased the mortality of viral CAP [OR (95%CI) =5.81 (1.48, 22.73), P=0.011]. The lymphocyte count in Aspergillus-positive patients was significantly lower than that of Aspergillus-negative patients (P=0.047). Conclusion:The positive detection results of Aspergillus from lower respiratory tract were associated with higher mortality in viral CAP. Trial registration: ClinicalTrials.gov, NCT03093220. Registered retrospectively on 28 March 2017.

The spread of IMP-type MBLs has increased dramatically in recent years. We discovered three novel IMP variants from three clinical isolates in China.

Increasing evidence indicates that respiratory tract microecological disorders may play a role in the pathogenesis of chronic obstructive pulmonary disease (COPD). Understanding the composition of the respiratory microbiome in COPD and its relevance to respiratory immunity will help develop microbiome-based diagnostic and therapeutic approaches. One hundred longitudinal sputum samples from 35 subjects with acute exacerbation of COPD (AECOPD) were analysed for respiratory bacterial microbiome using 16S ribosomal RNA amplicon sequencing technology, and the sputum supernatant was analysed for 12 cytokines using a Luminex liquid suspension chip. Unsupervised hierarchical clustering was employed to evaluate the existence of distinct microbial clusters. In AECOPD, the respiratory microbial diversity decreased, and the community composition changed significantly. The abundances of Haemophilus, Moraxella, Klebsiella, and Pseudomonas increased significantly. Significant positive correlations between the abundance of Pseudomonas and TNF-α, abundance of Klebsiella and the percentage of eosinophils were observed. Furthermore, COPD can be divided into four clusters based on the respiratory microbiome. AECOPD-related cluster was characterized by the enrichment of Pseudomonas and Haemophilus and a high level of TNF-α. Lactobacillus and Veillonella are enriched in therapy-related phenotypes and may play potential probiotic roles. There are two inflammatory endotypes in the stable state: Gemella is associated with the Th2 inflammatory endotypes, whereas Prevotella is associated with the Th17 inflammatory endotypes. Nevertheless, no differences in clinical manifestations were found between these two endotypes. The sputum microbiome is associated with the disease status of COPD, allowing us to distinguish different inflammatory endotypes. Targeted anti-inflammatory and anti-infective therapies may improve the long-term prognosis of COPD.

BackgroundLipid metabolism is associated with glucose metabolism, but whether there are variations between sexes in risk factors and prevalence of abnormal lipid metabolism in major depressive disorder (MDD) patients with glucose metabolism abnormalities remains ambiguous. In the present study, the frequency and risk factors of dyslipidemia in first-episode and drug-naïve (FEDN) MDD patients with dysglycemia were examined according to sex.MethodsOne thousand seven hundred and eighteen FEDN MDD patients were recruited and their demographic data, clinical data, various biochemical indicators and scale assessment scores including 17-item Hamilton Rating Scale for Depression (HAMD-17), 14-item Hamilton Anxiety Rating Scale (HAMA-14), and positive subscale of the Positive and Negative Syndrome Scale (PANSS) were collected.ResultsThe prevalence of abnormal lipid metabolism in both male and female MDD patients with abnormal glucose metabolism was higher than that in patients without abnormal glucose metabolism. Among male MDD patients with abnormal glucose metabolism, TC was positively correlated with HAMD score, TSH and TgAb levels, but negatively correlated with PANSS positive subscale scores. LDL-C was positively correlated with TSH and BMI, but negatively correlated with PANSS positive subscale scores. HDL-C was negatively correlated with TSH levels. Among females, TC was positively correlated with HAMD score, TSH, and BMI, but negatively correlated with PANSS positive subscale score. LDL-C was positively correlated with HADM score and negatively correlated with FT3 level. HDL-C was negatively correlated with TSH and BMI levels.ConclusionThere are sex differences in the correlated factors of lipid markers in MDD patients with impaired glucose.

Donnai-Barrow syndrome (DBS) is a rare autosomal recessive disorder caused by mutation in the low density lipoprotein receptor-related protein 2 gene (LRP2). Defects in this protein may lead to clinical multiple organ malformations by affecting the development of organs such as the nervous system, eyes, ears, and kidneys. Although some variations on LRP2 have been found to be associated with DBS, early diagnosis and prevention of patients with atypical DBS remains a challenge for many physicians because of their clinical heterogeneity. The objective of this study is to explore the association between the clinical presentation and the genotype of a DBS patient who was initially diagnosed with early-onset high myopia (eoHM) from a healthy Chinese family. To this end, we tested the patient of this family via whole exome sequencing and further verified the results among other family members by Sanger sequencing. Comprehensive ophthalmic tests as well as other systemic examinations were also performed on participants with various genotypes. Genetic assessment revealed that two novel variations in LRP2, a de novo missense variation (c.9032G>A; p.Arg3011Lys) and a novel splicing variation (c.2909-2A>T) inherited from the father, were both carried by the proband in this family, and they are strongly associated with the typical clinical features of DBS patients. Therefore, in this paper we are the first to report two novel compound heterozygous variations in LPR2 causing DBS. Our study extends the genotypic spectrums for LPR2-DBS and better assists physicians in predicting, diagnosing, and conducting gene therapy for DBS.

Cuffless blood pressure (BP) monitoring has gained great attention in the past twenty years considering its significant benefits in cardiovascular healthcare. However, the main challenge of this technology is the inaccurate BP modeling under activities, i.e., existing work have either been inappropriately validated with sufficient intra-individual BP variations, or did not show promising estimation accuracy under activities. In this study, a novel deep learning model UTransBPNet, featured in short- and long-range feature representation, is proposed aiming to improve the estimation accuracy and tracking capability of intra-individual BP changes under activities. The model performance was comprehensively evaluated in three different datasets, i.e., one public dataset (Dataset_MIMIC) and two datasets under daily activities (Dataset_Drink and Dataset_Exercise). Under subject-independent validation, the model achieved state-of-the-art performance in the Dataset_MIMIC, with the mean absolute differences (MADs) for systolic BP (SBP) and diastolic BP (DBP) of 4.38 and 2.25 mmHg, respectively. In addition, the model achieved strong tracking capability of intra-individual BP variations under activities, with the individual Pearson’ correlation coefficients for SBP and DBP of 0.61±0.17 and 0.62±0.13 (Dataset_Drink), 0.82±0.11 and 0.72±0.18 (Dataset_Exercise), respectively. Moreover, this study for the first time tested the generalization capability across different activities, and showed that with small-sized scenario-specific data for finetuning, our model showed good cross-scenario generalization capability which however degraded significantly when there are differences in the BP distribution and variation patterns between the datasets. In conclusion, UTransBPNet is generally a very promising deep learning model for accurate cuffless BP estimation and tracking BP changes. Future work should further investigate the influence of BP distribution and variation patterns on the generalization capability for building effective training dataset.

The construction of high-speed railways continues to extend in seismic prone areas, but there is limited research on the seismic-induced track irregularities occurred in positions where high-speed railway bridges are involved. Taking a five-span high-speed railway simply supported beam bridge as the engineering example, the corresponding nonlinear system model, with CRTS II slab ballastless track, is established by using ANSYS finite element analysis software. The distribution mode of post-earthquake track residual irregularity is studied, the statistical characteristics of its power spectral density are analyzed, and a representative seismic-induced track geometric irregularity spectrum is constructed. The effects of the site categories and the epicenter distance on seismic-induced track spectrum are also discussed. The results show that after the earthquake, the alignment irregularity is significant, while the vertical, cross-level and gauge irregularities can be ignored. The amplitude of track geometric irregularity, caused by earthquake, increases significantly with the increase of ground motion intensity. The seismic-induced track spectrum obeys lognormal distribution at all frequencies. The track spectra almost coincide for all five site categories, thus, the impact of site categories on the seismic-induced track spectrum of high-speed railway bridges is considered negligible. Due to the pulse effect, the seismic-induced track spectrum of near-field earthquakes is significantly larger than that of far-field earthquakes.

In nonsmall cell lung cancers (NSCLC), near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) has proven to be an efficient approach for locating pulmonary nodules and pulmonary sentinel lymph nodes. However, due to a lack of tumor selectivity, ICG's use as a photosensitizer for photothermal therapy (PTT) and photodynamic therapy (PDT) is restricted. In the current study, we aimed to develop a type of high-performance NIR nanoparticle formulated with ICG to enhance its targeted efficacy and tumor specificity on NSCLC. An ICG-osimertinib nanoparticle (ICG-Osi) was self-assembled through

Neuroglioma is the most common malignant tumor in the central nervous system and still has a poor prognosis. Here, we investigated the prognostic value of long non-coding RNAs(lncRNAs) in glioblastoma. We first analyzed the lncRNA expression profiles of glioblastoma (GBM) in The Cancer Genome Atlas database and selected the most differential survival genes (lncRNA RP4-669H2.1) for further validation. We then performed qRT-PCR using samples of 88 glioblastoma patients treated in our department between January 2011 and December 2017 that were retrospectively selected to validate the prognostic value of RP4-669H2.1expression in glioblastoma. Using a Cox multivariate analysis, we explored the prognostic value of RP4-669H2.1 and analyzed whether it was an independent prognostic factor. This analysis confirmed that the RP4-669H2.1 expression was significantly associated with glioblastoma-associated mortality in this patient cohort (P =1.80E–05) in TCGA database. In fact, the overall survival (OS) of the RP4-669H2.1 high-expression group (78 cases) was lower than that of the low-expression group (49 cases) (P = 4.6E–06) in TCGA database. Moreover, the TNM stage of the RP4-669H2.1 high-expression group was higher than that of the RP4-669H2.1 low-expression group (P = 0.001). A multivariate analysis further showed that a higher TNM stage (OR = 2.167, 95% CI: 1.349–3.479) and a higher RP4-669H2.1 expression (OR = 2.933, 95% CI: 1.122–7.663) were independent risk factors for the OS of glioblastoma patients. Finally, we predicted the target genes of RP4-669H2.1 using a Multi Experiment Matrix and annotated their biological functions. We observed that the target genes of RP4-669H2.1 were mainly enriched in biological functions related to DNA-binding transcription factor activity. Among these, we selected SMAD6 because the expression of RP4-669H2.1 was positively correlated with that of SMAD6 in glioblastoma. Overall, we conclude that the upregulation of RP4-669H2.1 is an independent poor prognosis factor for glioblastoma and that it can regulate the DNA-binding activity of transcription factors.

Background Although obesity is caused by different factors, individual susceptibility to obesity differs among people under the same circumstances. The microbiota in the caecum or fresh faeces and metabolites in blood or urine contribute to obesity resistance; however, the microbiota or metabolites in the small intestine have not been extensively studied. Methods To investigate the relationship between the microbiota or metabolites in the small intestine and susceptibility to obesity, eighty-eight male C57BL/6 mice were fed a high-fat diet (HFD) for 8 weeks to establish two models of obesity and obesity resistance. For further study, six mice were chosen from among the obesity models, and twelve mice were randomly chosen from among the obesity resistance models. After fasting plasma glucose and behavioural testing, the mice were fed in single cages for another 4 weeks to observe their weight and food intake. All mice were sacrificed at 20 weeks of age. Serum ALT, AST, HDL, LDL, TG and TC levels were measured using an automatic biochemical analyser. The microbiota and metabolites in the small intestine contents were analysed using 16 S sequencing and an ultrahigh-performance liquid chromatographic system, respectively. Transcripts in the jejunum were evaluated using full-length transcriptome sequencing and verified by qPCR. Results The results showed that HFD induced depression and anxiety behaviours and higher fasting plasma glucose, ALT, AST, HDL, LDL, TG and TC levels in the obese mice; however, these levels were improved in obese resistance mice. The correlation analysis showed that the phosphatidylcholine, TG, and phosphatidylethanolamine levels were higher in obese mice and correlated positively with intestinal microflora (Desulfovibrio and Gemella) and the Cxcl10 gene. A higher abundance of Clostridium_sensu_stricto_1 in obesity-resistant mice correlated negatively with the metabolite contents (neuromedin N and enkephalin L) and Pck1 gene expression and correlated positively with certain metabolites (5-hydroxy-L-tryptophan, cinnamyl alcohol and 1 H-indole-3-acetamide) and genes expression (Gdf15, Igfbp6 and Spp1). Conclusion Clostridium_sensu_stricto_1, neuromedin N, enkephalin L, Pck1, 5-hydroxy-L-tryptophan, Cxcl10 and cinnamyl alcohol may be novel biomarkers in the small intestine for obesity/obesity resistance. These might be helpful for obesity prevention or for treating obese patients.

The SARS-CoV-2 variants have been emerging and have made great challenges to current vaccine and pandemic control strategies. It is urgent to understand the current immune status of various Chinese populations given that the preexisting immunity has been established by national vaccination or exposure to past variants. Using sera from 85 individuals (including 21 convalescents of natural infection, 15 cases which suffered a breakthrough infection after being fully vaccinated, and 49 healthy vaccinees), we showed significantly enhanced neutralizing activities against SRAS-CoV-2 variants in convalescent sera, especially those who had been fully vaccinated. The neutralizing antibodies against Omicron were detectable in 75% of convalescents and 44.9% of healthy vaccinees ( p = 0.006 ), with a GMT of 289.5, 180.9-463.3, and 42.6, 31.3-59, respectively. However, the neutralizing activities were weaker in young convalescents ( aged < 18 y ), with a detectable rate of 50% and a GMT of 46.4 against Omicron. We also examined and found no pan-sarbecovirus neutralizing activities in vaccinated SARS-CoV-1 survivors. A booster dose could further increase the breadth and magnitude of neutralization against WT and variants of concern (VOCs) to different degrees. In addition, we showed that COVID-19-inactivated vaccines can elicit Omicron-specific T-cell responses. The positive rates of ELISpot reactions were 26.7% (4/15) and 43.8% (7/16) in the full vaccination group and the booster vaccination group, respectively, although without statistically significant difference. The neutralizing antibody titers declined while T-cell responses remain consistent over 6 months. These findings will inform the optimization of public health vaccination and intervention strategies to protect diverse populations against SARS-CoV-2 variants. Advances . Breakthrough infection significantly boosted neutralizing activities against SARS-CoV-2 variants as compared to booster immunization with inactivated vaccine. Vaccine-induced virus-specific T-cell immunity, on the other hand, may compensate for the shortfall. Furthermore, the public health system should target the most vulnerable group due to a poorer protective serological response in both infected and vaccinated adolescents.

Background Kidney function declines naturally with advancing age. Therefore an age-adapted estimated glomerular filtration rate (eGFR) threshold has been proposed instead of the fixed threshold for CKD definition. This study aims to describe and compare the profile of CKD patients defined by these two criteria in a Chinese population. Method We recruited adult participants with selected biochemical tests from the Chinese Physiological Constant and Health Condition survey conducted from 2007 to 2011, with the GFR estimated by the Chronic Kidney Disease Epidemiology Collaboration formula. The age-adapted threshold of eGFR is 75, 60 and 45 ml/min/1.73 m2 for the population 64 years, respectively. The fixed threshold is 60 ml/min/1.73 m2 for all ages. Results Among the recruited 23 438 participants, 480 were diagnosed with CKD by fixed threshold criteria, while 391 were diagnosed with CKD by age-adapted criteria. Patients diagnosed by fixed threshold criteria were significantly older (66.4 versus 43.4 years; P Conclusion An age-adapted criterion is more closely associated with CVD risk factors and CKD-related diseases compared with fixed threshold criteria.

Type 2 diabetes mellitus (T2DM) is worldwide epidemic, which challenges the health of the public. The pathological hyperactivity of cyclin-dependent kinase 5 (Cdk5) contributes to the pathogenesis of T2DM. P5, a peptide derived from the Cdk5 activator p35, shows excellent performance as a Cdk5 activity inhibitor. However, its inhibitory effect and functional regulation on Cdk5 activity needs to be confirmed. In this study, we conjugated P5 with a fluorescein isothiocyanate (FITC) tag at the N-terminus and a TAT protein transduction domain, an 11-amino acid peptide, at the C-terminus to synthesize TFP5, which was used to inhibits Cdk5 activity. We then evaluated the efficiency of TFP5 in treating T2DM. We demonstrated that TFP5 effectively penetrated pancreatic β-cells, inhibited the pathological hyperactivity of Cdk5, enhanced insulin secretion, and protected penetrated pancreatic β-cells (MIN6 cells) from apoptosis in pancreatic tissues of db/db mice (type II diabetes mice). Furthermore, we found that TFP5 reduced inflammation in pancreatic islets by reducing the expression of inflammatory cytokines, including TGF-β1, TNF-α, and IL-1β. These data indicates that the TFP5 peptide is a promising candidate for T2DM treatment.

In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices, radio frequency (RF) signals have been relied upon for transferring wireless power to them. The joint coordination of wireless power transfer (WPT) and wireless information transfer (WIT) yields simultaneous wireless information and power transfer (SWIPT) as well as data and energy integrated communication network (DEIN). However, as a promising technique, few efforts are invested in the hardware implementation of DEIN. In order to make DEIN a reality, this paper focuses on hardware implementation of a DEIN. It firstly provides a brief tutorial on SWIPT, while summarising the latest hardware design of WPT transceiver and the existing commercial solutions. Then, a prototype design in DEIN with full protocol stack is elaborated, followed by its performance evaluation.

The ranking of power generation sources is a very important prerequisite for power generation installation planning and power supply security. This study proposed a new multi-criteria system for ranking regional power generation sources in one country, including resources, economy, technology, environment, and society, using 11 sub-criteria. Based on the system, a novel decision-maker (DMs) preference-based integrated MCDM framework involving four methods (Visekriterijumsko Kompromisno Rangiranje (VIKOR), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), and Weighted Sum Method (WSM)) was developed for ranking six power generation sources (thermal, nuclear, wind, hydro, solar PV, and biomass) at the level of China's 30 provinces. Six different preferences of DMs are considered in the ranking according to five criteria. The results show that wind should be the power generation source given the top priority in most provinces in China whereas nuclear power and thermal power are the last choice for 26 provinces. Biomass is the most preferable power source for 17 provinces based on technological preference in which DMs regard the technology criteria is prior to all other criteria. Thermal power would still the preferred or secondary power source for provinces rich in coal resources such as Shanxi, Inner Mongolia, Henan, and Shaanxi.

Background T helper (Th) cell cytokine imbalances have been associated with the pathophysiology of chronic obstructive pulmonary disease (COPD), including the Th1/Th2 and Th17/T regulatory cells (Treg) paradigms. Clarifying cytokine profiles during COPD acute exacerbation (AE) and their relationships with clinical manifestations would help in understanding the pathogenesis of disease and improve clinical management. Materials and Methods Eighty seven patients admitted to the hospital with AEs of COPD were included in this study, and follow-up was conducted after discharge (every 30 days, for a total of 120 days). Sputum samples of patients at different time points (including at admission, discharge, and follow-up) were collected, and sputum cytokine profiling (12 cytokines in total) was performed using a Luminex assay. Results According to the cytokine profiles at admission, patients were divided into three clusters by a k-means clustering algorithm, namely, Th1high Th17high (n=26), Th1lowTh17low (n=56), and Th1high Th17low (n=5), which revealed distinct clinical characteristics. Patients with Th1high Th17low profile had a significantly longer length of non-invasive ventilation time and length of hospital stay than patients with Th1high Th17high profile (7 vs 0 days, 22 vs 11 days, respectively, p < 0.05), and had the highest AE frequency. Sputum levels of Th17 cytokines (IL-17A, IL-22, and IL-23) during AE were negatively correlated with AE frequency in the last 12 months (r = -0.258, -0.289 and -0.216, respectively, p < 0.05). Moreover, decreased sputum IL-17A levels were independently associated with increased AE frequency, with an OR (95% CI) of 0.975 (0.958-0.993) and p = 0.006. Conclusion Th1/Th17 imbalance during AE is associated with the severity of COPD. Decreased Th17 cytokine expression is correlated with increased AE frequency. The Th1/Th17 balance may be a specific target for the therapeutic manipulation of COPD.

Estimating hospital mortality of patients is important in assisting clinicians to make decisions and hospital providers to allocate resources. This paper proposed a multi-task recurrent neural network with attention mechanisms to predict patients' hospital mortality, using reconstruction of patients' physiological time series as an auxiliary task. Experiments were conducted on a large public electronic health record database, i.e., MIMIC-III. Fifteen physiological measurements during the first 24 h of critical care were used to predict death before hospital discharge. Compared with the conventional simplified acute physiology score (SAPS-II), the proposed multi-task learning model achieved better sensitivity (0.503 ± 0.020 versus 0.365 ± 0.021), when predictions were made based on the same 24-h observation period. The multi-task learning model is recommended to be updated daily with at least a 6-h observation period, in order for it to perform similarly or better than the SAPS-II. In the future, the need for intervention can be considered as another task to further optimize the performance of the multi-task learning model.

Summary Purpose Prognostic biomarkers help triage initial patients and inform targeted therapy selection. Here, we explored the role of progranulin (PGRN)—implicated in processes ranging from inflammation to neurodegeneration—in patients with community-acquired pneumonia (CAP). Methods A prospective observational cohort study was conducted during 2017. Patients who required invasive mechanical ventilation and/or had septic shock and were discharged from the hospital were cohort II. Those who died at the hospital were cohort III. Remaining patients discharged from the hospital were cohort I. The primary endpoint was that patients progressed to served as cohort II; the secondary endpoint was that patients progressed to served as cohort III. Serum PGRN levels were detected by ELISA. Results A total of 280 patients constituted the study cohort. 194 (69.3%) were categorized into cohort I, 61 (21.8%) were categorized into cohort II, and 25 (8.9%) were categorized into cohort III. Serum PGRN levels were increased in CAP patients, independently of etiology. Adjusting for clinical parameters, the odds ratios (95%CI) of cohort III and combined cohort II–III were 34.968 (3.743–326.692) and 3.741 (1.496–9.351), respectively, comparing lowest-to-highest quartile PGRN levels. PGRN exhibited high accuracy in predicting 30-day mortality, with AUC 0.862. PGRN combined with CURB-65 or PSI significantly improved prediction performance. Cox proportional regression analysis showed PGRN was an independent predictor for 30-day mortality risk. Cox survival curves confirmed PGRN ≥89.51 ng/mL had a significantly higher mortality rate than PGRN Conclusion Higher PGRN levels at admission were associated with higher odds of poor prognosis. PGRN can improve the prognostic power of CURB-65 or PSI, so PGRN could be apparently a prognostic biomarker for assisting triage of CAP patients.

Unlike traditional industrial robots, indoor service robots are usually required to possess high intelligence, such as the skills of flexible moving, precise spacial perceiving. And high intelligence is always accompanied by consuming complicated and expensive computation resources. One solution for indoor service robots is centralization of expensive computation resource so that it is possible to design a low cost client with a high-intelligence brain. However, as a fundamental intelligence function for mobile indoor robots, if a real-time visual Simultaneously Localization and Mapping (vSLAM) system is split into client and brain, it will be confronted with new challenges, such as the barrier of instant data sharing and performance degradation brought by network delay in between. To solve the problem, we focus on a framework and approach of cloud-based visual SLAM in this paper, and provide an efficient solution to offload the expensive computation and reduce the cost of robot clients. The integrated system is distributed in a 3-level Cloud with light-weight tracking, high precision dense mapping, and map sharing. Based on recent excellent algorithms, our system is able to run a real-time sparse tracking on the client, and a real-time dense mapping on the cloud server, which outputs an explicit 3D dense map. Only keyframes are sent to the local cloud center to reduce the network bandwidth requirement. Dense geometric pose estimation besides feature-based methods is computed to make the system resistant to feature-less indoor scenes. The camera poses associated with keyframes are optimized on the local computing cloud center, and are sent back to the client to decrease the trajectory drift. We evaluate the system on the Technical University of Munich (TUM) datasets, Imperial College London and National University of Ireland Maynooth (ICL-NUIM) datasets, and the real data captured by our robot in terms of visual odometry on the client side and dense maps generated on the server cloud. Qualitative and quantitative experiments show our cloud visual SLAM system is able to bear the network delay in Local Area Network (LAN), and it is an efficient vSLAM solution for indoor service robots with high intelligence from a centric brain.

Using the complex sink-source model (CSSM) and the Hertz potential method (HPM), the electromagnetic field expressions of tightly focused ultrashort azimuthally polarized pulses can be obtained. By numerically solving the relativistic Newton-Lorentz equation, the acceleration and confinement of electrons by the sub-cycle and few-cycle azimuthally polarized ultrashort pulses in vacuum are studied. Considering the radiation reaction force, it is found that electrons with an initial kinetic energy of less than 1MeV can be accelerated to hundreds of MeV and can be confined in the range of less than 1 micron for hundreds of femtoseconds in the direction perpendicular to the pulse propagation (transverse direction) by the pulses. With the increase of the beam waist and the intensity of the pulse, the electrons can obtain the exit kinetic energy exceeding 1GeV. When electrons are accelerated by the few-cycle pulses, the confined time of the electrons in the transverse direction is three times longer than that of the sub-cycle pulse. When the initial velocity of the electron points to a point in front of the focus, the electron can obtain the maximum exit kinetic energy. The change of the angular frequency corresponding to the spectral peak of the electromagnetic radiation from the electron acceleration with the electric field amplitude parameter E0 of the pulse is studied. The phenomena of redshift and blueshift of the spectrum peak frequency of the electron radiation with the E0 are found. These studies provide the methods to confine the movement of electrons in certain directions and accelerate electrons in the same time.

The emerging SARS-CoV-2 variants have made great challenges to current vaccine and pandemic control strategies. B.1.1.529 (Omicron), which was classified as a variant of concern (VOC) by the World Health Organization on November 26th, 2021, has quickly become the dominant circulating variant and causing waves of infections. It is urgent to understand the current immune status of the general population given that pre-existing immunity has been established by national vaccination or exposure to past variants. Using sera from 85 individuals (including 21 convalescents of natural infection, 15 cases suffered a breakthrough infection after vaccination, and 49 vaccinated participants without infection history), we showed that the cross-neutralizing activity against VOCs such as Omicron can be detected in 53 (62.4%) cases, although less potent than against the Wuhan-1 strain (WT), with a 3.9-fold reduction in geometric mean neutralizing titer (GMT) (130.7, 95% CI 88.4-193.3 vs 506, 355.8-719.7, respectively). Subgroup analysis revealed significantly enhanced neutralizing activity against WT and VOCs in Delta convalescent sera. The neutralizing antibodies against Omicron were detectable in 75% of convalescents and 44.9% of healthy donors (p = 0.006), with a GMT of 289.5, 180.9-463.3 and 42.6, 31.3-59, respectively. However, the protective effect against VOCs was weaker in young convalescents (aged < 18y), with a detectable rate of 50% and a GMT of 46.4 against Omicron, similar to vaccinees. The pan-sarbecovirus neutralizing activities were not observed in vaccinated SARS-CoV-1 survivors. A booster dose significantly increased the breadth and magnitude of neutralization against WT and VOCs to different degrees than full vaccination. In addition, we showed that COVID-19 inactivated vaccines can elicit Omicron-specific T cell responses. The positive rates of ELISpot reactions were 26.7% (4/15) and 43.8% (7/16) in the full vaccination group and the booster vaccination group, respectively. The neutralizing antibody titers declined while T-cell responses remain robust over 6 months. These findings will inform the optimization of public health vaccination and intervention strategies to protect diverse populations against SARS-CoV-2 variants.

Background Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential. Methods We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses. Results An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%. Conclusions A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

Community-acquired pneumonia (CAP) is a lower respiratory tract infection. It is one of the commonest infectious diseases and the third leading cause of death worldwide. However, the epidemiological profiles of CAP in southeastern China are unknown. Data of inpatients and outpatients diagnosed with CAP from January 1, 2015 to December 31, 2020 were obtained from the National Healthcare Big Data in Fuzhou (Fuzhou Database). This database covers medical data from 37 hospitals and 159 community health service stations. The incidence rate, treatment pattern, and direct medical costs of CAP were assessed using clinical data. A total of 8,156,237 patients were enrolled, with a mean age of 33.72 ± 20.88 years. The overall incidence rate of CAP was 3.13 (95% confidence interval [CI]: 3.11–3.15) per 1000 person-years (PY), with 15.97 (95% CI: 15.85–16.08) per 1000 PY in children below 5 years old and 2.62 (95% CI: 2.57–2.66) per 1000 PY in the elderly ≥60 years. The cost per outpatient was $242.83 ± 341.62, and the cost per inpatient was $4,530.4 ± 9,151.68. The three most used therapeutic drugs in patients with CAP are cefotaxime, moxifloxacin, and azithromycin. In addition, despite the ability of both imported and domestic pneumococcal conjugate vaccines to reduce the incidence rate of CAP, the current vaccination coverage rates were relatively low. We suggest that more attention should be paid to the disease burden of CAP, especially due to its great economic burden in China.

Objective:As the number of recovering COVID-19 patients increases worldwide, the persistence of symptoms and signs through the post-acute phase indicates an urgent need for prolonged follow-up care. To explore existing data about post-acute COVID-19 syndrome, this meta-analysis assesses the prevalence of persistent manifestations in multiple systems and abnormalities in lung function, as well as their related risks in patients with various severities.Methods:Articles about discharged COVID-19 patients (published from January 1, 2020 to February 23, 2021) were obtained by searching four databases. Cohort studies with follow-up periods >1 month post-discharge or >2 months post-admission were included.Results:A total of 4,478 COVID-19 patients from 16 cohort studies were included in this meta-analysis. Fatigue or weakness (47%) were the most prevalent physical effects of post-acute COVID-19 syndrome, while psychosocial (28%) symptoms were the most common manifestations among several systems. Abnormalities in lung function of recovering patients, i.e., DLCO Conclusions:Our research indicates that patients recovering from COVID-19 manifest long-term, multi-system symptoms, and the adverse effects on psychosocial health and lung functions were the most extensive and persistent. These findings together may facilitate much needed in-depth study of clinical treatments for long-term, post-acute phase symptoms that affect a great number of recovering COVID-19 patients.

Deep learning (DL) models have demonstrated great potential in cuffless blood pressure (BP) estimation under static conditions, while the performance under dynamic conditions was still not fully validated. This study developed a DL model using population data for training and followed by individualized fine-tuning to directly learn features from multisensory signals including electrocardiogram (ECG), photoplethysmogram (PPG) and PPG derivatives for beat-to-beat BP estimation under water drinking. 25 healthy subjects were recruited, and the leave-one-subject-out approach was used to evaluate the model performance. The results showed that individualized fine-tuning using a small amount of individual baseline data did not change the tracking capability of the model, while can largely reduce the individual bias in dynamic BP estimation, with the mean absolute errors decreased from 13.43 to 9.49 mmHg and 8.48 to 5.54 mmHg for systolic BP and diastolic BP, respectively. It was also found that the model presented better results around the baseline BP levels than that at larger deviations from the baseline, indicating that future work should incorporate individual dynamic data in the fine-tuning to improve dynamic BP estimation further.

Zika virus (ZIKV) infection during pregnancy has been linked to congenital abnormalities, such as microcephaly in infants. An efficacious vaccine is desirable for preventing the potential recurrence of ZIKV epidemic. Here, we report the generation of an attenuated ZIKV (rGZ02a) that has sharply decreased virulence in mice but grows to high titers in Vero cells, a widely approved cell line for manufacturing human vaccines. Compared to the wild-type ZIKV (GZ02) and a plasmid-launched rGZ02p, rGZ02a has 3 unique amino acid alterations in the envelope (E, S304F), nonstructural protein 1 (NS1, R103K), and NS5 (W637R). rGZ02a is more sensitive to type I interferon than GZ02 and rGZ02p, and causes no severe neurological disorders in either wild-type neonatal C57BL/6 mice or type I interferon receptor knockout (Ifnar1(−/−)) C57BL/6 mice. Immunization with rGZ02a elicits robust inhibitory antibody responses with a certain long-term durability. Neonates born to the immunized dams are effectively protected against ZIKV-caused neurological disorders and brain damage. rGZ02a as a booster vaccine greatly improves the protective immunity primed by Ad2-prME, an adenovirus-vectored vaccine expressing ZIKV prM and E proteins. Our results illustrate that rGZ02a-induced maternal immunity can be transferred to the neonates and confer effective protection. Hence, rGZ02a may be developed as an alternative live-attenuated vaccine and warrants further evaluation. IMPORTANCE Zika virus (ZIKV), a mosquito-borne flavivirus that has caused global outbreaks since 2013, is associated with severe neurological disorders, such as Guillian-Barré syndrome in adults and microcephaly in infants. The ZIKV epidemic has gradually subsided, but a safe and effective vaccine is still desirable to prevent its potential recurrence, especially in countries of endemicity with competent mosquito vectors. Here, we describe a novel live-attenuated ZIKV, rGZ02a, that carries 3 unique amino acid alterations compared to the wild-type GZ02 and a plasmid-launched rGZ02p. The growth capacity of rGZ02a is comparable to GZ02 in Vero cells, but the pathogenicity is significantly attenuated in two mice models. Immunization with rGZ02a elicits robust inhibitory antibody responses in the dams and effectively protects their offspring against ZIKV disease. Importantly, in a heterologous prime-boost regimen, rGZ02a effectively boosts the protective immunity primed by an adenovirus-vectored vaccine. Thus, rGZ02a is a promising candidate for a live-attenuated ZIKV vaccine.

Electric vehicles (EVs) play a crucial role in addressing climate change and urban air quality concerns. China has emerged as the global largest EV market with 1.2 million EVs sold in 2018. This study established a novel life cycle energy use and emission inventory collecting up-to-date data including the electricity generation mix, emission controls in the power and industrial sectors, and the energy use in the fuel transport to estimate the well-to-wheels (WTW) greenhouse gas (GHG), and air pollutant emissions for battery electric vehicles (BEVs) and gasoline passenger vehicles in China. The results show that an average BEV has 35% lower WTW GHG emissions than an average gasoline car. BEVs reduce volatile organic compounds (VOCs) and nitrogen oxides (NOX) emissions by 98% and 34%, respectively, but have comparable or slightly higher primary fine particulate matter (PM2.5) and sulfur dioxide (SO2) emissions. Compact and small-size vehicles generally have lower GHG and air pollutant emissions than mid- and large-size vehicles. Class A vehicles contribute the most in the absolute amount of GHG and air pollutant emissions and therefore have the biggest potential for emission reduction. Our results suggest that global policymakers should continue to promote the transition to clean power sources, emission control, and fuel economy regulations, which are critical to enhancing emission mitigation benefits of BEVs. We also suggest EV development strategies should be formulated targeting vehicle class with the biggest emission mitigation potentials.

Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy-to-monitor and highly stable materials for diagnosing Community-acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP-related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA-miRNA-mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus-infection-related signaling pathways (such as HTLV-1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP-related regulatory interactions that should inform future hypothesis-driven research into the causes and potential treatment of this widespread and frequently fatal disease.

The inadequate representativeness of driving cycles used by regulatory lab tests is one significant factor leading to the large discrepancy between real-world fuel consumption and type-approval levels. Onboard measurement devices have been used in previous researches to collect vehicle activity data but the amount of data is sometimes limited. With second-by-second GPS trajectory data of 459 private passenger cars, covering over 17,000 sampling days, this study used big-data mining techniques to study the variations in real-world driving cycles. A Markov chain method was developed to generate typical driving cycles that have representative features of real-world driving. As a case study, two typical cycles, Off-peak cycle, and Peak cycle are constructed from six sub-cycles representing different road types and travel periods. The travel dynamics indicated the New European Driving Cycle (NEDC) would be too mild to represent real-world driving in China. The simulation results of vehicle fuel consumption showed that different driving cycles could lead to different lab-to-road gaps when comparing with NEDC type-approval levels. For example, the fuel consumption (median value) of Off-peak cycle and Peak cycle were higher than the NEDC type-approval level by 29.3% and 37.5%, respectively. This study highlights the importance of addressing real-world features in improving future fuel economy regulations. The practical approach to generate representative driving cycles ensured by massive travel profiles can be employed reliably for fuel consumption and exhaust emission assessment in the future.

This study proposes comprehensive evaluation criteria, involving aspects of energy, economy, environment, technology, and society (E3TS), for the development and utilization of renewable energy (RE). The criteria consist of 22 indicators. The comprehensive performance, from 2011 to 2015, of 30 provincial regions in China with respect to renewable energy development and utilization (REDU) was evaluated on the basis of the E3TS criteria, using an analytic network process (ANP). The results show that the total comprehensive performance (2011–2015) of all the 30 provincial regions of China improved in general. There was a marked improvement in technology performance. Qinghai, Yunnan, and Sichuan ranked the top three in comprehensive performance of REDU, while the comprehensive performance of Shaanxi, Hainan, and Henan were the lowest. During the study period, while the comprehensive performance of most provincial regions such as Ningxia and Xinjiang increased, that of five provincial regions, including Tianjin and Hainan, decreased. The regional comprehensive performance was severely affected by the installed capacity and power generation of RE.

Recombinant influenza A viral (IAV) vectors are potential to stimulate systemic and mucosal immunity, but the packaging capacity is limited and only one or a few epitopes can be carried. Here, we report the generation of a replication-competent IAV vector that carries a full-length HIV-1 p24 gene linked to the 5′-terminal coding region of the neuraminidase segment via a protease cleavage sequence (IAV-p24). IAV-p24 was successfully rescued and stably propagated, and P24 protein was efficiently expressed in infected mammalian cells. In BALB/c mice, IAV-p24 showed attenuated pathogenicity compared to that of the parental A/PR/8/34 (H1N1) virus. An intranasal inoculation with IAV-p24 elicited moderate HIV-specific cell-mediated immune (CMI) responses in the airway and vaginal tracts and in the spleen, and an intranasal boost with a replication-incompetent adenovirus type 2 vector expressing the HIV-1 gag gene (Ad2-gag) greatly improved these responses. Importantly, compared to an Ad2-gag prime plus IAV-p24 boost regimen, the IAV-p24 prime plus Ad2-gag boost regimen had a greater efficacy in eliciting HIV-specific CMI responses. P24-specific CD8(+) T cells and antibodies were robustly provoked both systemically and in mucosal sites and showed long-term durability, revealing that IAV-p24 may be used as a mucosa-targeted priming vaccine. Our results illustrate that IAV-p24 is able to prime systemic and mucosal immunity against HIV-1 and warrants further evaluation in nonhuman primates. IMPORTANCE An effective HIV-1 vaccine remains elusive despite nearly 40 years of research. CD8(+) T cells and protective antibodies may both be desirable for preventing HIV-1 infection in susceptible mucosal sites. Recombinant influenza A virus (IAV) vector has the potential to stimulate these immune responses, but the packaging capacity is extremely limited. Here, we describe a replication-competent IAV vector expressing the HIV-1 p24 gene (IAV-p24). Unlike most other IAV vectors that carried one or several antigenic epitopes, IAV-p24 stably expressed the full-length P24 protein, which contains multiple epitopes and is highly conserved among all known HIV-1 sequences. Compared to the parental A/PR/8/34 (H1N1) virus, IAV-p24 showed an attenuated pathogenicity in BALB/c mice. When combined with an adenovirus vector expressing the HIV-1 gag gene, IAV-p24 was able to prime P24-specific systemic and mucosal immune responses. IAV-p24 as an alternative priming vaccine against HIV-1 warrants further evaluation in nonhuman primates.