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Abstract Since China proposed building a national park system in 2017, the establishment of a planning system for nature reserves, with national parks as the main body, is being actively promoted around the country. Among them, scientific ecological space management and control zoning (ESMCZ) is an important link in maintaining the ecological stability of national parks. How to zone national parks and how to improve the precision of zoning has become a new task for national parks. Therefore, this study takes the Giant Panda National Park as the study area, takes ecosystem services and land use/cover change as the research perspective, integrates the InVEST model, PLUS model and bayes belief network (BBN) model, and builds a set of ecological space management and control zoning (ESMCZ) spatial zoning framework based on raster scale, dividing the study area into strictly protected zone, ecological buffer zone, ecological control zone and controlled development zone. The results showed that: (1) The study area showed an increasing trend in water conservation, soil conservation and carbon storage from 2005 to 2020, and the habitat quality index was generally high. The spatial heterogeneity of ecosystem services in the study area was significant, and the effect of a single factor on ecosystem services was most pronounced. (2) Large variation in area for different land uses under natural development scenarios and ecological protection scenarios. In both scenarios, the area of cultivated land, the area of grassland and the area of unused land decrease relative to 2020, and the area of forested land, the area of water and the area of constructed land increase relative to 2020. (3) The Giant Panda National Park is divided into strictly protected zone, ecological buffer zone, ecological control zone and control development zone, of which the strictly protected zone have the largest area and the best ecosystem background condition, and the control development zone have the smallest area and the worst ecosystem background condition. (4) The ecological space management and control zoning (ESMCZ) framework provides a more refined method for the secondary zoning of nature reserves such as the Giant Panda National Park, which is valuable for the implementation of zoning and categorization management for ecological conservation in the Giant Panda National Park.

Abstract The COVID-19 pandemic has imposed significant challenges on global health, emphasizing the persistent threat of large-scale infectious diseases in the future. This study addresses the need to enhance pooled testing efficiency for large populations. The common approach in pooled testing involves consolidating multiple test samples into a single tube to efficiently detect positivity at a lower cost. However, what is the optimal number of samples to be grouped together in order to minimize costs? i.e. allocating ten individuals per group may not be the most cost-effective strategy. In response, this paper introduces the hierarchical quotient space, an extension of fuzzy equivalence relations, as a method to optimize group allocations. In this study, we propose a cost-sensitive multi-granularity intelligent decision model to further minimize testing costs. This model considers both testing and collection costs, aiming to achieve the lowest total cost through optimal grouping at a single layer. Building upon this foundation, two multi-granularity models are proposed, exploring hierarchical group optimization. The experimental simulations were conducted using MATLAB R2022a on a desktop with Intel i5-10500 CPU and 8G RAM, considering scenarios with a fixed number of individuals and fixed positive probability. The main findings from our simulations demonstrate that the proposed models significantly enhance the efficiency and reduce the overall costs associated with pooled testing. For example, testing costs were reduced by nearly half when the optimal grouping strategy was applied, compared to the traditional method of grouping ten individuals. Additionally, the multi-granularity approach further optimized the hierarchical groupings, leading to substantial cost savings and improved testing efficiency.

Abstract The coronavirus disease-2019 (COVID-19) pandemic has impaired the quality of life (QoL) for many due to its extensive impacts. However, few studies have addressed the specific impact of COVID-19 on the mental health of adolescents, particularly post-traumatic stress disorder (PTSD). This study considered the impact of COVID-19-related PTSD on the QoL of adolescents in China, the mediating effects of insomnia, and the moderating effects of resilience. Participants included 50,666 adolescents aged 12–18 years selected using a comprehensive sampling method. We performed data collection from January 8th to January 18th, 2023, using the Children’s Revised Impact of Event Scale, Pittsburgh Sleep Quality Index, Ten-item Connor-Davidson Resilience Scale, and Screening for and Promotion of Health-related QoL in Children and Adolescents Questionnaire for data collection. Male adolescents exhibited significantly lower levels of PTSD and insomnia compared to females and scored significantly higher in psychological resilience and overall QoL. Insomnia played a mediating role between PTSD and QoL. Psychological resilience moderated the impact of COVID-19-related stress on adolescents’ QoL through its influence on insomnia. PTSD resulting from the COVID-19 pandemic affects the QoL of adolescents through the presence of insomnia. Psychological resilience plays a moderating role in this process. Cultivating psychological resilience in adolescents can effectively enhance their ability to cope with the impacts of sudden public events.

Abstract Diabetes accelerates vascular senescence, which is the basis for atherosclerosis and stiffness. The activation of NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome and oxidative stress are closely associated with the deteriorative senescence in endothelial cells (ECs) and vascular smooth muscle cells (VSMCs). For decades, Sodium Tanshinone IIA Sulfonate (STS) has been utilized as a cardiovascular medicine with acknowledged anti-inflammatory and anti-oxidative properties. Nevertheless, the impact of STS on vascular senescence remains unexplored in diabetes. Diabetic mice, primary ECs and VSMCs were transfected with the NLRP3 overexpression/knockout plasmid, the tumor necrosis factor alpha-induced protein 3 (TNFAIP3/A20) overexpression/knockout plasmid, and treated with STS to detect senescence-associated markers. In diabetic mice, STS treatment maintained catalase (CAT) level and vascular relaxation, reduced hydrogen peroxide probe (ROSgreen) fluorescence, p21 immunofluorescence, Senescence β-Galactosidase Staining (SA-β-gal) staining area, and collagen deposition in aortas. Mechanistically, STS inhibited NLRP3 phosphorylation (serine 194), NLRP3 dimer formation, NLRP3 expression, and NLRP3-PYCARD (ASC) colocalization. It also suppressed the phosphorylation of IkappaB alpha (IκBα) and NFκB, preserved A20 and CAT levels, reduced ROSgreen density, and decreased the expression of p21 and SA-β-gal staining in ECs and VSMCs under HG culture. Our findings indicate that STS mitigates vascular senescence by modulating the A20-NFκB-NLRP3 inflammasome-CAT pathway in hyperglycemia conditions, offering novel insights into NLRP3 inflammasome activation and ECs and VSMCs senescence under HG culture. This study highlights the potential mechanism of STS in alleviating senescence in diabetic blood vessels, and provides essential evidence for its future clinical application.

Abstract Relationships between the visceral adiposity index (VAI) and type 2 diabetes mellitus (T2DM) have been underexplored. The purpose of this study is to explore association between VAI and T2DM in adults in the US. Based on the National Health and Nutrition Examination Survey 2007–2018, 11,214 participants aged 20 years or older were included in a cross-sectional study. Multifactorial logistic regression analysis and smoothed curve fitting analysis were performed to investigate links between VAI and the prevalence of T2DM, as well as the stability and incidence between subgroups. In a fully adjusted continuous model, the aggregate population risk of T2DM increased 0.43-fold with each 1-unit increase in VAI [odds ratio (OR) = 1.43; 95% confidence interval (CI) 1.35–1.50]. In the fully adjusted categorical model with VAI scores stratified by quartiles, results showed a higher T2DM advantage among participants in the second, third, and fourth quartiles (Q2: OR 1.35, 95% CI 1.06–1.71; Q3: OR 2.46, 95% CI 1.95–3.11; Q4: OR 4.42, 95% CI 3.55–05.50). Compared with Q1, the prevalence of T2DM in the total population increased 3.42-fold in Q4. The above results indicated that VAI was positively associated with the prevalence of T2DM, which was consistent and nonlinear with the smoothed curve-fitting analysis (P for non-linear = 0). Subgroup analyses after adjusting for covariates showed that keeping with the overall population results, it also was found that there was an interaction between sex and hypertension in the subgroups. VAI was positively associated with the prevalence of T2DM and was more prevalent in women, non-hypertensive than in men, hypertensive populations.

Abstract Direct laser acceleration (DLA) of electrons in plasmas of near-critical density (NCD) is a very advancing platform for high-energy PW-class lasers of moderate relativistic intensity supporting Inertial Confinement Fusion research. Experiments conducted at the PHELIX sub-PW Nd:glass laser demonstrated application-promising characteristics of DLA-based radiation and particle sources, such as ultra-high number, high directionality and high conversion efficiency. In this context, the bright synchrotron-like (betatron) radiation of DLA electrons, which arises from the interaction of a sub-ps PHELIX laser pulse with an intensity of 1019 W/cm2 with pre-ionized low-density polymer foam, was studied. The experimental results show that the betatron radiation produced by DLA electrons in NCD plasma is well directed with a half-angle of 100–200 mrad, yielding (3.4 ± 0.4)·1010 photons/keV/sr at 10 keV photon energy. The experimental photon fluence and the brilliance agree well with the particle-in-cell simulations. These results pave the way for innovative applications of the DLA regime using low-density pre-ionized foams in high energy density research.

Abstract Efficient seawater desalination is an effective way to solve the shortages of fresh water and energy but with limitations of the low fresh water production rate and high cost. Here, a hollow carbon fiber (HCF) wrapped by regular reduced graphene oxide (rGO) wave-like folds (rGO@HCF) is prepared on account of the differences in thermal shrinkage performance between graphene oxide (GO) and willow catkins fiber. Under one sun irradiation (1 kW m−2), the dry and wet surface temperature of the resulting evaporator reached up to 119.1 °C and 61.7 °C, respectively, and the water steam production rate reached 3.42 kg m−2 h−1. Also, for the outdoor experiment, the rGO@HCF exhibits good evaporator performance which reach up 27.8 kg m−2 day−1. Additionally, rGO@HCF also shows good seawater desalination performance and excellent durability for longtime work. DSC results indicate that the evaporation enthalpy of bulk water and adsorbed water decreased from 2503.92 to 1020.54 J g−1. The excellent evaporating performance is mainly attributed to the regular wave-like microstructure surface of the HCF, which can enhance the light absorption, reduced the vaporization enthalpy of the adsorption water. The findings not only introduce a novel approach for agricultural utilization, but also establish a crucial theoretical foundation for the design of regular wave-like microstructures.

Abstract New urbanization (NU) and ecological welfare performance (EWP) play pivotal roles in achieving sustainable urban development, with both emphasizing social equity and environmental management. Exploring the coordinated relationship between EWP and NU is invaluable for understanding the symbiotic interplay between humans and nature. We constructed a framework to elucidate the coupling mechanism of EWP and NU from the perspective of systems theory. We quantified the levels of NU and EWP utilizing the entropy weighting method and the super-efficient SBM method, respectively. Furthermore, we assessed the degree of coupling coordination between the two using the coupling coordination degree model (CCDM). Spatial and temporal evolution analysis was conducted, and factors influencing the degree of coupling coordination between EWP and NU were explored through a spatial–temporal geographically-weighted regression model (GTWR). The results indicate: (1) During the study period, the average annual increase in EWP in the study area was 2.59%, with a narrowing relative gap between cities. Conversely, the average annual increase in the level of NU was 7.6%, with demographic and economic dimensions carrying the highest weights. (2) The type of coupling coordination between EWP and NU transitions from basic coordination to moderate coordination, with the development of EWP lagging behind that of NU. (3) City size demonstrates a positive yet diminishing trend on the coupling coordination level, with economic development exerting the greatest influence and exhibiting a "V" trend, while the impact of green technology innovation diminishes negatively. Additionally, regional disparities are significant, with city size exhibiting a negative impact in areas of high population density and low economic levels, and green technology innovation showing notable polarization characteristics in core cities. These findings serve as a foundation for fostering coordinated ecological development amid the rapid urbanization process of the Chengdu–Chongqing Economic Circle.

Abstract Reduced hippocampal volume occurs in major depressive disorder (MDD), potentially due to elevated glucocorticoids from an overactivated hypothalamus–pituitary–adrenal (HPA) axis. To examine this in humans, hippocampal volume and hypothalamus (HPA axis) metabolism was quantified in participants with MDD before and after antidepressant treatment. 65 participants (n = 24 males, n = 41 females) with MDD were treated in a double-blind, randomized clinical trial of escitalopram. Participants received simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) before and after treatment. Linear mixed models examined the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism. Chi-squared tests and multivariable logistic regression examined the association between hippocampus/dentate gyrus volume change direction and hypothalamus activity change direction with treatment. Multiple linear regression compared these changes between remitter and non-remitter groups. Covariates included age, sex, and treatment type. No significant linear association was found between hippocampus/dentate gyrus volume and hypothalamus metabolism. 62% (38 of 61) of participants experienced a decrease in hypothalamus metabolism, 43% (27 of 63) of participants demonstrated an increase in hippocampus size (51% [32 of 63] for the dentate gyrus) following treatment. No significant association was found between change in hypothalamus activity and change in hippocampus/dentate gyrus volume, and this association did not vary by sex, medication, or remission status. As this multimodal study, in a cohort of participants on standardized treatment, did not find an association between hypothalamus metabolism and hippocampal volume, it supports a more complex pathway between hippocampus neurogenesis and hypothalamus metabolism changes in response to treatment.

Abstract Cardio-metabolic traits have been reported to be associated with the development of sepsis. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability, or are confounded by environmental factors. We performed three analyses to explore the relationships between cardio-metabolic traits and sepsis. Mendelian randomization (MR) study to evaluate the causal effects of multiple cardio-metabolic traits on sepsis. Global genetic correlation analysis to explore the correlations between cardio-metabolic traits and sepsis. Local genetic correlation (GC) analysis to explore shared genetic heritability between cardio-metabolic traits and sepsis. Some loci were further examined for related genes responsible for the causal relationships. Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies with sample sizes between 200,000 to 750,000. In MR, we found causality between BMI and sepsis (OR: 1.53 [1.4–1.67]; p

Abstract Endometrial cancer (EC) is a common gynecological tumor in females with an increasing incidence over the past few decades. Alcohol consumption has been linked to the occurrence of various cancers; However, epidemiological studies have shown inconsistent associations between alcohol consumption and EC risk. In order to avoid the influence of potential confounding factors and reverse causality in traditional epidemiological studies, we used a method based on genetic principles-Mendelian randomization (MR) analysis to test whether there is a causal relationship between alcohol consumption and EC. MR analysis was conducted using publicly available summary-level data from genome-wide association studies (GWAS). Fifty-seven single nucleotide polymorphisms (SNPs) were extracted as instrumental variables for alcohol exposure from the GWAS and Sequencing Consortium of Alcohol and Nicotine GWAS summary data involving 941,287 participants of European ancestry. SNPs for EC were obtained from the Endometrial Cancer Association Consortium, the Endometrial Cancer Epidemiology Consortium, and the UK Biobank, involving 121,885 European participants. The inverse variance weighted (IVW) method was used as the primary method to estimate the causal effect, and the MR-Egger regression and weighted median method were used as supplementary methods. Sensitivity analyses were conducted using the Mendelian Randomization Pleiotropy RESidual Sum and Outlier global test, MR-Egger intercept test, and leave-one-out analysis to evaluate the impact of pleiotropy on causal estimates. An increase of 1 standard deviation of genetically predicted log-transformed alcoholic drinks per day was associated with a 43% reduction in EC risk [odds ratio (OR) = 0.57, 95% confidence interval (CI) 0.41–0.79, P

Abstract Vehicle re-identification (Re-ID) involves identifying the same vehicle captured by other cameras, given a vehicle image. It plays a crucial role in the development of safe cities and smart cities. With the rapid growth and implementation of unmanned aerial vehicles (UAVs) technology, vehicle Re-ID in UAV aerial photography scenes has garnered significant attention from researchers. However, due to the high altitude of UAVs, the shooting angle of vehicle images sometimes approximates vertical, resulting in fewer local features for Re-ID. Therefore, this paper proposes a novel dual-pooling attention (DpA) module, which achieves the extraction and enhancement of locally important information about vehicles from both channel and spatial dimensions by constructing two branches of channel-pooling attention (CpA) and spatial-pooling attention (SpA), and employing multiple pooling operations to enhance the attention to fine-grained information of vehicles. Specifically, the CpA module operates between the channels of the feature map and splices features by combining four pooling operations so that vehicle regions containing discriminative information are given greater attention. The SpA module uses the same pooling operations strategy to identify discriminative representations and merge vehicle features in image regions in a weighted manner. The feature information of both dimensions is finally fused and trained jointly using label smoothing cross-entropy loss and hard mining triplet loss, thus solving the problem of missing detail information due to the high height of UAV shots. The proposed method’s effectiveness is demonstrated through extensive experiments on the UAV-based vehicle datasets VeRi-UAV and VRU.

Abstract Adipose tissue-derived stem cells (ADSCs) have been shown to improve erectile function in animal models of erectile dysfunction. However, few studies have been carried out using a reliable in vivo imaging method to trace transplanted cells in real time, which is necessary for systematic investigation of cell therapy. The study aims to explore the feasibility of non-invasively monitoring intracavernous injection of ADSCs in rat and miniature pig corpus cavernosum using in vivo magnetic resonance (MR) imaging. Thirty-six male Sprague Dawley rats (10 weeks old) and six healthy, sexually mature male miniature pigs (20 kg weight) were obtained. ADSCs were isolated from paratesticular fat of donor rats and cultured. Then ADSCs were labeled with superparamagnetic iron oxide nanoparticles (SPIONs), a type of MR imaging contrast agent, before transplantation into rats and pigs. After intracavernous injection, all rats and pigs underwent and were analyzed by MR imaging at the day of ADSC transplantation and follow-up at 1, 2 and 4 weeks after transplantation. In addition, penile histological examination was performed on all rats and pigs before (n = 6) and at 1 day (n = 6), 1 week (n = 6), 2 weeks (n = 6) or 4 weeks (n = 12) after ADSC transplantation. SPION-labeled ADSCs demonstrated a strong decreased signal intensity compared with distilled water, unlabeled ADSCs or agarose gel. SPION-labeled ADSCs showed a hypointense signal at all concentrations, and the greatest hypointense signal was observed at the concentration of 1 × 106. MR images of the corpus cavernosum showed a hypointense signal located at the injection site. T2*-weighted signal intensity increased over the course of 1 week after ADSCs transplantation, and demonstrated a similar MR signal with that before ADSCs transplantation. After SPION-labeled ADSC injection, T2*-weighted MR imaging clearly demonstrated a marked hypointense signal in pig corpus cavernosum. The T2*-weighted signal faded over time, similar to the MR imaging results in rats. Obvious acute inflammatory exudation was induced by intracavernous injection, and the T2*-weighted signal intensity of these exudation was higher than that of the injection site. The presence of iron was detected by Prussian blue staining, which demonstrated ADSC retention in rat corpus cavernosum. Lack of cellular infiltrations were demonstrated by H&E staining before and 4 weeks after transplantation, which indicated no negative immune response by rats. Prussian blue staining was positive for iron oxide nanoparticles at 2 weeks after transplantation. SPION-labeled ADSCs showed a clear hypointense signal on T2-weight MRI in vitro and in vivo. The MR signal intensity in the corpus cavernosum of the rats and miniature pigs faded and disappeared over time after ADSC transplantation. These findings suggested that MR imaging could trace transplanted ADSCs in the short term in the corpus cavernosum of animals.

Abstract Previous intervention studies have shown some benefits of dark chocolate for the cardiovascular system, but it has not been established whether dark chocolate intake is associated with the risk of cardiovascular diseases (CVDs). To investigate the causality between dark chocolate intake and the risk of CVDs, a Mendelian randomization (MR) study was conducted. We obtained summary-level data on dark chocolate intake and CVDs from publicly available genome-wide association studies. In this MR study, the main approach was to use a fixed-effect model with inverse variance weighted (IVW) and evaluate the robustness of the results via sensitivity analysis. We found that dark chocolate intake was significantly associated with the reduction of the risk of essential hypertension (EH) (OR = 0.73; 95% CI 0.60–0.88; p = 1.06 × 10−3), as well as with the suggestive association to the reduced risk of venous thromboembolism (OR = 0.69; 95% CI 0.50–0.96; p = 2.81 × 10−2). However, no association was found between dark chocolate intake and the other ten CVDs. Our study provides evidence for a causality between dark chocolate intake and a reduced risk of EH, which has important implications for the prevention of EH in the population.

Abstract To determine the risk factors for dilated cardiomyopathy (DCM) and construct a risk model for predicting HF in patients with DCM, We enrolled a total of 2122 patients, excluding those who did not meet the requirements. A total of 913 patients were included in the analysis (611 males and 302 females) from October 2012 to May 2020, and data on demographic characteristics, blood biochemical markers, and cardiac ultrasound results were collected. Patients were strictly screened for DCM based on the diagnostic criteria. First, these patients were evaluated using propensity score matching (PSM). Next, unconditional logistic regression was used to assess HF risk. Furthermore, receiver operating characteristic (ROC) curve analysis was conducted to determine diagnostic efficiency, and a nomogram was developed to predict HF. Finally, the Kaplan‒Meier survival curve was plotted. Of the initial 2122 patients, the ejection fraction (EF) in males was worse. We included 913 patients after the final DCM diagnosis. The results showed that the levels of NT-proBNP, WBC, PLT, neutrophils, lymphocytes, eosinophils, and IL-6, C-reactive protein (CRP) and the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and CRP/lymphocyte ratio (CLR) were higher in males than in females (P

Abstract Non-obese diabetic (NOD) mice were taken as primary Sjögren’s syndrome (pSS) model mice to examine the therapeutic impact of iguratimod (IGU) on inflammatory factors levels and apoptosis of submandibular epithelial cells, and provide experimental basis for the treatment of pSS by iguratimod. Twenty-four NOD murine models were divided into the model, high-dose (IGU 30 mg/kg) and low-dose (IGU 10 mg/kg) groups, eight mice per group. The normal control group comprised eight C57B/L mice. From 8 weeks of age, the NOD mice were administered IGU by intragastric gavage administration every day for 8 weeks; their water consumption, saliva secretion, submandibular gland, and spleen indices were measured. The levels of serum inflammatory factor (IL-1β, TNF-α, IL-6, and IL-17) were evaluated, and Bax, caspase-3, and Bcl-2 levels were detected. The histological alterations in the submandibular glands were discovered. IGU can reduce the water intake of NOD mice (p

Abstract Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg reflector (AgNPs/PSB) composite SERS substrate with high sensitivity and strong stability was prepared by immersion plating and heat treatment using porous silicon Bragg reflector (PSB) as the substrate. The substrate combines the five deep learning algorithms of the improved AlexNet, ResNet, SqueezeNet, temporal convolutional network (TCN) and multiscale fusion convolutional neural network (MCNN). We constructed rapid screening models for patients with primary Sjögren’s syndrome (pSS) and healthy controls (HC), diabetic nephropathy patients (DN) and healthy controls (HC), respectively. The results showed that the annealed AgNPs/PSB composite SERS substrates performed well in diagnosing. Among them, the MCNN model had the best classification effect in the two groups of experiments, with an accuracy rate of 94.7% and 92.0%, respectively. Previous studies have indicated that the AgNPs/PSB composite SERS substrate, combined with machine learning algorithms, has achieved promising classification results in disease diagnosis. This study shows that SERS technology based on annealed AgNPs/PSB composite substrate combined with deep learning algorithm has a greater developmental prospect and research value in the early identification and screening of immune diseases and chronic kidney disease, providing reference ideas for non-invasive and rapid clinical medical diagnosis of patients.

Abstract To evaluate the feasibility and clinical significance of the left perinephric fat sac vein (PFSV) as an anatomical landmark in locating left adrenal gland (LAD) during retroperitoneal laparoscopic left adrenalectomy (RLLA). In this study, a total of 36 patients who underwent RLLA were enrolled from February 2019 and March 2021. By following a vein vessel on the internal surface of perinephric fat sac (PFS), known as PFSV, LAD was searched finally along the upper edge of this vein. The demographic and clinical characteristics of these patients were acquired, including tumor features and perioperative outcomes (operating time, estimated blood loss, complications). The operations were successfully completed in all the 36 patients without conversion to open surgery. In addition, the LAD was successfully found along the upper edge of PFSV in 34 patients. For all operations, the mean operative time was 75 min (range 60–95) and the estimated blood loss was 20 ml (range 10–50). The median oral intake was 20.7 h (range 6–39). The median hospital stay was 6.3 days (range 4–9), and the median follow-up was 12.3 months (range 9–17). Moreover, no intraoperative complications were observed and no residual tumors were detected after 9 to 15 months follow-up. It may be a safe and efficient procedure to use PFSV as a landmark for searching LAD during RLLA, especially for beginners. However, more studies with larger sample size are need to be conducted to further evaluate the outcomes of this method and the significance of PFSV in searching LAD during RLLA.

Abstract Traditional fingerprint localization algorithms need help with low localization accuracy, large data volumes, and device dependence. This paper proposes a LoRa-based improved fingerprint localization algorithm-particle swarm optimization-random forest-fingerprint localization for indoor localization. The first improvement step involves creating a new exceptional fingerprint value (referred to as RSSI-RANGE) by adding the Time of Flight ranging value (referred to as RANGE) to the Received Signal Strength Indication (RSSI) value and weighting them together. The second improvement step involves preprocessing the fingerprint data to eliminate gross errors using Gaussian and median filtering. After noise reduction, the particle swarm optimization algorithm is used to optimize the hyper parameters of the random forest algorithm, and the best RSSI-RANGE value is obtained using the random forest algorithm. The Kriging method is then used for interpolation to establish an offline fingerprint database, and the final online recognition and localization are performed. Experimental results demonstrate that the first improvement step improves localization accuracy by 53–57% in different experimental scenarios, while the second improves localization accuracy by 25–31%. When both steps are combined, the localization accuracy is improved by 58–63%. The effectiveness of this method is demonstrated through experiments.

Abstract A three-dimensional CFD simulation model was established to study the characteristics of flow, drifts and salt deposition from 6 super-large seawater cooling towers in a power station. In the model, site meteorological data, design parameters of cooling tower, general layout, environmental characteristics, are considered. The results show that: (1) when the wind direction is parallel to the towers, the streams overlap, reducing deposition of drifts and salt onto the ground. (2) The drifts with particle size greater than 550 μm cannot float out of cooling towers. (3) In normal operation of 6 such cooling towers, the resulting salt deposition will not cause serious damage to plants.

Abstract To assess biobehavioral sex differences in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) utilizing a low burden exercise protocol, 22 females and 15 males with ME/CFS and 14 healthy controls underwent two six-min walk tests. Fifteen daily assessments were scheduled for fatigue and function ratings and heart monitoring. Six-min walk tests were conducted on days 8 and 9. The ME/CFS group showed high self-report fatigue and impaired physical function, whereas healthy controls did not show fatigue or function abnormalities. In patients, no significant post-exercise changes were found for heart rate variability (HRV); however, heart rate decreased in ME/CFS males from Day 14 to Day 15 (p = 0.046). Female patients showed increased fatigue (p = 0.006) after the initial walk test, but a downward slope (p = 0.008) in fatigue following the second walk test. Male patients showed a decrease in self-report work limitation in the days after exercise (p = 0.046). The healthy control group evidenced a decrease in HRV after the walk tests from Day 9–14 (p = 0.038). This pilot study did not confirm hypotheses that females as compared to males would show slower exercise recovery on autonomic or self-report (e.g. fatigue) measures. A more exertion-sensitive test may be required to document prolonged post-exertional abnormalities in ME/CFS. Trial registration: NCT NCT03331419.

Abstract Crohn's disease (CD) is a complex autoimmune disorder presumed to be driven by complex interactions of genetic, immune, microbial and even environmental factors. Intrinsic molecular mechanisms in CD, however, remain poorly understood. The identification of novel biomarkers in CD cases based on larger samples through machine learning approaches may inform the diagnosis and treatment of diseases. A comprehensive analysis was conducted on all CD datasets of Gene Expression Omnibus (GEO); our team then used the robust rank aggregation (RRA) method to identify differentially expressed genes (DEGs) between controls and CD patients. PPI (protein‒protein interaction) network and functional enrichment analyses were performed to investigate the potential functions of the DEGs, with molecular complex detection (MCODE) identifying some important functional modules from the PPI network. Three machine learning algorithms, support vector machine-recursive feature elimination (SVM-RFE), random forest (RF), and least absolute shrinkage and selection operator (LASSO), were applied to determine characteristic genes, which were verified by ROC curve analysis and immunohistochemistry (IHC) using clinical samples. Univariable and multivariable logistic regression were used to establish a machine learning score for diagnosis. Single-sample GSEA (ssGSEA) was performed to examine the correlation between immune infiltration and biomarkers. In total, 5 datasets met the inclusion criteria: GSE75214, GSE95095, GSE126124, GSE179285, and GSE186582. Based on RRA integrated analysis, 203 significant DEGs were identified (120 upregulated genes and 83 downregulated genes), and MCODE revealed some important functional modules in the PPI network. Machine learning identified LCN2, REG1A, AQP9, CCL2, GIP, PROK2, DEFA5, CXCL9, and NAMPT; AQP9, PROK2, LCN2, and NAMPT were further verified by ROC curves and IHC in the external cohort. The final machine learning score was defined as [Expression level of AQP9 × (2.644)] + [Expression level of LCN2 × (0.958)] + [Expression level of NAMPT × (1.115)]. ssGSEA showed markedly elevated levels of dendritic cells and innate immune cells, such as macrophages and NK cells, in CD, consistent with the gene enrichment results that the DEGs are mainly involved in the IL-17 signaling pathway and humoral immune response. The selected biomarkers analyzed by the RRA method and machine learning are highly reliable. These findings improve our understanding of the molecular mechanisms of CD pathogenesis.

Abstract The association between gut microbiome and chronic metabolic disease including polycystic ovary syndrome (PCOS), is well documented, however, the relationship between the gut microbiota and serum metabolites remains unknown. In this study, untargeted metabolomics together with a 16S rRNA gene sequencing tool was used to detect small molecule serum metabolites and the gut microbiome. We identified 15 differential metabolites between PCOS patients and the healthy control. Lysophosphatidylcholine (LPC) (18:2, 20:3, 18:1, P-16:0, 17:0, 15:0, 18:3, 20:4), phosphatidylcholine(PC), ganglioside GA2 (d18:1/16:0) and 1-linoleoylglycerophosphocholine were increased in the PCOS group, and the concentrations of phosphoniodidous acid, bilirubin, nicotinate beta-d-ribonucleotide and citric acid were decreased in the PCOS group, suggesting a lipid metabolism and energy metabolism disorder in the PCOS patients. The diversity of gut microbiota in PCOS group was lower than that in healthy controls. Escherichia/Shigella, Alistipes and an unnamed strain 0319_6G20 belonging to Proteobacteria were important distinguishing genera (LDA > 3.5) in PCOS. Prevotella_9 was positively correlated with phosphoniodidous acid, nicotinate beta-d-ribonucleotide and citric acid concentrations, and negatively correlated with the concentration of LPC (20:3) and 1-linoleoylglycerophosphocholine; Roseburia was negatively correlated with LPC concentration (20:4), while the characteristic genus 0319_6G20 of PCOS was positively correlated with LPC concentration (20:3) (COR > 0.45). SF-36 in the PCOS group was significantly lower than that in the healthy control (HC) group, which was associated with the presence of Escherichia-Shigella and Alistipes. Our finding demonstrated the correlation between the gut microbiota and serum metabolites in PCOS, and therefore characteristic gut microbiota and metabolites may play an important role in the insulin resistance and the mood changes of PCOS patients.

Abstract Although people all know that nicotine in tobacco smoke is the key to cause health damage, they ignore the synergistic effect of a large number of Volatile Organic Compounds (VOCs) produced by incomplete tobacco combustion on nicotine or cotinine metabolism. Our aim is to investigate the association between serum VOCs and cotinine in smokers infected with HIV, HBV or HCV. National Health and Nutrition Examination Survey (NHANES 2005–2018) database, including 13,652 nationally representative subjects’ sociodemographic characteristics and serological indicators, was used in this study. Smokers living with human immunodeficiency virus (HIV), hepatitis B virus (HBV) or hepatitis C virus (HCV) were compared to non-infected population. The correlation between VOCs and cotinine as well as the effects of VOCs on cotinine metabolism were analyzed by Spearman correlation analysis and multivariable logistic regression analysis, respectively. Among HIV, HBV, or HCV infected smokers with the largest exposure dose to tobacco, the intensity of the association between VOCs and cotinine was the strongest. The results of multivariable binary logistic regression showed that high concentrations of 1,2-Dichlorobenzene (OR:1.036, CI:1.009–1.124), Benzene (OR:1.478, CI:1.036–2.292), Carbon Tetrachloride (OR:1.576, CI:1.275–2.085) and 2,5-Dimethylfuran (OR:1.091, CI:1.030–1.157) in blood might be independent risk factors leading to the increase of serum metabolite cotinine in smokers.

Abstract Ferroptosis, a newly discovered irondependent form of regulated cell death caused by excessive accumulation of lipid peroxides, is linked to the development and treatment response of various types of cancer, including gastric cancer (GC). Noncoding RNAs (ncRNAs), as key regulators in cancer, have both oncogenic and tumor suppressive roles. However, studies on ferroptosis-related ncRNA networks in GC are still lacking. Here, we first identified 61 differentially expressed genes associated with ferroptosis in GC by computing and analyzing gene expression profile of tumor and normal tissues for GC. Then, upstream lncRNAs and miRNAs interacting with them were found through miRNet and miRBase databases, and hub lncRNAs and miRNAs were obtained through topological analysis. Finally, the ceRNA regulatory network linked to ferroptosis in GC was established, which includes two ferroptosis marker genes (TXNIP and TSC22D3), one driver gene (GABARAPL1), and one suppressor gene (CAV1). Kaplan-Meier survival analysis showed that changes in the expression of these genes were associated with the survival of GC patients. Furthermore, our study revealed that this ceRNA network may influence the progression of GC by regulating ferroptosis process. These results will help experimental researchers to design an experiment study to further explore the roles of this regulatory network in GC ferroptosis.

Abstract Although the smoking rate of human immunodeficiency virus (HIV), hepatitis B virus (HBV) or hepatitis C virus (HCV) infected people was much higher than that of the general population, smoking cessation interventions have long been ineffective. We aimed to examine the estimates of prevalence, time-trend, and association of smoking among people living with HIV, HBV, or HCV. This cohort was composed of 32,115 individuals from the NHANES database (1999–2018) and they were collected in the US. The time trend analysis of smoking and quitting rates was conducted using different years of survey follow-up and different infected groups. Multivariable logistic regression analysis was used to identify the risk factors related to smoking behavior of these infected people. Compared to non-infected smokers, infected smokers were more likely to be older (aged 30–39, OR = 9.92, CI 6.07–16.21; aged 40–49,OR = 3.51, CI 2.49–4.94), males (1.99, 1.54–2.55), lower education and economic level (1.78, 1.39–2.29; 2.05, 1.59–2.65), unemployed (1.63, 1.21–2.20), suffering depression (1.35, 1.05–1.72), and drug users (7.65, 5.04–11.59). Taken together, our study showed that these complex psychosocial characteristics and unhealthy behavioral factors might be major independent risk factors for increasing smoking rate and decreasing smoking cessation rate among these infected people.

Abstract In this current research, the left-over residues collected from the dark fermentation-microbial electrolysis cells (DF-MEC) integrated system solely biocatalyzed by activated sludge during the bioconversion of the agricultural straw wastes into hydrogen energy, was investigated for its feasibility to be used as a potential alternative biofertilizer to the commonly costly inorganic ones. The results revealed that the electrohydrogenesis left-over residues enriched various plant growth-promoting microbial communities including Enterobacter (8.57%), Paenibacillus (1.18%), Mycobacterium (0.77%), Pseudomonas (0.65%), Bradyrhizobium (0.12%), Azospirillum (0.11%), and Mesorhizobium (0.1%) that are generally known for their ability to produce different essential phytohormones such as indole-3-acetic acid/indole acetic acid (IAA) and Gibberellins for plant growth. Moreover, they also contain both phosphate-solubilizing and nitrogen-fixing microbial communities that remarkably provide an adequate amount of assimilable phosphorus and nitrogen required for enhanced plants or crop growth. Furthermore, macro-, and micronutrients (including N, P, K, etc.) were all analyzed from the residues and detected adequate appreciate concentrations required for plant growth promotions. The direct application of MEC-effluent as fertilizer in this current study conspicuously promoted plant growth (Solanum lycopersicum L. (tomato), Capsicum annuum L. (chilli), and Solanum melongena L. (brinjal)) and speeded up flowering and fruit-generating processes. Based on these findings, electrohydrogenesis residues could undoubtedly be considered as a potential biofertilizer. Thus, this technology provides a new approach to agricultural residue control and concomitantly provides a sustainable, cheap, and eco-friendly biofertilizer that could replace the chemical costly fertilizers.

Abstract The value of ecosystem services, as well as their temporal and spatial characteristics, can be used to help areas develop focused and localized sustainable ecological management plans. Thus, this study conducted in the Yellow River Basin (YRB) of China, analyzed the ecosystem service value (ESV) and its spatial–temporal variation characteristics. This study used the equivalent factor and geospatial exploration methods, introduced the elasticity coefficient, and explored the response of ESV change to land-use change, based on the land use cover data from 1990 to 2020. The results showed that from 1990 to 2020, YRB ecosystem service value showed an overall increasing trend, mainly because the ecological construction project increased forest and grasslands in this region. In the past 30 years, spatial characteristics of ESV in YRB was relatively stable. The high-value areas were mainly distributed in the upper Yellow River Basin, while the low-value areas were mainly distributed in the lower Yellow River Basin, as the cold and hot spots were reduced. The ESV barycenter coordinates showed the direction of the transfer trajectory, which is first to southwest, northeast, and then to southwest. From 2000 to 2010, YRB land-use change had greater impact on ESV. Since 2010, the disturbance of ecosystem services by land-use change has decreased. Consequently, the elastic index of the upstream and Loess Plateau regions were significantly higher than that of other regions, and the impact of land-use change on ecosystem services was more obvious, due to improved large-scale ecological construction projects implementation. Conclusively, this study recommends the use of comprehensive spatial–temporal assessment of ESV for sustainable development and ecological protection in the YRB.

Abstract Facial colour characteristics convey vital personal information and influence social interactions and mate choices as contributing factors to perceived beauty, health, and age. How various colour characteristics affect facial preference and whether there are cultural differences are not fully understood. Here, we provide a useful and repeatable methodology for skin colour research based on a realistic skin model to investigate the effect of various facial colour characteristics on facial preference and compare the role of colour predictors in Caucasian (CA) and Chinese (CN) samples. Our results show that, although the average skin colour of facial areas plays a limited role, together with colour variation and contrast, there are stronger links between colour and facial preference than previously revealed. We also find large cultural differences in facial colour perceptions; Chinese observers tend to rely more heavily on colour and lightness cues to judge facial preference than Caucasian observers.

Abstract The optimization work of a newly proposed 20-in. photomultiplier tube based on dynode and microchannel plates (Dynode-MCP-PMT) are conducted in this paper. Three-dimensional models are developed in CST STUDIO SUITE to systematically investigate the effects of the size and bias voltage of the two focusing electrodes, dynode and the glass envelop handle based on the Finite Integral Technique and Monte Carlo method. Results predict that the collection efficiency and the transit time spread of the optimized design are substantially improved which are 100% and 3.7 ns.

Abstract To date, various solar driven evaporation technologies have been developed for treatment of seawater and wastewater but with the threat from salt polluted and single treatment of seawater. Herein, we develop a multifunctional evaporator constructed by carbon fiber coated by quinoa cellulose nanosheet (CFQC) with outstanding self-cleaning performance and good purification property for treatment of organic and antibiotic polluted water. The resulting Zn-CFQC exhibits good light to thermal performance which can absorb about 86.95% lights in the range of UV–Vis–NIR (200–2500 nm); therefore, the wet and dry surface temperatures of Zn-CFQC are held at 62.1 and 124.3 °C respectively, and keep a speed of 3.2 kg m−2 h−1 for water evaporating under 1000 W m−2 illumination. Such good light-to-thermal capabilities can be mainly imputed to the unique surface microstructures of the carbon fiber which decorated by two-dimension cellulose and activated by ZnCl2. Additionally, Zn-CFQC shows good salt automatic-cleaning capability at night and corresponding mechanism has been simply elucidated according to the chemical potential theory. The method of treatment of carbon fiber opens a new way for commercial carbon fiber utilization of solar assisted water purification.

Abstract In the present paper, the pile-soil system’s total potential energy equation of underpinning piles was established based on the Winkler elastic foundation beam theory. This energy equation was used to explore the effect of basement excavation beneath existing buildings on the underpinning pile’ buckling stability. Utilizing the minimum potential energy theory, the expression of the critical buckling load for underpinning piles’ stability during the excavation project was obtained. Moreover, the influencing factors of the critical buckling load were investigated. It was found that the underpinning pile’s critical load converged with the augment of half-wave number. Moreover, the pile skin friction and deadweight had an insignificant influence on it. In addition, the critical load of underpinning piles decreased sharply with the increasing excavation depth and gradually increased with the augment of pile diameter. The results of this study provides a basis for the design of adding piles in similar projects and reduces the hidden danger of excavation instability.

Abstract Predicting the chances mortality within 1 year in non-ischemic dilated cardiomyopathy patients can be very useful in clinical decision-making. This study has developed and validated a risk-prediction model for identifying factors contributing to mortality within 1 year in such patients. The predictive nomogram was constructed using a retrospective cohort study, with 615 of patients hospitalized in the First Affiliated Hospital of Guangxi Medical University between October 2012 and May 2020. A variety of factors, including presence of comorbidities, demographics, results of laboratory tests, echocardiography data, medication strategies, and instances of heart transplant or death were collected from electronic medical records and follow-up telephonic consultations. The least absolute shrinkage and selection operator and logistic regression analyses were used to identify the critical clinical factors for constructing the nomogram. Calibration, discrimination, and clinical usefulness of the predictive model were assessed using the calibration plot, C-index and decision curve analysis. Internal validation was assessed with bootstrapping validation. Among the patients from whom follow-up data were obtained, the incidence of an end event (deaths or heart transplantation within 1 year) was 171 cases per 1000 person-years (105 out of 615). The main predictors included in the nomogram were pulse pressure, red blood cell count, left ventricular end-diastolic dimension, levels of N-terminal pro b-type natriuretic peptide, medical history, in-hospital worsening heart failure, and use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. The model showed excellent discrimination with a C-index of 0.839 (95% CI 0.799–0.879), and the calibration curve demonstrated good agreement. The C-index of internal validation was 0.826, which demonstrated that the model was quite efficacious. A decision curve analysis confirmed that our nomogram was clinically useful. In this study, we have developed a nomogram that can predict the risk of death within 1 year in patients with non-ischemic dilated cardiomyopathy. This will be useful in the early identification of patients in the terminal stages for better individualized clinical decisions.

Abstract As a distributed storage scheme, the blockchain network lacks storage space has been a long-term concern in this field. At present, there are relatively few research on algorithms and protocols to reduce the storage requirement of blockchain, and the existing research has limitations such as sacrificing fault tolerance performance and raising time cost, which need to be further improved. Facing the above problems, this paper proposes a protocol based on Distributed Image Storage Protocol (DISP), which can effectively improve blockchain storage space and reduces computational costs in the help of InterPlanetary File System (IPFS). In order to prove the feasibility of the protocol, we make full use of IPFS and distributed database to design a simulation experiment for blockchain. Through distributed pooling (DP) algorithm in this protocol, we can divide image evidence into recognizable several small files and stored in several nodes. And these files can be restored to lossless original documents again by inverse distributed pooling (IDP) algorithm after authorization. These advantages in performance create conditions for large scale industrial and commercial applications.

Abstract Deep learning techniques have led to significant advancements in seizure prediction research. However, corresponding used benchmarks are not uniform in published results. Moreover, inappropriate training and evaluation processes used in various work create overfitted models, making prediction performance fluctuate or unreliable. In this study, we analyzed the various data preparation methods, dataset partition methods in related works, and explained the corresponding impacts to the prediction algorithms. Then we applied a robust processing procedure that considers the appropriate sampling parameters and the leave-one-out cross-validation method to avoid possible overfitting and provide prerequisites for ease benchmarking. Moreover, a deep learning architecture takes advantage of a one-dimension convolutional neural network and a bi-directional long short-term memory network is proposed for seizure prediction. The architecture achieves 77.6% accuracy, 82.7% sensitivity, and 72.4% specificity, and it outperforms the indicators of other prior-art works. The proposed model is also hardware friendly; it has 6.274 k parameters and requires only 12.825 M floating-point operations, which is advantageous for memory and power constrained device implementations.

Abstract Intravitreal anti-VEGF (anti-vascular endothelial growth factor) biologics have revolutionized the pharmacological management of chorioretinal diseases. However, the systemic adverse events such as stroke or bleeding are the concerns for many patients and physicians. The mechanism to develop these side effects are poorly understood. Consecutive 95 patients with retinal diseases were studied for their blood activated partial thromboplastin time (APTT), prothrombin time (PT), international normalized ratio (INR), and concentration of fibrinogen before and after intravitreal conbercept. Additionally, plasma nitric oxide (NO) and endothelin-1 (ET-1) were investigated on 38 of the 95 patients. Compared with the pre-injection, 4-week post-injection values of APTT and PT were increased by 0.582 s (p = 0.038, paired t test) and by 0.086 s (p = 0.080, paired t test; p = 0.0475, Sign test), respectively. At the same time, fibrinogen decreased by 0.048 g/L. Plasma levels of NO or ET-1 or VEGF did not significantly change from pre-injection levels. Our findings advanced the understanding of mechanism for systemic side effects associated with intravitreal anti-VEGF and emphasized paying more attention to higher risk of possible bleedings for patients following intravitreal conbercept.

Abstract Chest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific CXR findings has been the main focus of several artificial intelligence (AI) systems. However, the wide range of possible CXR abnormalities makes it impractical to detect every possible condition by building multiple separate systems, each of which detects one or more pre-specified conditions. In this work, we developed and evaluated an AI system to classify CXRs as normal or abnormal. For training and tuning the system, we used a de-identified dataset of 248,445 patients from a multi-city hospital network in India. To assess generalizability, we evaluated our system using 6 international datasets from India, China, and the United States. Of these datasets, 4 focused on diseases that the AI was not trained to detect: 2 datasets with tuberculosis and 2 datasets with coronavirus disease 2019. Our results suggest that the AI system trained using a large dataset containing a diverse array of CXR abnormalities generalizes to new patient populations and unseen diseases. In a simulated workflow where the AI system prioritized abnormal cases, the turnaround time for abnormal cases reduced by 7–28%. These results represent an important step towards evaluating whether AI can be safely used to flag cases in a general setting where previously unseen abnormalities exist. Lastly, to facilitate the continued development of AI models for CXR, we release our collected labels for the publicly available dataset.

Abstract Sarcoma is a rare malignancy with unfavorable prognoses. Accumulating evidence indicates that aberrant alternative splicing (AS) events are generally involved in cancer pathogenesis. The aim of this study was to identify the prognostic value of AS-related survival genes as potential biomarkers, and highlight the functional roles of AS events in sarcoma. RNA-sequencing and AS-event datasets were downloaded from The Cancer Genome Atlas (TCGA) sarcoma cohort and TCGA SpliceSeq, respectively. Survival-related AS events were further assessed using a univariate analysis. A multivariate Cox regression analysis was also performed to establish a survival-gene signature to predict patient survival, and the area-under-the-curve method was used to evaluate prognostic reliability. KOBAS 3.0 and Cytoscape were used to functionally annotate AS-related genes and to assess their network interactions. We detected 9674 AS events in 40,184 genes from 236 sarcoma samples, and the 15 most significant genes were then used to construct a survival regression model. We further validated the involvement of ten potential survival-related genes (TUBB3, TRIM69, ZNFX1, VAV1, KCNN2, VGLL3, AK7, ARMC4, LRRC1, and CRIP1) in the occurrence and development of sarcoma. Multivariate survival model analyses were also performed, and validated that a model using these ten genes provided good classifications for predicting patient outcomes. The present study has increased our understanding of AS events in sarcoma, and the gene-based model using AS-related events may serve as a potential predictor to determine the survival of sarcoma patients.

Abstract Feed efficiency (FE) is an important economic indicator in pig production. Improving the FE of commercial pigs is an important strategy for minimizing pig production costs and providing sustainability to the pig industry. In this study, nontargeted LC–MS metabolomics was performed on the contents of the three intestine segments (ileum, cecum and colon) of high-FE and low-FE pigs to explore the effects of small-molecule metabolites in pig intestine on pig FE. A total of 225 Duroc × (Landrace × Yorkshire) pigs in the 30–100 kg stage were sorted based on FE, and 20 pigs with extreme phenotypes were selected, with 10 in each group. A total of 749 metabolites were identified, of which 15, 38 and 11 differed between high-FE and low-FE pigs in ileum, cecum and colon, respectively. These candidate biomarkers mainly comprised lipids and organic acids, which could partially explain the FE difference between the two groups. Among the identified differential metabolites, the lipids are mainly involved in combatting inflammation and oxidation in the ileum and cecum and in bile acid metabolism and vitamin D absorption in the cecum. A difference in organic acids was mainly observed in the hindgut, which is involved in the metabolism of amino acids and fatty acids. This comprehensive study provides new insight into the biochemical mechanisms associated with pig FE.

Abstract In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement on the sentiment and performance of other companies from the same or even different sectors. In this paper, we apply NLP techniques to understand news sentiment of 87 companies among the most reported on Reuters for a period of 7 years. We investigate the propagation of such sentiment in company networks and evaluate the associated market movements in terms of stock price and volatility. Our results suggest that, in certain sectors, strong media sentiment towards one company may indicate a significant change in media sentiment towards related companies measured as neighbours in a financial network constructed from news co-occurrence. Furthermore, there exists a weak but statistically significant association between strong media sentiment and abnormal market return as well as volatility. Such an association is more significant at the level of individual companies, but nevertheless remains visible at the level of sectors or groups of companies.

Abstract Extracellular acidosis is considered as a hallmark of most human tumors, which plays an important role in promoting tumor malignant and aggressive phenotype in tumorigenesis. Acidosis and lactic acidosis can induce different responses in tumors. Previous studies have associated the response to lactic acidosis of tumors with good survival outcomes. In this study, we investigated the metabolomic changes in triple negative and luminal subtype breast cancer cell lines in response to acidosis and lactic acidosis. Our results showed that acidosis results in the reduction of cell viability and glycolysis in breast cancer cells, which is reversely correlated with the malignancy of cell lines. Under lactic acidosis, this reduction is reversed slightly. Untargeted metabolomic profiling revealed that glutaminolysis and fatty acid synthesis in cancer cells under acidosis are increased, while TCA cycle and glycolysis are decreased. Under lactic acidosis, the pentose phosphate pathway and acetate release are increased in MDA-MB-231 cells. The current results uncovered the different metabolic responses of breast cancer cells to acidosis and lactic acidosis, demonstrating the power of combined untargeted and stable isotope assisted metabolomics in comprehensive metabolomic analysis.

Abstract Slope aspect plays a critical role in influencing vegetation pattern in semiarid area. The dry valleys of the Hengduan Mountains Region, southwestern China, are striking geographical landscape, suffering from severe ecological degradation. Here, we comprehensively investigated how slope aspect affects vegetation attributes in one of these valleys- the dry valley in the upper reaches of Min River. Three sites were selected along the valley and we quantitively examined the vegetation difference between slope aspects at the whole valley scale and each site level. We found significant vegetation differences between slope aspects in species composition, vegetative structure, and biodiversity pattern, which were in accordance with the observed significant difference in soil nutrient. Generally, north-facing slopes are associated with higher biomass, coverage and height, and species diversity than south-facing slopes. We also found between-aspect differences varied among the study sites, resulting in increased biomass, height, and β diversity differences, decreased density and coverage differences, and opposite trend observed in α diversity at relatively wet site. In conclusion, slope aspect had significant effect on vegetation attributes, which was significantly influenced by local climate (aridity) in terms of both strength and direction depending on the specific attributes investigated.

Abstract Fireflies are among the most charismatic insects for their spectacular bioluminescence, but the origin and evolution of bioluminescence remain elusive. Especially, the genic basis of luciferin (d-luciferin) biosynthesis and light patterns is largely unknown. Here, we present the high-quality reference genomes of two fireflies Lamprigera yunnana (1053 Mb) and Abscondita terminalis (501 Mb) with great differences in both morphology and luminous behavior. We sequenced the transcriptomes and proteomes of luminous organs of two species. We created the CRISPR/Cas9-induced mutants of Abdominal B gene without luminous organs in the larvae of A. terminalis and sequenced the transcriptomes of mutants and wild-types. Combining gene expression analyses with comparative genomics, we propose a more complete luciferin synthesis pathway, and confirm the convergent evolution of bioluminescence in insects. Using experiments, the function of the firefly acyl-CoA thioesterase (ACOT1) to convert l-luciferin to d-luciferin was validated for the first time. Comparisons of three-dimension reconstruction of luminous organs and their differentially expressed genes among two species suggest that two positive genes in the calcium signaling pathway and structural difference of luminous organs may play an important role in the evolution of flash pattern. Altogether, our results provide important resources for further exploring bioluminescence in insects.

Abstract The decoding throughput during post-processing is one of the major bottlenecks that occur in a continuous-variable quantum key distribution (CV-QKD) system. In this paper, we propose a layered decoder to decode quasi-cyclic multi-edge type LDPC (QC-MET-LDPC) codes using a graphics processing unit (GPU) in continuous-variable quantum key distribution (CV-QKD) systems. As described herein, we optimize the storage methods related to the parity check matrix, merge the sub-matrices which are unrelated, and decode multiple codewords in parallel on the GPU. Simulation results demonstrate that the average decoding speed of LDPC codes with three typical code rates, i.e., 0.1, 0.05 and 0.02, is up to 64.11 Mbits/s, 48.65 Mbits/s and 39.51 Mbits/s, respectively, when decoding 128 codewords of length $${10}^{{6}}$$ 10 6 simultaneously without early termination.

Abstract Moulting is a fundamental component of the ecdysozoan life cycle, but the fossil record of this strategy is susceptible to preservation biases, making evidence of ecdysis in soft-bodied organisms extremely rare. Here, we report an exceptional specimen of the fuxianhuiid Alacaris mirabilis preserved in the act of moulting from the Cambrian (Stage 3) Xiaoshiba Lagerstätte, South China. The specimen displays a flattened and wrinkled head shield, inverted overlap of the trunk tergites over the head shield, and duplication of exoskeletal elements including the posterior body margins and telson. We interpret this fossil as a discarded exoskeleton overlying the carcass of an emerging individual. The moulting behaviour of A. mirabilis evokes that of decapods, in which the carapace is separated posteriorly and rotated forward from the body, forming a wide gape for the emerging individual. A. mirabilis illuminates the moult strategy of stem-group Euarthropoda, offers the stratigraphically and phylogenetically earliest direct evidence of ecdysis within total-group Euarthropoda, and represents one of the oldest examples of this growth strategy in the evolution of Ecdysozoa.

Abstract The production of vertebrate retinal projection neurons, retinal ganglion cells (RGCs), is regulated by cell-intrinsic determinants and cell-to-cell signaling events. The basic-helix-loop-helix (bHLH) protein Atoh7 is a key neurogenic transcription factor required for RGC development. Here, we investigate whether manipulating human ATOH7 expression among uncommitted progenitors can promote RGC fate specification and thus be used as a strategy to enhance RGC genesis. Using the chicken retina as a model, we show that cell autonomous expression of ATOH7 is sufficient to induce precocious RGC formation and expansion of the neurogenic territory. ATOH7 overexpression among neurogenic progenitors significantly enhances RGC production at the expense of reducing the progenitor pool. Furthermore, forced expression of ATOH7 leads to a minor increase of cone photoreceptors. We provide evidence that elevating ATOH7 levels accelerates cell cycle progression from S to M phase and promotes cell cycle exit. We also show that ATOH7-induced ectopic RGCs often exhibit aberrant axonal projection patterns and are correlated with increased cell death during the period of retinotectal connections. These results demonstrate the high potency of human ATOH7 in promoting early retinogenesis and specifying the RGC differentiation program, thus providing insight for manipulating RGC production from stem cell-derived retinal organoids.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Abstract Door-to-needle time (DNT) is a key performance indicator for efficient use of intravenous thrombolysis in acute ischemic stroke (AIS). We aimed to determine whether DNT improved over time in the Enhanced Control of Hypertension and Acute Stroke Study (ENCHANTED) and the clinical predictors of DNT. Temporal trends in DNT were assessed across fourths of time since activation of study centers using generalized linear model. Predictors of long DNT (>60 min) were determined in logistic regression models. Overall mean DNT (min) was 71.8 (95% confidence interval [CI] 70.4–73.2), but decreased significantly over time (fourths): 77.9 (74.9–80.9), 69.3 (66.7–72.0), 69.1 (66.5–71.8) and 71.4 (68.7–74.2) (P for trend, 0.003). The reduction in DNT was particularly marked in China (P for trend, 0.001), but was not significant across the other participating countries (P for trend, 0.065). Independent predictors of long DNT were recruitment from China, short onset-to-door time, lower numbers of patients treated per center, higher diastolic blood pressure, off-hour admission, and absence of proximal clot occlusion. DNT in ENCHANTED declined progressively during the trial, especially in China. However, DNT in China is still longer than the key performance parameter of ≤60 minutes recommended in guidelines. Effective national programs are needed to improve DNT in China.