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BackgroundUlcerative colitis (UC) is a chronic inflammatory bowel disease (IBD) influenced by multiple factors. Berberine, an isoquinoline alkaloid derived from the root and bark of Coptis chinensis Franch., has shown promise in managing UC, but its underlying mechanisms remain unclear.MethodsTo elucidate the relationship between berberine, ulcerative colitis (UC), and the organism’s metabolome, we established a dextran sulfate sodium (DSS)-induced UC model in rats. Colonic tissue was collected for histopathological examination, while plasma samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with dynamic Multiple Reaction Monitoring (dMRM). This approach, characterized by its short analysis time of 20 min per sample, excellent reproducibility, and straightforward data processing, allowed for the comprehensive detection of a wide array of metabolites, including amino acids, lipids, and organic acids, many of which are implicated in the pathophysiology of UC.ResultsOur results showed that berberine modulated the metabolic disturbances of 33 compounds in the plasma of UC rats, primarily including amino acids, pyrimidines, organic phosphoric acids, fatty acyls, and organonitrogen compounds. These altered metabolites were associated with various pathways, such as amino acid metabolism, glutathione metabolism, nicotinate and nicotinamide metabolism, taurine and hypotaurine metabolism, pyrimidine metabolism, glyoxylate and dicarboxylate metabolism, and the citrate cycle (TCA cycle). Notably, 3-hydroxyproline, homocysteic acid, L-threonine, L-lysine, carbamoyl phosphate, O-phosphoethanolamine, taurine, leucine, and phosphorylcholine exhibited significant differences between the Treatment and Model groups, with levels reverting to those of the Control group (p < 0.001). These findings suggested that these compounds may serve as potential plasma biomarkers for UC.ConclusionThis study provided valuable insights into the mechanism by which berberine exerted its therapeutic effects on UC through metabolomics. Our results highlighted berberine’s potential to modulate key metabolic pathways and restore the levels of several metabolites, suggesting its utility as a therapeutic agent for UC. These findings underscored the importance of metabolomics in understanding the pathophysiology and treatment of UC.

Abstract Background Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage rates of human papillomavirus (HPV) vaccines and routine screening are low in most developing countries and even some developed countries. This study aimed to explore the benefit of an artificial intelligence-assisted cytology (AI) system in a screening program for a cervical cancer high-risk population in China. Methods A total of 1231 liquid-based cytology (LBC) slides from women who underwent colposcopy at the Chinese PLA General Hospital from 2018 to 2020 were collected. All women had received a histological diagnosis based on the results of colposcopy and biopsy. The sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), false-positive rate (FPR), false-negative rate (FNR), overall accuracy (OA), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and Youden index (YI) of the AI, LBC, HPV, LBC + HPV, AI + LBC, AI + HPV and HPV Seq LBC screening strategies at low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL) thresholds were calculated to assess their effectiveness. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic values of the different screening strategies. Results The Se and Sp of the primary AI-alone strategy at the LSIL and HSIL thresholds were superior to those of the LBC + HPV cotesting strategy. Among the screening strategies, the YIs of the AI strategy at the LSIL + threshold and HSIL + threshold were the highest. At the HSIL + threshold, the AI strategy achieved the best result, with an AUC value of 0.621 (95% CI, 0.587–0.654), whereas HPV testing achieved the worst result, with an AUC value of 0.521 (95% CI, 0.484–0.559). Similarly, at the LSIL + threshold, the LBC-based strategy achieved the best result, with an AUC of 0.637 (95% CI, 0.606–0.668), whereas HPV testing achieved the worst result, with an AUC of 0.524 (95% CI, 0.491–0.557). Moreover, the AUCs of the AI and LBC strategies at this threshold were similar (0.631 and 0.637, respectively). Conclusions These results confirmed that AI-only screening was the most authoritative method for diagnosing HSILs and LSILs, improving the accuracy of colposcopy diagnosis, and was more beneficial for patients than traditional LBC + HPV cotesting.

The Mycobacterium tuberculosis variant bovis (M. bovis) is a highly pathogenic environmental microorganism that causes bovine tuberculosis (bTB), a significant zoonotic disease. Currently, “test and culling” is the primary measure for controlling bTB, but it has been proven to be inadequate in animals due to their high susceptibility to the pathogen. Selective breeding for increased host resistance to bTB to reduce its prevalence is feasible. In this study, we found a vital host-dependent factor, RBMX2, that can potentially promote M. bovis infection. By knocking RBMX2 out, we investigated its function during M. bovis infection. Through transcriptome sequencing and alternative splicing transcriptome sequencing, we concluded that after M. bovis infection, embryo bovine lung (EBL) cells were significantly enriched in RNA splicing associated with apoptosis compared with wild-type EBL cells. Through protein/molecular docking, molecular dynamics simulations, and real-time quantitative PCR, we demonstrated that RBMX2 promotes the apoptosis of epithelial cells by upregulating and binding to apoptotic peptidase activating factor 1 (APAF-1), resulting in the alternative splicing of APAF-1 as a retention intron. To our knowledge, this is the first report of M. bovis affecting host epithelial cell apoptosis by hijacking RBMX2 to promote the intron splicing of downstream APAF-1. These findings may represent a significant contribution to the development of novel TB prevention and control strategies.

Abstract Spiders are representative arthropods of adaptive radiation. The high-quality genomes have only been reported in several web weaver spider species, leaving the wandering spiders’ genomic information scarce. The pond wolf spider, Pardosa pseudoannulata, is a representative species in the retrolateral titial apophysis (RTA) clade. We present a chromosome-level P. pseusoannulata genome assembly of 2.42 Gb in size with a scaffold N50 of 169.99 Mb. Hi-C scaffolding assigns 94.83% of the bases to 15 pseudo-chromosomes. The repeats account for 52.79% of the assembly. The assembly includes 96.2% of the complete arthropod universal single-copy orthologs. Gene annotation predicted 24,530 protein-coding genes with a BUSCO score of 95.8% complete. We identified duplicate clusters of Hox genes and an expanded cuticle protein gene family with 243 genes. The expression patterns of CPR genes change in response to environmental stresses such as coldness and insecticide exposure. The high-quality P. pseudoannulata genome provides valuable information for functional and comparative studies in spiders.

Abstract Background Panax japonicus var. major (PJM) belongs to the well-known ginseng species used in west China for hundreds of years, which has the effects of lung tonifying and yin nourishing, and exerts the analgesic, antitussive, and hemostatic activities. Compared with the other Panax species, the chemical composition and the spatial tissue distribution of the bioactive ginsenosides in PJM have seldom been investigated. Methods Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS) and desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) were integrated for the systematic characterization and spatial tissue distribution studies of ginsenosides in the rhizome of PJM. Considering the great difficulty in exposing the minor saponins, apart from the conventional Auto MS/MS (M1), two different precursor ions list-including data-dependent acquisition (PIL-DDA) approaches, involving the direct input of an in-house library containing 579 known ginsenosides (M2) and the inclusion of the target precursors screened from the MS1 data by mass defect filtering (M3), were developed. The in situ spatial distribution of various ginsenosides in PJM was profiled based on DESI-MSI with a mass range of m/z 100–1500 in the negative ion mode, with the imaging data processed by the High Definition Imaging (HDI) software. Results Under the optimized condition, 272 ginsenosides were identified or tentatively characterized, and 138 thereof were possibly not ever reported from the Panax genus. They were composed by 75 oleanolic acid type, 22 protopanaxadiol type, 52 protopanaxatriol type, 16 octillol type, 19 malonylated, 35 C-17 side-chain varied, and 53 others. In addition, the DESI-MSI experiment unveiled the differentiated distribution of saponins, but the main location in the cork layer and phloem of the rhizome. The abundance of the oleanolic acid ginsenosides was high in the rhizome slice of PJM, which was consistent with the results obtained by UHPLC/QTOF-MS. Conclusion Comprehensive characterization of the ginsenosides in the rhizome of PJM was achieved, with a large amount of unknown structures unveiled primarily. We, for the first time, reported the spatial tissue distribution of different subtypes of ginsenosides in the rhizome slice of PJM. These results can benefit the quality control and further development of PJM and the other ginseng species.

Abstract The traditional identification methods of direct current‐to‐direct current (DC–DC) converters usually consider the common situation where the training and testing sets have the same input voltage. In real‐world applications, the actual input voltage may fluctuate beyond its original value, thus negatively affecting the parameter identification accuracy. Therefore, this paper presents a parameter identification method under fluctuating input voltages. Firstly, to increase the identification accuracy, the paper proposes the coefficient of variation method to extract key features from all time‐ and frequency‐domain features as training data. Then, for fluctuating input voltages, the paper adds the input voltages into the training data to build the parameter identification network based on Dendrite Net. When using the established network to identify component parameters in practical applications, the actual input voltage may change to an unknown value because of irregular fluctuation. Hence, the actual input voltage needs to be identified before identifying the component parameters of a DC–DC converter. Finally, the paper builds the input voltage identification network. By combining the identification results of the actual input voltage, the parameter identification under fluctuating input voltages can be completed. The simulation and hardware experiments results validate the practicability and effectiveness of the proposed method.

With the emergence and vigorous development of 5G technology, there is a significant surge in network usage and traffic, resulting in heightened complexity within network and IT environments. This exponential increase in activity produces a plethora of events, making conventional systems inadequate for the efficient management of 5G networks. In comparison to 4G technology, 5G technology brings forth a host of new features, one of which is the network data analytics function (NWDAF). This function grants network operators the flexibility to either employ their own data analytics methodologies based on machine learning (ML) and deep learning (DL) into their networks. In this paper, we present a dataset named “NWDAF-NFPP” for network function performance time series prediction, collected from a laboratory at China Telecom. The dataset is carefully anonymized to ensure maximum realism and comprehensiveness, while safeguarding sensitive information. It encompasses eight categories of network functions, with data collected at five-minute intervals. The availability of this dataset provides valuable resources for researchers to conduct time series prediction research on network element performance. Following data collection, a total of six models were employed for network element performance prediction, encompassing both machine learning and deep learning approaches. This diverse set of models was carefully chosen to ensure comprehensive coverage of different techniques and algorithms. Through the comparison and analysis of these models, we aim to evaluate their predictive capabilities and identify the most effective approach for network element performance prediction. This comparative analysis will provide valuable insights into the strengths and limitations of each model, aiding in informed decision-making for network optimization and management strategies in the future.

Background: Cohort evidence linking long-term ozone (O3) exposure to mortality remained largely mixed worldwide and was extensively deficient in densely-populated Asia. This study aimed to assess the long-term effects of O3 exposure on all-cause mortality among Chinese adults, as well as to examine potential regional heterogeneity across the globe. Methods: A national dynamic cohort of 42153 adults aged 16+ years were recruited from 25 provinces across Chinese mainland and followed up during 2010–2018. Annual warm-season (April–September) O3 and year-round co-pollutants (i.e., nitrogen dioxide [NO2] and fine particulate matter [PM2.5]) were simulated through validated spatial-temporal prediction models and were assigned to each enrollee in each calendar year. Cox proportional hazards models with time-varying exposures were employed to assess the O3-mortality association. Concentration-response (C-R) curves were fitted by natural cubic spline function to investigate the potential nonlinear association. Both single-pollutant model and co-pollutant models additionally adjusting for PM2.5 and/or NO2 were employed to examine the robustness of the estimated association. The random-effect meta-analysis was adopted to pool effect estimates from the current and prior population-based cohorts (n = 29), and pooled C-R curves were fitted through the meta-smoothing approach by regions. Results: The study population comprised of 42153 participants who contributed 258921.5 person-years at risk (median 6.4 years), of whom 2382 death events occurred during study period. Participants were exposed to an annual average of 51.4 ppb (range: 22.7−74.4 ppb) of warm-season O3 concentration. In the single-pollutant model, a significantly increased hazard ratio (HR) of 1.098 (95% confidence interval [CI]: 1.023−1.179) was associated with a 10-ppb rise in O3 exposure. Associations remained robust to additional adjustments of co-pollutants, with HRs of 1.099 (95% CI: 1.023−1.180) in bi-pollutant model (+PM2.5) and 1.093 (95% CI: 1.018−1.174) in tri-pollutant model (+PM2.5+NO2), respectively. A J-shaped C-R relationship was identified among Chinese general population, suggesting significant excess mortality risk at high ozone exposure only. The combined C-R curves from Asia (n = 4) and North America (n = 17) demonstrated an overall increased risk of all-cause mortality with O3 exposure, with pooled HRs of 1.124 (95% CI: 0.966−1.307) and 1.023 (95% CI: 1.007−1.039) per 10-ppb rise, respectively. Conversely, an opposite association was observed in Europe (n = 8, HR: 0.914 [95% CI: 0.860−0.972]), suggesting significant heterogeneity across regions (P

Objective:. Data comparing the outcomes of MiStent (Micell Technologies, Durham, North Carolina, USA) microcrystalline biodegradable polymer (BP) drug-eluting stent (DES) and those of another post-marketing BP-DES, TIVOLI (EssenTech, Beijing, China) are rare. This study sought to compare the angiographic efficacy and clinical outcomes of the microcrystalline BP sirolimus-eluting stent (SES) system MiStent and those of TIVOLI BP-SES. Methods:. The DESSOLVE-C trial was a prospective, single-blinded, multicenter, randomized trial (NCT02448524), which randomly assigned patients with de novo coronary lesions to receive MiStent or TIVOLI BP-SES by a 1:1 ratio. The primary endpoint was a non-inferiority comparison of in-stent late lumen loss (LLL) by quantitative coronary angiography at 9 months. The secondary endpoint was device-related clinical cardiovascular composite events (target lesion failure (TLF), composite of cardiac death, target vessel myocardial infarction (MI), and clinically driven target lesion revascularization) and 1-year outcomes. Results:. A total of 428 patients (216 patients in the MiStent group and 212 patients in the TIVOLI group) were enrolled and included in an intention-to-treat analysis. MiStent was not only non-inferior but superior to TIVOLI for in-stent LLL at 9 months ((0.23 ± 0.37) mm vs. (0.34 ± 0.48) mm, P for non-inferiority

Malicious software or misbehaving applications have the potential to trigger signaling storms on mobile networks, leading to battery drainage on devices and causing bandwidth overuse at the cell level. Additionally, these storms may result in an excessive signaling load within the mobile operator’s infrastructure. This paper uses a combination of time series prediction, adaptive threshold, and anomaly detection algorithms to predict signaling storms. Whether a signaling storm will be triggered in the future can be determined based on the fluctuation pattern of the data. Our method enables us to identify the top cause of the signaling storm in advance, so that the network optimization team can address the issues that will arise in advance, maximizing the stop-loss. The time series prediction algorithm has significant advantages over the moving average and TFT(Temporal Fusion Transformers), with a WAPE(Weighted Absolute Percentage Error) of only 0.09. Adaptive threshold can avoid treating holiday data as abnormal data, and the accuracy of anomaly detection based on the automatic adaptive threshold is higher than the traditional fixed threshold. In addition, combining the signaling conduction chain can also perform top cause localization to identify the upstream network element instance that first encountered the problem. The entire algorithm not only performs well in the current network but also performs well in artificially generated signaling storm data, pioneering the field of signaling storm prediction.

As the scale of telecommunication networks continues to grow, the structure of network elements becomes increasingly complex. Consequently, the data service has experienced a significant boom, leading to a substantial increase in network failures and equipment alarms. Effectively detecting hidden anomalies within massive network time series presents a significant challenge for network operators during their operation and maintenance tasks. This paper proposes a multi-dimensional sequence anomaly detection method named TransKS that integrates Transform and K-SIGMA on dynamic variable thresholds and applies it on the VoLTE and 5G core network. By designing the Transform multi-dimensional time series predictor, the method carries out parallel modeling and forecasting of the index sequence. It may thoroughly investigate the time dimension correlation relationship of the indicators as well as the linking effect of the indicators. And then we designed an adaptive sliding window approach on validation score by dynamically updating the value K and the threshold interval to detect context abnormalities and evaluate the abnormality of network element indicators quantitatively and reasonably. Experiments show that compared the performance with other algorithms, the TransKS has a higher accuracy rate of anomaly detection. When MAPE=0.01 and k is 4, the accuracy rate is the highest, up to 96.92%, which is at least 2.10% higher than other combined models, and its false positive rate and false positive rate have decreased, only 3.06% and 3.25%.

Introduction: A number of population-based studies have investigated long-term effects of nitrogen dioxide (NO2) on mortality, while great heterogeneities exist between studies. In highly populated countries in Asia, cohort evidence for NO2-mortality association was extensively sparse. Objectives: This study aimed to quantify longitudinal association of ambient NO2 exposure with all-cause mortality in Chinese adults. Methods: A national cohort of 30,843 adults were drawn from 25 provincial regions across mainland China, and followed up from 2010 through 2018. Participants’ exposures to ambient air pollutants were assigned according to their residential counties at baseline, through deriving monthly estimates from high-quality gridded datasets developed by machine learning methods. Cox proportional hazards models with time-varying exposures were utilized to assess the association of all-cause mortality with long-term exposure to ambient NO2. NO2-attributable deaths in China were estimated by province and county for years 2010 and 2018, with reference to the counterfactual exposure of 6.9 μg/m3 (the lowest county-level average in this cohort). Results: We observed a total of 1662 deaths during 224020 person-years of follow-up (median 8.1 year). An approximately linear NO2-mortality relation (p = 0.273 for nonlinearity) was identified across a broad exposure range of 6.9–57.4 μg/m3. Per 10-µg/m3 increase in annual NO2 exposure was associated with an hazard ratio of 1.127 (95% confidence interval: 1.042–1.219, p = 0.003) for all-cause mortality. Risk estimates remained robust after additionally adjusting for the confounding effects of co-pollutants (i.e., PM2.5 or/and O3). In 2018, 1.65 million deaths could be attributed to ambient NO2 exposure (national average 17.3 µg/m3) in China, representing a decrease of 4.3% compared with the estimate of 1.72 million in 2010 (20.5 µg/m3). Conclusion: This cohort study provided national evidence for elevated risk of all-cause mortality associated with long-term exposure to ambient NO2 in Chinese adults.

Background: A number of studies suggested a nexus between long-term exposure to nitrogen dioxide (NO2) and the incidence of cardiovascular disease (CVD), while population-based cohort evidence in low- and middle-income countries was extensively sparse. Methods: We carried out an 8-year longitudinal study (2010–2018) in a nationwide dynamic cohort of 36,948 Chinese adult participants, who were free of CVD at baseline. Annual average estimates of NO2 exposure were predicted using a well-validated spatiotemporal model and assigned to study participants based on their residential counties. Considering death as a competing risk event, Fine-Gray competing risk models with time-varying exposures at an annual scale were used to quantify incident risks of overall CVD, hypertension, and stroke associated with a 10-μg/m3 rise in NO2 exposure. Using the meta-analysis approach, we performed a pooled analysis of hazard ratio (HR) drawn from this and prior multinational cohort studies for the assessment of attributable burden. NO2-attributable overall CVD incidents in China were evaluated by city and province for years 2010 and 2018, referring to a counterfactual exposure level of 10 μg/m3 (2021 World Health Organization [WHO] air quality guidelines). A decomposition method was used to decompose net change in NO2-attributable CVD incidents during 2010 and 2018 into 3 primary contributions of driving factors (i.e., changes in NO2 exposure, population size, and incidence rate). Results: A total of 4428 overall CVD events (hypertension 2448, stroke 1044) occurred during a median follow-up period of 6.1 years. Annual mean NO2 concentration from 2010 to 2018 was 20.0 μg/m3 (range: 6.9–57.4 μg/m3). An increase of 10-µg/m3 in NO2 was associated with an HR of 1.558 (95% confidence interval [CI]: 1.477, 1.642) for overall CVD, 1.521 (95% CI: 1.419, 1.631) for hypertension, and 1.664 (95% CI: 1.485, 1.865) for stroke. Longitudinal associations of NO2 exposure with incident CVD were nearly linear over the exposure range, suggesting no discernible thresholds. Subgroup analyses indicated significantly higher NO2-associated risks of incident CVD among urban residents and overweight/obese individuals. According to pooled HR of NO2-CVD association (1.108, 95% CI: [1.007, 1.219]) from 10 multinational cohort studies, we estimated totally 1.44 million incident CVD cases attributable to NO2 exposure in 2018, representing a substantial decrease of 0.41 million compared to the estimate in 2010 (1.85 million) in mainland of China. Nationally, from 2010 to 2018, the attributable incident cases greatly dropped by 22.4%, which was dominantly driven by declined NO2 concentration (−47.1%) that had offset far from the rise of CVD incidence rate (+19.6%) and population growth (+5.1%). Conclusions: This study provided nationwide cohort evidence for elevated risks of CVD incidence associated with long-term ambient NO2 exposure among Chinese adults, particularly in urban areas and among overweight/obese individuals. Our findings highlighted that reducing NO2 exposure below 2021 WHO guideline could help prevent a substantial portion of incident CVD cases in China.

Emerging epidemiological studies suggest that long-term ozone (O3) exposure may increase the risk of mortality, while pre-existing evidence is mixed and has been generated predominantly in North America and Europe. In this study, we investigated the impact of long-term O3 exposure on all-cause mortality in a national cohort in China. A dynamic cohort of 20882 participants aged ≥40 years was recruited between 2011 and 2018 from four waves of the China Health and Retirement Longitudinal Study. A Cox proportional hazard regression model with time-varying exposures on an annual scale was used to estimate the mortality risk associated with warm-season (April–September) O3 exposure. The annual average level of participant exposure to warm-season O3 concentrations was 100 μg m−3 (range: 61–142 μg m−3). An increase of 10 μg m−3 in O3 was associated with a hazard ratio (HR) of 1.18 (95% confidence interval [CI]: 1.13–1.23) for all-cause mortality. Compared with the first exposure quartile of O3, HRs of mortality associated with the second, third, and highest exposure quartiles were 1.09 (95% CI: 0.95–1.25), 1.02 (95% CI: 0.88–1.19), and 1.56 (95% CI: 1.34–1.82), respectively. A J-shaped concentration–response association was observed, revealing a non-significant increase in risk below a concentration of approximately 110 μg m−3. Low-temperature-exposure residents had a higher risk of mortality associated with long-term O3 exposure. This study expands current epidemiological evidence from China and reveals that high-concentration O3 exposure curtails the long-term survival of middle-aged and older adults.

Objectives: Circulating exosomal microRNAs (miRNAs) have been identified as promising biomarkers for diagnosis of cardiovascular diseases. Nevertheless, the diagnostic potential of miRNAs in circulating exosomes for stable coronary artery disease (SCAD) remains unclear. We aim here to analyze the exosomal differentially expressed miRNAs (DEmiRNAs) in plasma of SCAD patients and investigate their diagnostic potential as SCAD biomarkers.Methods: Plasma was collected from SCAD patients and healthy controls, and exosomes were isolated by ultracentrifugation. Exosomal DEmiRNAs were analyzed by small RNA sequencing and were further validated by quantitative real-time PCR (qRT-PCR) in a larger set of plasma samples. Relationships between plasma exosomal let-7c-5p, miR-335–3p, miR-652–3p, genders and Gensini Scores in patients with SCAD were analyzed using correlation analyses. Moreover, we conducted receiver operating characteristic (ROC) curves for these DEmiRNAs and analyzed their possible functions and signaling pathways.Results: Vesicles isolated from plasma displayed all characteristics of exosomes. In the small RNA sequencing study, a total of 12 DEmiRNAs were identified, among which seven were verified to be statistically significant by qRT-PCR. The areas under the ROC curves of exosomal let-7c-5p, miR-335–3p, and miR-652–3p were 0.8472, 0.8029, and 0.8009, respectively. Exosomal miR-335–3p levels were positively correlated with Gensini scores of patients with SCAD. Bioinformatics analysis revealed that these DEmiRNAs may be involved in the pathogenesis of SCAD.Conclusion: Our findings indicated that plasma exosomal let-7c-5p, miR-335–3p, and miR-652–3p can be used as promising biomarkers for diagnosis of SCAD. In addition, plasma exosomal miR-335–3p levels coordinated with severity of SCAD.

Rutin, a flavonoid found in fruits and vegetables, is a potential anticancer compound with strong anticancer activity. Therefore, electrochemical sensor was developed for the detection of rutin. In this study, CoWO4 nanosheets were synthesized via a hydrothermal method, and porous carbon (PC) was prepared via high-temperature pyrolysis. Successful preparation of the materials was confirmed, and characterization was performed by transmission electron microscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy. A mixture of PC and CoWO4 nanosheets was used as an electrode modifier to fabricate the electrochemical sensor for the electrochemical determination of rutin. The 3D CoWO4 nanosheets exhibited high electrocatalytic activity and good stability. PC has a high surface-to-volume ratio and superior conductivity. Moreover, the hydrophobicity of PC allows large amounts of rutin to be adsorbed, thereby increasing the concentration of rutin at the electrode surface. Owing to the synergistic effect of the 3D CoWO4 nanosheets and PC, the developed electrochemical sensor was employed to quantitively determine rutin with high stability and sensitivity. The sensor showed a good linear range (5–5000 ng/mL) with a detection limit of 0.45 ng/mL. The developed sensor was successfully applied to the determination of rutin in crushed tablets and human serum samples.

Abstract Background This study compared the bacterial spectrum and antibiotic susceptibility of uropathogens in older and younger patients with urinary stones to provide appropriate antibiotic management. Methods We retrospectively reviewed urinary tract infection patients with urolithiasis, presented to Xiangya Hospital from March 2014 to April 2021. Patients were divided into older and younger groups according to 60 years of age. The bacterial spectrum and drug sensitivity of uropathogens were compared. Results A total of 542 strains of uropathogens (177 in older and 365 in younger groups) were isolated from 507 patients. E. coli (41.8% vs 43.6%) remains the most common pathogen, followed by E. faecalis (6.2% vs 9.6%) in older and younger groups, respectively. Particularly, K. pneumoniae was significantly more frequent in older (9.6%) than in younger group (4.7%, P

The Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) is an NP-hard problem, which has attracted a lot of attention in the past decades due to its many practical applications in logistics. In order to better describe the actual logistics distribution scenario, this paper studies the DVRPTW based on real road networks and proposes the hybrid BSO-ACO algorithm, which is a combination of Brain Storm Optimization (BSO), Ant Colony Optimization (ACO) and Neighborhood Search (2-opt, relocate, exchange). The algorithm 1) uses ACO to generate new individuals from the same cluster formed by BSO, and increases exploitation by ACO’s pheromone accumulation, 2) harnesses the 2-opt, relocate, and exchange to increase exploration to avoid the algorithm from falling into local optima. We construct a test set by extracting the real road networks in Panyu District, Guangzhou, China and compare the hybrid BSO-ACO algorithm with other algorithms on this test set. The computation experiments show the effectiveness and efficiency of the hybrid BSO-ACO algorithm.

Background: Currently, there is no consensus on patient selection for ambulatory laparoscopic cholecystectomy (LC). This study is a systematic review of previously published patient selection for ambulatory LC. Methods: A comprehensive search was done in PubMed, Web of Science, Embase and Google Scholar Database up to March 2020 to summarise previously reported medical or surgical selection criteria used for inclusion and exclusion of patients, as well as successful same-day discharge rates and readmission rate after discharge. Results: Fifty-nine studies with a total of 13,219 patients were included in this systematic review. In total, the median same-day discharge rate was 90% (range: 63%–99.4%), and median readmission rate was 2.22% (range: 0%–16.9%). The most considered medical criteria were American Society of Anesthesiologists classification I and II, age

Abstract Background Urothelial bladder cancer (BC) is one of the most prevalent malignancies with high mortality and high recurrence rate. Angiogenesis, tumor growth and metastasis of multiple cancers are partly modulated by CC chemokines. However, we know little about the function of distinct CC chemokines in BC. Methods ONCOMINE, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan–Meier plotter, cBioPortal, GeneMANIA, and TIMER were used for analyzing differential expression, prognostic value, protein–protein interaction, genetic alteration and immune cell infiltration of CC chemokines in BC patients based on bioinformatics. Results The results showed that transcriptional levels of CCL2/3/4/5/14/19/21/23 in BC patients were significantly reduced. A significant relation was observed between the expression of CCL2/11/14/18/19/21/23/24/26 and the pathological stage of BC patients. BC patients with high expression levels of CCL1, CCL2, CCL3, CCL4, CCL5, CCL8, CCL13, CCL15, CCL17, CCL18, CCL19, CCL22, CCL25, CCL27 were associated with a significantly better prognosis. Moreover, we found that differentially expressed CC chemokines are primarily correlated with cytokine activity, chemokines receptor binding, chemotaxis, immune cell migration. Further, there were significant correlations among the expression of CC chemokines and the infiltration of several types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells). Conclusions This study is an analysis to the potential role of CC chemokines in the therapeutic targets and prognostic biomarkers of BC, which gives a novel insight into the relationship between CC chemokines and BC.

AbstractThe North China Craton (NCC) has thick lithosphere in the Paleozoic (>200 km) but appears to be decratonized in the Mesozoic. However, the actual processes operated in the lower crust-deep mantle are still unclear. The Mesozoic granitic rocks can provide important clues to the NCC decratonization mechanism. Here, we conducted trace element modeling to check whether partial melting of the Archean lower crust can generate these Mesozoic magmatic suites. Meanwhile, zircon Hf isotope analysis was conducted to reveal crust-mantle interaction processes and further give constraints on the decratonization of the NCC. Zircon Hf isotope data of the Linglong, Guojialing, and Aishan suites, the mafic microgranular enclaves (MMEs) in the Guojialing suite, and mafic dykes display minor differences: the Linglong (160–150 Ma), Guojialing (~130 Ma), and Aishan (118–116 Ma) suites have zircon εHft=–25.4 to –14.5, –15.3 to –10.4, and –23.1 to –11.9, respectively. The Cretaceous mafic dyke (126 Ma) has a highly negative εHft value (–22.8 to –17.7). Meanwhile, the MMEs (in the Guojialing granodiorite, DCW-2A, 129 Ma) have zircon εHft=–13.0 to –8.9. Temperature-pressure conditions calculated using amphibole compositions for both the Guojialing granodiorite and its MMEs are basically identical, implying possible magma mixing. Our modeling results show that certain trace elements (e.g., Tb, Yb, and Y) have to be retained in the source to match the composition of the Linglong suite, which requires substantial garnet residues (high-pressure melting) in the Jurassic. The Early Cretaceous garnet-dominated lower crust is Yb-/Y-enriched but depleted in elements like Sr and La. Therefore, it could not form geochemical features like high Sr/Y and La/Yb ratios akin to the Guojialing suite. Integrating the modeling results and zircon Hf isotope data, we propose that the crust in the eastern NCC had thickened and partially melted by dehydration to produce an eclogitic residue containing a large amount of garnet (>50% by weight) during the Jurassic (Linglong granite), whereas upwelling of hot and hydrous mafic magma from the asthenospheric mantle induced fluxed melting of both the lower crust and lithospheric mantle in the Early Cretaceous, during which the lithospheric mantle and part of the lower crust in the Jiaodong were removed by the convective mantle. About 10 Mys later while the Aishan suite formed, the crust was not thick anymore, and melting occurred under moderate pressure which does not necessarily require abundant garnet as the residue phase.

Lower crust-derived granitic rocks provide constraints on the crustal reworking process and consequently give hints on the destruction mechanism of the cratons. The North China Craton (NCC) underwent extensive crustal melting in the Mesozoic. This study investigated granitic intrusions in the Dazeshan region of the Jiaodong Peninsula. Whole-rock major and trace element analyses and zircon U-Pb ages coupled with Hf isotopes were used to reveal the crustal reworking processes. Zircons separated from the quartz porphyry, Linglong granite, rhyolite porphyry, and biotite granite showed weighted mean 206Pb-238U ages of 119.2 ± 1.0 Ma, 140.2 ± 1.0 Ma, 120.6 ± 0.5 Ma, and 119.9 ± 0.7 Ma, respectively. The quartz porphyry, rhyolite porphyry, and biotite granite had high silica contents (SiO2 = 74–77 wt.%) but low MgO, Co, and Ni concentrations. The calculated εHf(t) values for the rhyolite porphyry and the biotite granite ranged from −18.3 to −20.0 and −17.8 to −20.2, respectively. These geochemical features imply ancient crust sources. The quartz porphyry showed distinct primitive mantle-normalized rare earth element (REE) patterns and was characterized by lower ΣREE content and lack of pronounced negative Eu anomalies. Whole-rock and zircon Dy/Yb ratios showed no correlation with whole-rock Rb/Sr ratios and zircon Hf contents, reflecting limited effects of crystal fractionation. The Ba/La ratios were also high (>150), but the Sr/Y and La/Yb ratios were low (Sr/Y < 50; La/Yb < 15). These features likely indicate that the quartz porphyry was generated by water-fluxed melting without differentiation. The rhyolite porphyry and biotite granite shared many geochemical similarities, denoting a unified source. The high La/Yb (>30) but low Sr/Y (

The Himalayan leucogranites provide a good opportunity to investigate the crustal evolution of the southern Qinghai-Tibet Plateau. In this study, we present zircon U-Pb and monazite U-Th-Pb ages, zircon Hf isotopes and whole-rock Sr-Nd-Pb isotopes and major and trace elements for the Liemai two-mica granite, eastern Himalaya. Together with previously published data we revalued the petrogenesis of the Early Eocene magmatic rocks in this region and their geological implications. The zircon and monazite U-(Th)-Pb dating results showed that the Liemai two-mica granite was generated at ∼ 43 Ma, similar to adjacent Yardoi, Dala and Quedang adakitic two-mica granites, Ridang subvolcanic rocks and Yardoi leucogranite. The Liemai two-mica granite, similar to these coeval adakitic two-mica granites, is enriched in SiO2, Al2O3, Th, U, Pb, La, and Sr, and depleted in MgO, total iron, Yb and Y with high Sr/Y and (La/Yb)N ratios (showing adakitic affinities), and exhibits enriched Sr-Nd-Pb-Hf isotopic compositions, suggesting an origin of a thickened lower crust consisting mainly of garnet amphibolite. Although the Ridang subvolcanic rocks and Yardoi leucogranite show similar Sr-Nd-Hf isotopes to these adjacent coeval two-mica granites, perceptible differences in whole-rock major and trace elements can be observed. Broadly, these granites can be divided into high-Mg# granites (HMGs, the two-mica granites) and low-Mg# granites (LMGs, the Ridang subvolcanic rocks and Yardoi leucogranite). The former has relatively higher contents of total iron, MgO, Mg#, TiO2, P2O5, LREE, Y, Th, Sr, incompatible elements (Cr and Ni) and Eu/Eu* values, and lower contents of SiO2 and Rb/Sr and Rb/Ba ratios, thus is less evolved than the latter. According to recent studies of differentiation processes in silicic magma reservoirs, we proposed that the HMGs represent a congealed crystal mush that was composed of ‘cumulate crystals’ and a trapped interstitial liquid, while the LMGs represent the almost pure liquid that was extracted from the crystal mush. Modeling using the trace elements Sr and Ba shows that the extraction probably occurred when the crystallinity of the mush was ∼ 60%–63%, at least for the most evolved LMGs sample. The HMGs correspond to a residual crystal mush that had a terminal porosity of ∼ 21%–25% filled with a trapped interstitial liquid. Underplating of mafic magmas following slab breakoff of the Neo-Tethys oceanic lithosphere caused partial melting of the amphibolitic lower crust, which had been thickened to ~50 km prior to ~43 Ma.

The construction of standardized tea gardens is the main trend in the development of modern agriculture worldwide. As one of the most important economic crops, tea has increasingly stringent requirements placed on its planting capacity and quality. The application of machine vision technology has led to the gradual development of tea production moving towards intelligence and informatization. In recent years, research on tea production based on machine vision technology has received widespread attention, as it can greatly improve production efficiency and reduce labor costs. This article reviews the current application status of machine vision technology in tea pest monitoring, intelligent harvesting, quality evaluation, and classification, and analyzes and discusses specific challenges around machine vision technology in tea production; for example, this technology lacks a standard database and weather interference, training errors in the model, and differences in the hardware computing speed can become a challenge. Based on the current research and application of machine vision technology in various fields, this article looks ahead to the development prospects and future trends of machine vision technology in tea production applications, such as future research to further integrate multiple types of sensors, improvements in the quality and usability of datasets, optimized model algorithms for existing problems, dissemination of research results, and intelligent management of tea production through machine vision technology.

The construction of standardized citrus orchards is the main trend in the future development of modern agriculture worldwide. As the most widely used and mature technology in the agricultural field, machine vision has greatly promoted the industrial development model of the citrus industry. This paper summarizes the application of machine vision technology including citrus pest and disease detection, harvesting identification and localization, and fruit grading. We compare the advantages and disadvantages of relevant research, and analyze the existing problems and prospects for future research. Due to the complex and changeable in-field environment, robots may experience unpredictable interference in the recognition process, which leads to errors in target fruit localization. The lack of datasets also affects the accuracy and stability of the algorithm. While expanding the dataset, it is necessary to conduct further research on the algorithm. In addition, the existing research focuses on indoor monitoring methods, which are not practical for the changeable outdoors environment. Therefore, realizing the diversity of sample datasets, designing agricultural robots suitable for complex environments, developing high-quality image processing hardware and intelligent parallel algorithms, and increasing dynamic monitoring methods are the future research directions. Although machine vision has certain limitations, it is still a technology with strong potential for development.

Diabetic foot ulcers (DFUs) are pathological states of tissue destruction of the foot or lower extremity in diabetic patients and are one of the serious chronic complications of diabetes mellitus. Matrix metalloproteinases (MMPs) serve crucial roles in both pathogenesis and wound healing. The primary functions of MMPs are degradation, which involves removing the disrupted extracellular matrix (ECM) during the inflammatory phase, facilitating angiogenesis and cell migration during the proliferation phase, and contracting and rebuilding the tissue during the remodeling phase. Overexpression of MMPs is a feature of DFUs. The upregulated MMPs in DFUs can cause excessive tissue degradation and impaired wound healing. Regulation of MMP levels in wounds could promote wound healing in DFUs. In this review, we talk about the roles of MMPs in DFUs and list potential methods to prevent MMPs from behaving in a manner detrimental to wound healing in DFUs.

Background: Previous studies have indicated the associations between fine particulate matter (PM2.5) exposure and diabetes or glucose levels. However, evidence linking PM2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO3-], sulfate [SO42-], and ammonium [NH4+]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations. Methods: A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China’s mainland. Health examination and questionnaire survey for each respondent were performed during 2011−2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM2.5 mass and its five constituents (BC, OM, NO3-, SO42-, and NH4+) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age. Results: We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM2.5, BC, OM, NO3-, SO42-, and NH4+ were 47.9 (27.4) µg/m3, 2.9 (2.2) µg/m3, 9.2 (6.6) µg/m3, 10.2 (9.4) µg/m3, 11.0 (5.2) µg/m3, and 7.1 (4.4) µg/m3, respectively. Per IQR rise in exposure to PM2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048−0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012−0.181]), OM (0.160 mmol/L [0.065−0.256]), NO3- (0.145 mmol/L [0.039−0.251]), SO42- (0.111 mmol/L [0.026−0.196]), and NH4+ (0.135 mmol/L [0.041−0.230]). Under different diabetes definitions, PM2.5 mass and selected constituents with the exception of SO42- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097−1.270) for PM2.5, 1.154 (1.079−1.235) for BC, 1.170 (1.079−1.270) for OM, 1.200 (1.098−1.312) for NO3-, and 1.123 (1.037−1.215) for NH4+. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064−1.411]) than females (1.024 [0.923−1.136]) when exposed to PM2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM2.5 constituents exposure. Conclusions: Exposures to PM2.5 and its constituents (i.e., BC, OM, NO3-, and NH4+) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

Insecticides harm the beneficial organisms, such as predatory spiders, through direct killing or regulation of the development and reproduction. In this study, the bioassay showed that the treatment of juvenile hormone (JH) analogue fenoxycarb delayed the moulting of Pardosa pseudoannulata, a dominant predatory spider in paddy fields. In order to figure out the regulatory mechanism of fenoxycarb on the spider development, we systematically analyzed JH biosynthesis in P. pseudoannulata. All genes involved in JH biosynthesis pathway were retrieved from the genome of P. pseudoannulata, except for CYP15A1. The absence of CYP15A1 was in agreement with the identification of methyl farnesoate (MF) rather than JH III in the spider. The delayed moulting and decreased expression of JH biosynthesis-related genes in the MF-applied spiderlings supported that MF was an active JH. Fenoxycarb treatment significantly upregulated the transcriptional level of JH biosynthesis-related genes and consequently delayed the spiderling moulting. In the spider development, ecdysteroid played the opposite role, in contrast to MF, to accelerate the development, as our previous study. Here we found that the treatment of ecdysteroid analogue tebufenozide accelerated P. pseudoannulata spiderling moulting, which resulted from the expressional suppression of ecdysteroid biosynthesis-related genes. In total, the JH and ecdysteroid analogues affected the development of P. pseudoannulata by the expressional regulation of biosynthesis-related genes, which would be helpful for the evaluation of hormone analogue insecticides in environmental safety, and useful for the protection and application of P. pseudoannulate and related spider species.

Objective While greater body mass index (BMI) is associated with increased risk of developing atrial fibrillation (AF), the impact of BMI on outcomes in newly diagnosed AF is unclear. We examine the influence of BMI on outcomes and whether this is modified by sex and evaluate the effect of non-vitamin K oral anticoagulants (NOACs) in patients with high BMI.Methods GARFIELD-AF is a prospective registry of 52 057 newly diagnosed AF patients. The study population comprised 40 482 participants: 703 underweight (BMI

Mineral resources are essential to prosperity and security of modern societies. How mineral resources can guarantee sustainable development of economy in countries, especially those developing countries, has long been a focus of attention of international communities. This paper provides a comprehensive summary for major advance of the research on mineral resources in past decades, and proposes some key issues regarding ore-forming mechanism, exploration and utilization of major and critical mineral resources. On the basis of these aspects, we also identify four priority science issues to be addressed in the future, including (1) mechanism of both metal circulation and extremely high concentration, (2) theories and technologies of prospecting deep-earth resources, (3) investigation of mineral resources in seafloor and polar regions, and (4) efficient, clean and recycling utilization of mineral resources. It can be expected that new advances in these four issues would tremendously promote the innovation of mineral resource science, and provide scientific and technologic support to meet the demand of mineral resources for human activities and the harmonious development of both mineral-resource exploration and ecological restoration.

The segmentation and positioning of tea buds are the basis for intelligent picking robots to pick tea buds accurately. Tea images were collected in a complex environment, and median filtering was carried out to obtain tea bud images with smooth edges. Four semantic segmentation algorithms, U-Net, high-resolution network (HRNet_W18), fast semantic segmentation network (Fast-SCNN), and Deeplabv3+, were selected for processing images. The centroid of the tea buds and the image center of the minimum external rectangle were calculated. The farthest point from the centroid was extracted from the tea stalk orientation, which was the final picking point for tea buds. The experimental results showed that the mean intersection over union (mIoU) of HRNet_W18 was 0.81, and for a kernel with a median filter size of 3 × 3, the proportion of abnormal tea buds was only 11.6%. The average prediction accuracy of picking points with different tea stalk orientations was 57%. This study proposed a fresh tea bud segmentation and picking point location method based on a high-resolution network model. In addition, the cloud platform can be used for data sharing and real-time calculation of tea bud coordinates, reducing the computational burden of picking robots.

Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.

Convolutional Neural Networks (CNNs) have truly gained attention in object recognition and object classification in particular. When being implemented on Graphics Processing Units (GPUs), deeper networks are more accurate than shallow ones. Residual Networks (ResNets) are one of the deepest CNN architectures used in various fields including safety-critical ones. GPUs have proven to be the major accelerator for CNN models. However, modern GPUs are prone to radiation-induced soft errors, which is a serious issue in safety-compliant systems. In this work, we analyze and propose an approach to address the reliability of ResNet on GPUs. We firstly analyze three popular ResNet models, explicitly, ResNet-50, ResNet-101, and ResNet-152 through NVIDIA's fault injector, SASSIFI. We perform an in-depth analysis of the model from the perspective of layer and kernel vulnerability. Then, we experimentally show the vulnerability of ResNet models and identify the most vulnerable portions. Finally, we validate our solution, which is a selective-hardening technique, through hardening the worth-hardening kernels to avoid unnecessary overheads. Our strategy is demonstrated to mask up to 93.38% of the injected errors with performance overhead less than 5.35%. Furthermore, the percentage of the errors causing misclassifications can be reduced from 4.2% to 0.104%, thereby significantly improving the model's reliability.

Abstract Background Perivesical lymph nodes (PVLNs) are occasionally isolated during grossing of cystectomy specimens. However, the prognostic implications of the involvement of PVLNs in bladder cancer patients, especially those with comparisons to pN0 disease, remain poorly understood. Methods A retrospective review identified 115 radical cystectomy cases where PVLNs had been histologically assessed. These cases were then divided into 4 groups – Group 1 (n = 76): PVLN-negative/other pelvic lymph node (non-PVLN)-negative; Group 2 (n = 5): PVLN-positive/non-PVLN-negative; Group 3 (n = 17): PVLN-negative/non-PVLN-positive; and Group 4 (n = 17): PVLN-positive/non-PVLN-positive. Results pT stage at cystectomy was significantly higher in Group 3 (P = 0.013), Group 4 (P

IntroductionThe numbers of retrieved lymph nodes (RLNs) and positive lymph nodes (PLNs) had a significant impact on the survival of patients with ampulla of vater cancer (AVC), but the optimal numbers of the both were controversial.ObjectiveThe cohort study aimed to explore the prognostic value and the optimal point of RLNs and PLNs for AVC.MethodsA total of 2347 AVC patients with M0 disease who underwent surgical resection and lymph node dissection from January 2004 to December 2013 were acquired from a prospective database.ResultsThe study found that the optimal cut-off values of RLNs were 18 in the N0 cohort and 16 in N1 or entire cohort due to the highest 5-year overall survival (OS) rate and disease-specific survival (DSS) rate and the separation of survival curves (all P < 0.05). In patients with RLNs ≥ 16, patients with PLN = 0 demonstrated significantly better 5-year OS and DSS rates (70.9% and 77.1%) compared to those with PLNs = 1-2 (41.6% and 44.7%; all P < 0.001), and patients with PLNs = 1-2 demonstrated significantly better 5-year OS and DSS rates (41.6% and 44.7%) compared to those with PLNs ≥ 3 (24.3% and 28.0%; all P < 0.001).ConclusionsThis article recommended that at least 16 lymph nodes will improve the prognosis of AVC patients undergoing surgery. The best cut-off values of PLNs recommended for this study were 0 and 2, which may accurately stratify patients.

Objective This study aimed to detect circulating microRNA (miR)-17 and miR-20a levels in patients with pulmonary arterial hypertension (PAH), and to investigate whether circulating miR-17 levels are associated with PAH. Methods Thirty-five PAH patients and 20 healthy controls were enrolled in the study. Circulating miR-17 and miR-20a levels were measured using real-time PCR analysis. Results miR-17 levels were significantly increased in PAH patients compared with healthy controls. They were also higher in PAH patients at World Health Organization functional class (WHO FC) III–IV than WHO FC I–II PAH patients. There was no significant difference in miR-20a levels between PAH patients and controls. miR-17 had a high area under the corresponding receiver operating characteristic curve. Further, we found that circulating miR-17 levels correlated with the 6-minute walk distance, mean pulmonary artery pressure, and mean right atrial pressure in PAH patients. Conclusion Circulating miR-17 levels may be associated with human PAH. Therefore, miR-17 could be used as a diagnostic index and prognostic factor for PAH patients.

NFV is evolving from the initial stage of software and hardware decoupling to the goal of full cloudification and cloud native,which will make the telecommunication networks more scalable,flexible and efficient.The introduction of the NFV PaaS platform is an important measure to realize the evolution and development of NFV.The basic concepts and application scenarios of NFV PaaS were introduced,several deployment options of NFV PaaS were analyzed,and an architecture design of NFV PaaS platform was proposed.The reference for telecom operators to build NFV PaaS platform will be provided.

Abstract Background Exogenous stressors resulting from air pollution can lead to depression and chronic disease. Chinese levels of air pollution are among the highest in the world, and although associated adverse health effects are gradually emerging, research determining individual vulnerability is limited. This study estimated the association between air pollution and depressive symptoms and identified whether chronic disease influences an individual’s susceptibility to depressive symptoms relating to air pollution. Methods Individual sample data from the China Health and Retirement Longitudinal Study and a group of city-level variables in 2011 and 2013 were used with the random effects model and Tobit model. Adjustments were made for demographic, socioeconomic status, health behavior, and city-level climate variables with respect to living areas. Analysis was also stratified using chronic disease characteristics. Results The total Center for Epidemiological Studies Depression scale evaluating depressive symptoms ranged between 7 and 28 [average 11.623 (SD = 4.664)]. An 1% increase in sulfur dioxide and total suspended particulate emission intensities was associated with depressive symptoms scores that were 1.266 (SE = 0.107, P

Photothermal interferometry (PTI) incorporated with wavelength modulation spectroscopy is a typical ultrasensitive spectroscopic technique for trace gas detection. In this paper, to our best knowledge, we demonstrate that the first harmonic signal is the best choice for a PTI spectroscopy gas sensing system for the first time. Both the theoretical and experimental results confirm that the first harmonics signal has the largest peak-to-peak amplitude in all harmonic signals. The noise measurement indicates that the all harmonic signals nearly have the same noise level. The detection limit in terms of noise equivalent concentration is improved by 30%, from 114 to 78 ppb (9 × 10-8 cm-1 in absorption coefficient) by use of the first harmonic signal instead of the second harmonic signal.

In the actual fault diagnosis process of an analog circuit, there is often a problem due to the lack of fault samples, leading to the low-accuracy of diagnostic models. Therefore, using positive samples that are easy to obtain to establish diagnostic models became a research hotspot in the field of analog circuit fault diagnosis. This paper proposes a method based on Support Vector Data Description (SVDD) and Dempster–Shafer evidence theory (D–S evidence theory) for fault diagnosis of modular analog circuit. Firstly, the principle of circuit module partition is proposed to divide the analog circuit under test, and the output port of each module is selected as test point. Secondly, the paper extracts the feature of the time-domain and frequency-domain output signals of the circuit module through Principal Component Analysis (PCA). Thirdly, four state detection models based on SVDD are established to judge the working state of each circuit module, including TSG, TSP, FSG, and FSP state detection model. Finally, the D–S theory is introduced to integrate the test results of each model for locating fault circuit module. To verify the effectiveness of the proposed method, the dual bandpass filter circuit is selected for simulation and hardware experiment. The results show that the proposed method can locate the analog fault effectively and has a higher diagnosis accuracy.

NFV implements the hardware and software decoupling of telecommunications network equipment,gets rid of the dependence on dedicated hardware equipment.NFV brings benefits such as resource sharing,automatic deployment,flexibility and other features,but it also brings some problems such as more fault points,difficult fault analysis and so on.It results in NFV network operation and maintenance more difficult.The NFV fault process and fault association were analyzed,and guidance for fault location processing in NFV was provided.At the same time,the VNF fault self-healing implementation scheme was given to realize the network element and service fault self-healing,and improve capability of automatic operation and maintenance.

IntroductionThe American Joint Committee on Cancer (AJCC) recommended retrieval of at least 12 lymph nodes and firstly classified N category by the number of positive lymph nodes (PLNs) for Distal Cholangiocarcinoma (DCC).ObjectiveThe end of this cohort study was to explore the optimal cut-off values of the number of examined lymph nodes (ELNs) and PLNs to better stratify patients by utilizing a population-based database.MethodsA number of 758 patients with DCC from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in the study and comparing by the survival analysis.ResultsSurvival analysis found that patients with ELNs < 5 had a lower 3-year disease-specific survival rate than ELNs ≥ 5 in N0M0 cohort (35.3% vs. 53.0%, P = 0.001) and in M0 cohort (42.7% vs. 32.8%, P = 0.006); survival curves between patients with ELNs < 12 and ELNs ≥ 12 were overlapped in N0M0 cohort (P = 0.256) and in M0 cohort (P = 0.233). Among patients with ELNs ≥ 5, using the optimal cut-off value of the number of PLNs (0, 2) could accurately stratify patients, but the recommendation of the number of PLNs (0, 3) by the AJCC could not.ConclusionsThis study recommended examining at least 5 lymph nodes and defining PLNs = 1-2 as the N1 category and PLNs ≥ 3 as the N2 category, which may better stratify distal cholangiocarcinoma patients and improve the accuracy of the eighth edition AJCC staging.

Increasing incidents of regional pollution in China have threatened the well-being and physical and mental health of individuals. Therefore, the potential impact of air pollution on mental health must be assessed. This study examined the relationship between air pollution and mental health, as well as the regulatory effects of health behaviors. Air pollution was measured using the concentration of particulates with a diameter less than 2.5 μ m (PM _2.5 ), and mental health was measured using the Center for Epidemiologic Studies Depression (CES-D) scale. Using the China Family Panel Studies 2010 and 2014 data sets, the panel data regression model was employed to discuss the associations between air pollution and mental health and the interaction between air pollution and health behaviors on mental health. In total, 52 568 observations were collected. When the concentration of PM _2.5 increased by 1 μ g m ^−3 , the CES-D scale scores decreased by 0.012 (95% CI: −0.021 to −0.003). Smoking was the only health behavior that made this effect more pronounced, its regulatory effect on the CES-D scale scores was −0.011 (95% CI: −0.021 to −0.002). The mental health of low-income individuals was also more vulnerable to the adverse effects of air pollution. This study highlights the potential impact of air pollution on mental health and the importance of health behaviors; it also provides suggestions for maintaining mental health and formulating policies based on changing air quality in the future.

Freeform surface is one of the research focuses in the measurement field. A composite module is composed of a plane and rotating paraboloid. The composite module array can identify 21 geometric errors of the machine tool in a wide range, which is composed of several composite modules. Eliminating the error of the array itself is of great significance for improving measurement accuracy. For this reason, this paper proposed a noncontact method for calibrating the angle and position of the composite module array. This paper used a self-developed angle sensor to access corresponding information and established the mathematical model according to the freeform surface’s geometric characteristics to achieve calibration. In addition, the influence of array placement error on calibration was analyzed. The experimental results showed that the angle repeatability was within 0.4″ around the X-axis and within 0.3″ around the Y-axis, and the position repeatability was within 0.4 µm in the X direction and within 0.7 µm in the Y direction. The measurement comparison experiments with high-precision laser interferometer and uncalibrated array verified the correctness of the experimental results. This method provides an important reference for practical application and freeform surface array calibration, and creates conditions for the implementation of machine tool error detection.

Background/Aims: Atherosclerosis is a chronic inflammatory disease. Intracellular adhesion molecule-1 (ICAM-1), vascular cellular adhesion molecule-1 (VCAM-1), and monocyte chemoattractant protein-1 (MCP-1) play important roles in inflammatory processes. P38 mitogen-activated protein kinase (MAPK) and nuclear factor (NF)-κB signaling regulate ICAM-1, VCAM-1, and MCP-1 expression. Angiotensin (Ang) II upregulates ICAM-1, VCAM-1, and MCP-1 expression through the P38 MAPK and NF-κB pathways. Ang-(1-7) may oppose the actions of Ang II. We investigated whether Ang-(1-7) prevents Ang II-induced ICAM-1, VCAM-1, and MCP-1 expression in human umbilical vein endothelial cells (HUVECs). Methods: ICAM-1, VCAM-1, and MCP-1 expression was estimated by real-time polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA); P38, NF-κB, and p-IκB-a expression was estimated by western blotting. Results: Ang-(1-7) inhibited Ang II-induced ICAM-1, VCAM-1, and MCP-1 expression and secretion in HUVECs. Ang II sharply increased P38 MAPK phosphorylation, which was inhibited by pretreatment with Ang-(1-7). Moreover, Ang-(1-7) significantly inhibited Ang II-induced IκB-a phosphorylation and NF-κB P65 nuclear translocation. The MAS receptor antagonist A-779 abolished the suppressive effects of Ang-(1-7). Conclusion: Ang-(1-7) attenuates Ang II-induced ICAM-1, VCAM-1, and MCP-1 expression via the MAs receptor by suppressing the P38 and NF-κB pathways in HUVECs. Ang-(1-7) might delay the progression of inflammatory diseases, including atherosclerosis.

Benign mesothelial inclusions in pelvic lymph nodes may be mistaken for metastatic disease in the setting of pelvic malignancy. In this case-report a patient with Low-Risk prostate cancer (confirmed by biopsy and genomic testing) underwent radical prostatectomy with pelvic lymph node dissection. The initial pathological diagnosis was organ-confined Gleason 3 + 3 = 6 cancer with metastasis to a pelvic lymph node. Upon review of the pathological specimen and immunohistochemical staining the lymph node tissue concerning for metastatic disease was recharacterized as mesothelial in origin. This case illustrates the importance of second opinions and immunohistochemistry for unexpected or unusual pathological findings.

Based on requirements of intensive operation and problems in legacy network management systems,the layered network management system architecture which has five function groups was developed,and then,the evolution modes toward intelligent network management systems were studied.

In order to improve the accuracy of the linear motion of computer numerical control (CNC) machine tools, a novel method based on a new type of 1-D (1-dimensional) artifact is proposed to measure the geometric errors. Based on the properties of the displacement measurement of a revolutionary paraboloid and the angle measurement of plane mirrors, the 1-D artifact can be applied to identify position errors and angle errors. Meanwhile, the concrete 6 degrees-of-freedom error identification method is described in this paper in sufficient detail. Through measuring the 1-D artifact horizontally and vertically using the machine tool, the geometric errors can be obtained by calculating the deviation between the characteristic parameter of the 1-D artifact measured by the machine tool and that measured by a more precise method, for example, laser interferometry. Experiments were carried out on a coordinate measuring machine, and the validity and accuracy of the method were discussed by comparing the result with the identification error measured by a laser interferometer.

Using an optical freeform surface to realize the precision measurement of displacement has become a research focus in the present day. However, the measurement range of this method is limited by the size of the freeform surface processed. In order to overcome this difficulty, this paper presents a two-dimensional displacement measurement system with a large range, which is composed of a slope sensor and a rotating paraboloid array. The slope sensor utilizes the optical structure of an autocollimator with minor optimization, and the rotating paraboloid array expands the measurement range of the system in a discrete manner. The experimental results showed that the optimized optical system enhanced the measurement accuracy to ±0.4 μm within the range of 1500 μm and the overall measurement error was approximately ±2 μm when measured within the range of 450 mm. The developed measurement system has potential applicability for detection of errors, such as the position error and straightness error of multi-axis systems.