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Abstract As the primary variable load of bridges, vehicle load is an important parameter for bridge health monitoring. However, traditional Weigh-in-Motion (WIM) systems and the commonly used method of placing sensors on the bridge are challenging to apply in load monitoring for many small and medium-sized bridges. Therefore, this paper proposes a bridge vehicle load identification method based on traffic surveillance video data. Leveraging the surveillance video data on the bridge, without introducing additional hardware devices, the displacement of target points is detected through sub-pixel level image detection algorithms, enabling non-contact measurement of bridge structural response through imaging. A spatiotemporal relationship model of structural displacement, vehicle load, and load distribution is established to solve for vehicle load. Finally, model bridge tests under various loading conditions and engineering practice experiments are conducted to validate the feasibility of the method. The results of the model bridge tests show that the structural displacement measured using traffic video measurement has a deviation of less than 10% compared to the measurements obtained using contact displacement sensors (LVDT), and it can accurately reflect the displacement characteristics of the structure. The results of the field tests demonstrate that the average estimation deviation for heavy vehicle loads ranging from 12 to 18 tons is approximately 18%, meeting the engineering requirements. The proposed method can provide load statistical information for the extensive health monitoring of small and medium-sized bridges and offer a new technical pathway for obtaining bridge load information.

Abstract Background Previous literature has explored the relationship between chronic atrophic gastritis (CAG) and isolated cancers within the upper gastrointestinal cancers; However, an integrative synthesis across the totality of upper gastrointestinal cancers was conspicuously absent. The research objective was to assess the relationship between CAG and the risk of incident upper gastrointestinal cancers, specifically including gastric cancer, oesophageal cancer, and oesophagogastric junction cancer. Methods Rigorous systematic searches were conducted across three major databases, namely PubMed, Embase and Web of Science, encompassing the timeline from database inception until August 10, 2023. We extracted the necessary odds ratio (OR) and their corresponding 95% confidence interval (CI) for subsequent meta-analysis. Statistical analyses were conducted using Stata 17.0 software. Results This meta-analysis included a total of 23 articles encompassing 5858 patients diagnosed with upper gastrointestinal cancers. CAG resulted in a statistically significant 4.12-fold elevated risk of incident gastric cancer (OR = 4.12, 95% CI 3.20–5.30). Likewise, CAG was linked to a 2.08-fold increased risk of incident oesophageal cancer (OR = 2.08, 95%CI 1.60–2.72). Intriguingly, a specific correlation was found between CAG and the risk of incident oesophageal squamous cell carcinoma (OR = 2.29, 95%CI 1.77–2.95), while no significant association was detected for oesophageal adenocarcinoma (OR = 0.62, 95%CI 0.17–2.26). Moreover, CAG was correlated with a 2.77-fold heightened risk of oesophagogastric junction cancer (OR = 2.77, 95%CI 2.21–3.46). Notably, for the same type of upper gastrointestinal cancer, it was observed that diagnosing CAG through histological methods was linked to a 33–77% higher risk of developing cancer compared to diagnosing CAG through serological methods. Conclusion This meta-analysis indicated a two- to fourfold increased risk of gastric cancer, oesophageal cancer, and oesophagogastric junction cancer in patients with CAG. Importantly, for the same upper gastrointestinal cancer, the risk of incident cancer was higher when CAG was diagnosed histologically compared to serological diagnosis. Further rigorous study designs are required to explore the impact of CAG diagnosed through both diagnostic methods on the risk of upper gastrointestinal cancers.

Introduction: Sodium zirconium cyclosilicate (SZC) is a nonabsorbed cation-exchanger approved in China for the treatment of hyperkalemia [HK; serum potassium (sK+) levels >5.0 mmol/L]. This is the first real-world study aimed to assess the effectiveness, safety, and treatment patterns of SZC in Chinese patients with HK. Here we present the results of the first interim analysis.Methods: This multicenter, prospective, cohort study included patients aged ≥18 years with documented HK within 1-year before study enrollment day. These patients were followed up for 6 months from the enrollment day after initiating SZC treatment. The treatment was categorized into correction phase (FAS-P1) and maintenance phase (FAS-P2 new and ongoing users). Subgroup analysis was performed in patients on hemodialysis (FAS-H). The primary objective was evaluation of safety profile of SZC; secondary objectives included assessment of treatment patterns of SZC and its effectiveness.Results: Of 421 screened patients, 193, 354, and 162 patients were enrolled in the FAS-P1, FAS-P2, and FAS-H groups, respectively. sK+ levels were reduced significantly from 5.9 mmol/L to 5.0 mmol/L after the correction phase. For the maintenance phase, the mean sK+ levels were maintained at 5.2 mmol/L and 5.0 mmol/L in the FAS-P2 new and ongoing user, respectively, and 5.3 mmol/L in the FAS-H subgroup. A considerable proportion of patients showed normokalemia after 48 h of SZC treatment (FAS-P1:51.3%) which was maintained up to 6 months in the maintenance phase (FAS-P2:44%). SZC was well-tolerated.Conclusion: SZC was effective and safe for the treatment of HK in real-world clinical practice in China.

Large-scale vegetation restoration can reduce local watershed water yield, limit vegetation establishment and subsequent growth, and influence regional ecosystem functions. Clipping management by reducing aboveground parts of grassland was gradually recommended and adopted in Grain-for-Green project management to offset these additional issues. Thus, scientific evaluation of the effectiveness of clipping management on infiltration and runoff processes is necessary for maintaining the stability of the surface water system and the sustainability of vegetation restoration in semi-arid regions. A field simulated rainfall experiment was conducted with four managed clipping grasslands (mainly bunge needlegrass and Stipa grandis), including no clipping, light clipping, heavy clipping, and complete clipping under three slope gradients (10, 20, and 30°) and three rainfall intensities (60, 90, and 120 mm/h) to explore the mechanism of runoff and infiltration responses to clipping using structural equation modeling and variation partitioning based on an SCS-CN model. The results showed the runoff coefficient of the light clipping, heavy clipping, and complete clipping plots were 1.33, 2.22, and 4.22 times that of the no clipping plot. The light clipping, heavy clipping, and complete clipping plots decreased the infiltration coefficients by 0%, 5%, and 26% relative to the no clipping plot. Rainfall intensity dominated runoff and infiltration amounts, and clipping intensity's total effect was stronger than slope gradient. Clipping intensity and slope gradient were more influential on runoff with increasing rainfall intensity. The mutual inhibition effect was between clipping intensity and slope gradient on runoff. In order to maintain the sustainability of restoration, a 25–50% vegetation coverage after clipping maximizes the benefits of increasing runoff and maintaining enough soil water supply that prevents possible soil drought. We propose that future vegetation restoration policies should evaluate the appropriate clipping intensity; meanwhile, local physiographic and climate conditions should be considered. These findings may offer guidance for the development of measures for runoff regulation and ecosystem functions of the watershed during vegetation restoration on the northern Loess Plateau.

Abstract Background Systemic lupus erythematosus (SLE) is a complex systemic autoimmune disease characterized by the presence of numerous autoantibodies. The interaction of infectious agents (viruses, bacteria and parasites) and a genetically susceptible host may be a key mechanism for SLE. Toxoplasma gondii is a widespread intracellular parasite that has been implicated in the pathogenesis of autoimmune diseases. However, the relationship between T. gondii infection and the increased risk of SLE in Chinese populations remains unclear. Methods The seroprevalence of T. gondii infection was assessed in 1771 serum samples collected from Chinese individuals (908 healthy controls and 863 SLE patients) from different regions of China using an enzyme-linked immunosorbent assay. Serum autoantibodies and clinical information were obtained and analysed. Results Our observations revealed a higher prevalence of anti-T. gondii antibodies (ATxA) immunoglobulin G (IgG) in serum samples from SLE patients (144/863, 16.7%) than in those from the healthy controls (53/917, 5.8%; P

Objectives To investigate the effectiveness of belimumab on active lupus nephritis (LN) and explore the predictors, including serological biomarkers, of renal response to belimumab in a real-world setting.Methods This multicentre, real-world observational study enrolled patients with active LN receiving intravenous belimumab as an add-on therapy with 24-hour urine protein≥1 g and estimated glomerular filtration rate≥30 mL/min/1.73 m2 at baseline. Complete renal response (CRR), partial renal response (PRR), no renal response (NRR) and primary efficacy renal response (PERR) were evaluated. Multivariable logistic regression was used to identify risk factors for NRR to belimumab at 6 months.Results Among the 122 patients enrolled, the proportions of patients achieving CRR, PRR, NRR and PERR were 35.9%, 17.1%, 47.0% and 44.4% at 6 months (n=117) and 55.6%, 19.4%, 26.4% and 58.3% at 12 months (n=72), respectively. Proteinuria, daily prednisone dosage and Systemic Lupus Erythematosus Disease Activity Index 2000 scores significantly decreased at 6 and 12 months (p

Objectives Systemic lupus erythematosus (SLE) is a highly heterogeneous disease, and B cell abnormalities play a central role in the pathogenesis of SLE. Long non-coding RNAs (lncRNAs) have also been implicated in the pathogenesis of SLE. The expression of lncRNAs is finely regulated and cell-type dependent, so we aimed to identify B cell-expressing lncRNAs as biomarkers for SLE, and to explore their ability to reflect the status of SLE critical pathway and disease activity.Methods Weighted gene coexpression network analysis (WGCNA) was used to cluster B cell-expressing genes of patients with SLE into different gene modules and relate them to clinical features. Based on the results of WGCNA, candidate lncRNA levels were further explored in public bulk and single-cell RNA-sequencing data. In another independent cohort, the levels of the candidate were detected by RT-qPCR and the correlation with disease activity was analysed.Results WGCNA analysis revealed one gene module significantly correlated with clinical features, which was enriched in type I interferon (IFN) pathway. Among non-coding genes in this module, lncRNA RP11-273G15.2 was differentially expressed in all five subsets of B cells from patients with SLE compared with healthy controls and other autoimmune diseases. RT-qPCR validated that RP11-273G15.2 was highly expressed in SLE B cells and positively correlated with IFN scores (r=0.7329, p

Abstract Background Various studies have indicated that stress hyperglycemia ratio (SHR) can reflect true acute hyperglycemic status and is associated with poor outcomes in patients with acute coronary syndrome (ACS). However, data on dialysis patients with ACS are limited. The Global Registry of Acute Coronary Events (GRACE) risk score is a well-validated risk prediction tool for ACS patients, yet it underestimates the risk of major events in patients receiving dialysis. This study aimed to evaluate the association between SHR and adverse cardiovascular events in dialysis patients with ACS and explore the potential incremental prognostic value of incorporating SHR into the GRACE risk score. Methods This study enrolled 714 dialysis patients with ACS from January 2015 to June 2021 at 30 tertiary medical centers in China. Patients were stratified into three groups based on the tertiles of SHR. The primary outcome was major adverse cardiovascular events (MACE), and the secondary outcomes were all-cause mortality and cardiovascular mortality. Results After a median follow-up of 20.9 months, 345 (48.3%) MACE and 280 (39.2%) all-cause mortality occurred, comprising 205 cases of cardiovascular death. When the highest SHR tertile was compared to the second SHR tertile, a significantly increased risk of MACE (adjusted hazard ratio, 1.92; 95% CI, 1.48–2.49), all-cause mortality (adjusted hazard ratio, 2.19; 95% CI, 1.64–2.93), and cardiovascular mortality (adjusted hazard ratio, 2.70; 95% CI, 1.90–3.83) was identified in the multivariable Cox regression model. A similar association was observed in both diabetic and nondiabetic patients. Further restricted cubic spline analysis identified a J-shaped association between the SHR and primary and secondary outcomes, with hazard ratios for MACE and mortality significantly increasing when SHR was > 1.08. Furthermore, adding SHR to the GRACE score led to a significant improvement in its predictive accuracy for MACE and mortality, as measured by the C-statistic, net reclassification improvement, and integrated discrimination improvement, especially for those with diabetes. Conclusions In dialysis patients with ACS, SHR was independently associated with increased risks of MACE and mortality. Furthermore, SHR may aid in improving the predictive efficiency of the GRACE score, especially for those with diabetes. These results indicated that SHR might be a valuable tool for risk stratification and management of dialysis patients with ACS.

Abstract Background The triglyceride-glucose (TyG) index has been suggested as a dependable indicator for predicting major adverse cardiovascular events (MACE) in individuals with cardiovascular conditions. Nevertheless, there is insufficient data on the predictive significance of the TyG index in end-stage renal disease (ESRD) patients with coronary artery disease (CAD). Methods This study, conducted at multiple centers in China, included 959 patients diagnosed with dialysis and CAD from January 2015 to June 2021. Based on the TyG index, the participants were categorized into three distinct groups. The study’s primary endpoint was the combination of MACE occurring within one year of follow-up, including death from any cause, non-fatal myocardial infarction, and non-fatal stroke. We assessed the association between the TyG index and MACE using Cox proportional hazard models and restricted cubic spline analysis. The TyG index value was evaluated for prediction incrementally using C-statistics, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results The three groups showed notable variations in the risk of MACE (16.3% in tertile 1, 23.5% in tertile 2, and 27.2% in tertile 3; log-rank P = 0.003). Following complete adjustment, patients with the highest TyG index exhibited a notably elevated risk of MACE in comparison to those in the lowest tertile (hazard ratio [HR] 1.63, 95% confidence interval [CI] 1.14–2.35, P = 0.007). Likewise, each unit increase in the TyG index correlated with a 1.37-fold higher risk of MACE (HR 1.37, 95% CI 1.13–1.66, P = 0.001). Restricted cubic spline analysis revealed a connection between the TyG index and MACE (P for nonlinearity > 0.05). Furthermore, incorporating the TyG index to the Global Registry of Acute Coronary Events risk score or baseline risk model with fully adjusted factors considerably enhanced the forecast of MACE, as demonstrated by the C-statistic, continuous NRI, and IDI. Conclusions The TyG index might serve as a valuable and dependable indicator of MACE risk in individuals with dialysis and CAD, indicating its potential significance in enhancing risk categorization in clinical settings.

Abstract Background The triglyceride–glucose (TyG) index is validated as a reliable biomarker of insulin resistance and an independent predictor of cardiovascular prognosis. However, the prognostic value of the TyG index in patients on dialysis with coronary artery disease (CAD) remained unexplored. This study aimed to determine the association between the TyG index and CAD severity and mortality in these patients. Methods A total of 1061 dialysis patients with CAD were enrolled in this multi-center cohort study from January 2015 to June 2021. The extent and severity of CAD were evaluated using the multivessel disease and Gensini score (GS). Patients were followed up for all-cause death and cardiovascular death. Results The multivariable logistic regression model indicated that the TyG index was significantly associated with multivessel disease (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.18–1.94, P = 0.001), and high GS (OR 1.33, 95% CI 1.10–1.61, P = 0.003). After adjusting for baseline risk factors, the hazards of all-cause death and cardiovascular death were 1.23 (95% CI 1.06–1.43, P = 0.007), and 1.33 (95% CI 1.11–1.59, P = 0.002), independent of CAD severity. Restricted cubic spline analysis identified a dose–response association between the TyG index and both CAD severity and mortality (all P for nonlinearity > 0.05). When modeling the TyG index as a categorical variable, these independent associations remained. Subgroup analyses did not substantially modify the results. Furthermore, incorporating the TyG index into the existing risk prediction model improved the predictive accuracy for all-cause death and cardiovascular death, as evaluated by C-statistic, continuous net reclassification improvement, and integrated discrimination improvement. Conclusions In patients on dialysis with CAD, the TyG index was significantly associated with more severe CAD as well as mortality. These results highlight the clinical importance of the TyG index for assessing CAD severity and risk stratification in patients on dialysis with CAD.

As a technology for water landscape performance that considers landscape, ecological, and social effects, nature-based solutions play a crucial role in enhancing the functionality of integrated ecosystem services on the micro-scale. This study conducted a systematic investigation into the landscape performance of the “Clear as a Drain” composite sponge facility at Handan Garden Expo Park. The following conclusions were drawn: (1) In terms of ecological restoration support services, the “Clear as a Drain” artificial wetland exhibited diverse habitat types, a rich variety of plant species specific to the site’s region, and high plant diversity indices for shrubs (1.776) and herbaceous aquatic plants (3.352). Reclaimed water reused in the artificial terraced wetland promoted plant growth and diversity while contributing to site self-rehabilitation; plants also significantly contributed to carbon fixation, oxygen release, and carbon emission reduction. (2) Regarding ecological restoration regulation services, the artificial wetland effectively purified reclaimed water with substantial improvements observed in incoming water quality during spring, summer, and autumn—particularly notable purification effects were observed during the summer months. Pollutant reduction rates for COD, BOD5 ammonia nitrogen, TP, and TN reached 75.8%, 72.1%, 93.8%, 96.7%, and 90.3%, respectively; different independent subsystems within the wetland demonstrated distinct advantages in pollutant removal; park plants displayed strong air purification capabilities; annual energy savings from park plants could fully cover daily energy consumption for nearby residents. This case could serve as guidance for scientific management and design parameter optimization of other composite sponge facilities.

BackgroundData with fine granularity about COVID-19-related outcomes and risk factors were still limited in the idiopathic inflammatory myopathies (IIMs) population. This study aimed to investigate clinical factors associated with hospitalized and severe COVID-19 in patients with IIMs, particularly those gauged by myositis-specific antibodies.MethodsThis retrospective cohort study was conducted in the Renji IIM cohort in Shanghai, China, under an upsurge of SARS-CoV-2 omicron variant infections from December 2022 to January 2023. Clinical data were collected and analyzed by multivariable logistic regression to determine risk factors. High-dimensional flow cytometry analysis was performed to outline the immunological features.ResultsAmong 463 infected patients in the eligible cohort (n=613), 65 (14.0%) were hospitalized, 19 (4.1%) suffered severe COVID-19, and 10 (2.2%) died. Older age (OR=1.59/decade, 95% CI 1.18 to 2.16, p=0.003), requiring family oxygen supplement (2.62, 1.11 to 6.19, 0.028), patients with anti-synthetase syndrome (ASyS) (2.88, 1.12 to 7.34, 0.027, vs. other dermatomyositis), higher IIM disease activity, and prednisone intake >10mg/day (5.59, 2.70 to 11.57,

The morbidity and mortality rates in lung cancer are high worldwide. Early diagnosis and personalized treatment are important to manage this public health issue. In recent years, artificial intelligence (AI) has played increasingly important roles in early screening, auxiliary diagnosis, and prognostic assessment. AI uses algorithms to extract quantitative feature information from high-volume and high-latitude data and learn existing data to predict disease outcomes. In this review, we describe the current uses of AI in lung cancer-focused pathomics, imageomics, and genomics applications.

Abstract Metabolic fingerprints in serum characterize diverse diseases for diagnostics and biomarker discovery. The identification of systemic lupus erythematosus (SLE) by serum metabolic fingerprints (SMFs) will facilitate precision medicine in SLE in an early and designed manner. Here, a discovery cohort of 731 individuals including 357 SLE patients and 374 healthy controls (HCs), and a validation cohort of 184 individuals (SLE/HC, 91/93) are constructed. Each SMF is directly recorded by nano‐assisted laser desorption/ionization mass spectrometry (LDI MS) within 1 minute using 1 µL of native serum, which contains 908 mass to charge features. Sparse learning of SMFs achieves the SLE identification with sensitivity/specificity and area‐under‐the‐curve (AUC) up to 86.0%/92.0% and 0.950 for the discovery cohort. For the independent validation cohort, it exhibits no performance loss by affording the sensitivity/specificity and AUC of 89.0%/100.0% and 0.992. Notably, a metabolic biomarker panel is screened out from the SMFs, demonstrating the unique metabolic pattern of SLE patients different from both HCs and rheumatoid arthritis patients. In conclusion, SMFs characterize SLE by revealing its unique metabolic pattern. Different regulation of small molecule metabolites contributes to the precise diagnosis of autoimmune disease and further exploration of the pathogenic mechanisms.

Mesenchymal stem cells (MSCs) influence T cells in health, disease and therapy through messengers of intercellular communication including extracellular vesicles (EVs). Apoptosis is a mode of cell death that tends to promote immune tolerance, and a large number of apoptotic vesicles (apoVs) are generated from MSCs during apoptosis. In an effort to characterize these apoVs and explore their immunomodulatory potential, here we show that after replenishing them systemically, the apoV deficiency in Fas mutant mice and pathological lymphoproliferation were rescued, leading to the amelioration of inflammation and lupus activity. ApoVs directly interacted with CD4+ T cells and inhibited CD25 expression and IL-2 production in a dose-dependent manner. A broad range of Th1/2/17 subsets and cytokines including IFNγ, IL17A and IL-10 were suppressed while Foxp3+ cells were maintained. Mechanistically, exposed phosphatidylserine (PtdSer/PS) on apoVs mediated the interaction with T cells to disrupt proximal T cell receptor signaling transduction. Remarkably, administration of apoVs prevented Th17 differentiation and memory formation, and ameliorated inflammation and joint erosion in murine arthritis. Collectively, our findings unveil a previously unrecognized crosstalk between MSC apoVs and CD4+ T cells and suggest a promising therapeutic use of apoVs for autoimmune diseases.

Investigating the spatial distribution characteristics of the interaction between soil salinity and moisture is crucial in revealing moisture–salinity interaction in semi-arid farmland. The sampling of soil was performed on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after the erosive rainfall. The multifractal method was used to analyze spatial distribution parameters of soil moisture and salinity under the different stages. The findings showed that the soil moisture content decreased from 22.44% to 12.73%, while the salinity increased from 0.71 to 1.18 g kg–1 after the rainfall. As the amount of moisture in the soil decreased, the variability in the distribution of moisture initially increased from S1 to S3 and then decreased, while the salinity content also decreased. The spatial distribution of soil moisture and salinity content showed a strong correlation at S3 to S4 (with the relative water content of soil ranging from 0.52 to 0.75), indicating a significant coupling effect in these stages. However, the distribution of soil salinity was not uniform under high moisture content conditions (S1 to S2), as it was leached unevenly by rainfall, and under low moisture content conditions (S5), it precipitated, resulting in a low correlation between the spatial distribution of soil moisture and salinity content. This research has provided insight into the coupling dynamics of soil moisture and salinity content, revealing the mechanisms governing their spatial distribution in dryland agricultural regions.

Abstract Objective This study aimed to explore the association between the triglyceride glucose index (TyG) and the risk of in-hospital and one-year mortality in patients with chronic kidney disease (CKD) and cardiovascular disease (CAD) admitted to the intensive care unit (ICU). Methods The data for the study were taken from the Medical Information Mart for Intensive Care-IV database which contained over 50,000 ICU admissions from 2008 to 2019. The Boruta algorithm was used for feature selection. The study used univariable and multivariable logistic regression analysis, Cox regression analysis, and 3-knotted multivariate restricted cubic spline regression to evaluate the association between the TyG index and mortality risk. Results After applying inclusion and exclusion criteria, 639 CKD patients with CAD were included in the study with a median TyG index of 9.1 [8.6,9.5]. The TyG index was nonlinearly associated with in-hospital and one-year mortality risk in populations within the specified range. Conclusion This study shows that TyG is a predictor of one-year mortality and in-hospital mortality in ICU patients with CAD and CKD and inform the development of new interventions to improve outcomes. In the high-risk group, TyG might be a valuable tool for risk categorization and management. Further research is required to confirm these results and identify the mechanisms behind the link between TyG and mortality in CAD and CKD patients.

Background/Aims Although the conversion from tacrolimus (TAC) to cytotoxic T-lymphocyte-associated antigen 4-immunoglobulin (CTLA4-Ig) is effective in reducing TAC-induced nephrotoxicity, it remains unclear whether CTLA4-Ig has a direct effect on TAC-induced renal injury. In this study, we evaluated the effects of CTLA4-Ig on TAC-induced renal injury in terms of oxidative stress. Methods in vitro study was performed to assess the effect of CTLA4-Ig on TAC-induced cell death, reactive oxygen species (ROS), apoptosis, and the protein kinase B (AKT)/forkhead transcription factor (FOXO) 3 pathway in human kidney 2 cells. In the in vivo study, the effect of CTLA4-Ig on TAC-induced renal injury was evaluated using renal function, histopathology, markers of oxidative stress (8-hydroxy-2’-deoxyguanosine) and metabolites (4-hydroxy-2-hexenal, catalase, glutathione S-transferase, and glutathione reductase), and activation of the AKT/FOXO3 pathway with insulin-like growth factor 1 (IGF-1). Results CTLA4-Ig significantly decreased cell death, ROS, and apoptosis caused by TAC. TAC treatment increased apoptotic cell death and apoptosis-related proteins (increased Bcl-2-associated X protein and caspase-3 and decreased Bcl-2), but it was reversed by CTLA4-Ig treatment. The activation of p-AKT and p-FOXO3 by TAC decreased with CTLA4-Ig treatment. TAC-induced renal dysfunction and oxidative marker levels were significantly improved by CTLA4-Ig in vivo. Concomitant IGF-1 treatment abolished the effects of CTLA4-Ig. Conclusions CTLA4-Ig has a direct protective effect on TAC-induced renal injury via the inhibition of AKT/FOXO3 pathway.

Abstract Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.

Background: The no-/slow-reflow phenomenon following primary percutaneous coronary intervention (PCI) in patients with ST-elevation myocardial infarction (STEMI)is associated with poor prognosis. The early identification of high-risk patients with no-/slow-reflow is critical. This study aimed to evaluate the predictive ability of the Canada Acute Coronary Syndrome (C-ACS) risk score for no-/slow-reflow in these patients. Methods: Patients with STEMI who underwent primary PCI were consecutively enrolled and divided into three groups based on their C-ACS scores: 0, 1, and ≥2. The C-ACS score was computed using the four clinical variables evaluated at admission (one point for each): age ≥75 years, heart rate >100 beats/min, systolic blood pressure 1. No-/slow-reflow was defined as thrombolysis in a myocardial infarction flow grade of 0–2 after primary PCI. The predictive ability of the C-ACS score for no-/slow-reflow was evaluated using a receiver operating characteristic curve. Results: A total of 834 patients were enrolled, of whom 109 (13.1 %) developed no-/slow-reflow. The incidence of no-/slow-reflow increased from the C-ACS 0 group to the C-ACS ≥2 group (6.1 % vs 17.7 % vs 34.3 %, respectively, p

Self-improving collodion ichthyosis (SICI) is a relatively rare subtype of autosomal recessive congenital ichthyosis (ARCI) that is often characterized by a collodion baby (CB) phenotype at birth. A newborn girl, just 1 hour old, presented with taut, shiny, thick yellow crusts, like parchment, and scales on her trunk and upper limbs. The tightening effect had caused both upper eyelids to appear everted, and her lips and auricles were deformed. Based on whole-exome sequencing and examination of the clinical phenotype, the patient was diagnosed with ARCI. After admission, the exposed mucosa was covered with a sterile Vaseline gauze dressing, and she was placed in an incubator set to a temperature of 32°C with a humidity level of 75%. One week later, the parchment-like scales had begun to flake off, and at the age of 3 weeks, all bodily skin appeared normal. SICI was diagnosed. After discharge, the patient was followed up to 3 months of age, at which time her growth and development were comparable to those of her peers. Clinicians should consider SICI as a possible diagnosis when analyzing the prognosis of patients with CB. Reducing water loss and maintaining the electrolyte balance are particularly important for SICI treatment.

Abstract Objective Chronic kidney disease (CKD) patients with coronary artery disease (CAD) in the intensive care unit (ICU) have higher in-hospital mortality and poorer prognosis than patients with either single condition. The objective of this study is to develop a novel model that can predict the in-hospital mortality of that kind of patient in the ICU using machine learning methods. Methods Data of CKD patients with CAD were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Boruta algorithm was conducted for the feature selection process. Eight machine learning algorithms, such as logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were conducted to construct the predictive model for in-hospital mortality and performance was evaluated by average precision (AP) and area under the receiver operating characteristic curve (AUC). Shapley Additive Explanations (SHAP) algorithm was applied to explain the model visually. Moreover, data from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) were acquired as an external validation set. Results 3590 and 1657 CKD patients with CAD were acquired from MIMIC-IV and eICU-CRD databases, respectively. A total of 78 variables were selected for the machine learning model development process. Comparatively, GBDT had the highest predictive performance according to the results of AUC (0.946) and AP (0.778). The SHAP method reveals the top 20 factors based on the importance ranking. In addition, GBDT had good predictive value and a certain degree of clinical value in the external validation according to the AUC (0.865), AP (0.672), decision curve analysis, and calibration curve. Conclusion Machine learning algorithms, especially GBDT, can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. This contributed to providing optimal resource allocation and reducing in-hospital mortality by tailoring precise management and implementation of early interventions.

ABSTRACTIndoor positioning with high accuracy plays an important role in different application scenarios. As a widely used mobile communication signal, the Long-Term Evolution (LTE) network can be well received in indoor and outdoor environments. This article studies a method of using different reference signals in the LTE downlink for carrier phase time of arrival (TOA) estimation. Specifically, a solution is proposed and a multipath tracking Software Defined Receiver (SDR) is developed for indoor positioning. With our SDR indoor positioning system, the pilot signals of the LTE signals are firstly obtained by the coarse synchronization and demodulation. Then, with the assistance of the pilot signals, the time delay acquisition, the multipath estimating delay lock loop (MEDLL) algorithm, and the multipath anomaly detection are sequentially carried out to obtain navigation observations of received signals. Furthermore, to compare the performance of different pilot signals, the Secondary Synchronous Signals (SSS) and Cell Reference Signals (CRS) are used as pilot signals for carrier phase-based TOA estimation, respectively. Finally, to quantify the accuracy of our multipath tracking SDR, indoor field tests are carried out in a conference environment, where an LTE base station is installed for commercial use. Our test results based on CRS show that, in the static test scenarios, the TOA accuracy measured by the 1-σ error interval is about 0.5 m, while in the mobile environment, the probability of range accuracy within 1.0 m is 95%.

To identify the key parameters and develop accurate experimental models of detachment and transport, splash detachment and transport of loess soil were investigated in relation to the rainfall characteristics and slope. The experiment was conducted under 25 combinations of five rainfall intensities (60, 84, 108, 132 and 156 mm h−1) and five slope gradients (0°, 5°, 10°, 15° and 20°), using a custom splash pan. Raindrop characteristics (diameter, velocity and kinetics) and splash mass were measured in downslope and upslope. The results indicated that rainfall intensity and slope contributed 94.77% and 0.46%, respectively, to the detachment rate, and 24.39% and 67.82%, respectively, to the transport rate. From a holistic viewpoint, the positive effect of slope became more visible on the detachment rate when the rainfall intensity exceeded 108 mm h−1, and on the transport rate when the slope exceeded 15°. Based on the rainfall simulator in this study, the rainfall kinetic energy (KE, J), raindrop median particle size (D50, mm) and raindrop terminal velocity (V, m s−1) all increased with increasing rainfall intensity (I) within the 60~108 mm h−1 range but decreased with increasing rainfall intensity within the 132~156 mm h−1 range. The rainfall intensity and raindrop characteristics (D50/V/KE) are the key parameters of splash detachment (Dr, g·m−2 min−1), and three detachment models were developed: (1) Dr = 0.1153 I1.09D500.79 (R2 = 0.99, NSE = 0.98, p < 0.01); (2) Dr = 0.0162 I1.11V1.22 (R2 = 0.99, NSE = 0.99, p < 0.01); and (3) Dr = 0.0813 I1.10KE0.18 (R2 = 0.99, NSE = 0.99, p < 0.01). The rainfall intensity and slope are the key parameters for splash transport (Tr, g·m−2 min−1), and the developed transport models could be expressed as: (1) Tr = 0.00657 I1.343S0.116 (R2 = 0.914, NSE = 0.874, p < 0.01) (slopes of 0°, 5° and 10°) and (2) Tr = 0.00218 I1.165S1.033 (R2 = 0.986, NSE = 0.986, p < 0.01) (slopes of 15° and 20°). The results of this study could enhance the understanding of soil splash detachment and transport on loess slopes.

Abstract Systemic lupus erythematosus (SLE) is a complex autoimmune disease with abnormal activation of the immune system. Recent attention is increasing about how aberrant lipid and cholesterol metabolism is linked together with type I interferon (IFN‐I) signaling in the regulation of the pathogenesis of SLE. Here, a metabonomic analysis is performed and increased plasma concentrations of oxysterols, especially 7α, 25‐dihydroxycholesterol (7α, 25‐OHC), are identified in SLE patients. The authors find that 7α, 25‐OHC binding to its receptor Epstein–Barr virus‐induced gene 2 (EBI2) in macrophages can suppress STAT activation and the production of IFN‐β, chemokines, and cytokines. Importantly, monocytes/macrophages from SLE patients and mice show significantly reduced EBI2 expression, which can be triggered by IFN‐γ produced in activated T cells. Previous findings suggest that EBI2 enhances immune cell migration. Opposite to this effect, the authors demonstrate that EBI2‐deficient macrophages produce higher levels of chemokines and cytokines, which recruits and activates myeloid cells,T and B lymphocytes to exacerbate tetramethylpentadecane‐induced SLE. Together, via sensing the oxysterol 7α, 25‐OHC, EBI2 in macrophages can modulate innate and adaptive immune responses, which may be used as a potential diagnostic marker and therapeutic target for SLE.

ObjectiveThere is an urgent need for novel biomarkers in lupus nephritis (LN). We report a non-invasive urinary biomarker, L-selectin, in two independent multi-ethnic cohorts.MethodsuL-selectin was tested cross-sectionally in a Chinese cohort (n=255) and a US cohort (n=219) of SLE patients and controls using ELISA. A longitudinal cohort includes 20 active Chinese LN patients.ResultsuL-selectin was significantly increased in active LN patients compared to active non-renal SLE, inactive LN, inactive non-renal SLE, chronic kidney disease patients, and healthy controls. uL-selectin positively correlated with global and renal disease activities and was significantly associated with histological activity index and chronicity index (CI). Low uL-selectin was an independent predictor for high CI. During follow-up, uL-selectin levels decreased significantly in the complete renal remission group.ConclusionuL-selectin is a novel biomarker of disease activity and renal histopathology in LN across multiple ethnicities. It also reflects treatment response in LN patients during follow up.

Anti-melanoma differentiation-associated gene 5-positive dermatomyositis is a severe autoimmune disease with largely unknown aetiology. Here authors identify the key immune cell types that contribute to the disease phenotype and implicate type I interferons signalling in the patho-mechanism.

Objectives: Infectious diseases are common but are not easily or readily diagnosed with current methodologies. This problem is further exacerbated by the constant presence of mutated, emerging, and novel pathogens. One of the most common sites of infection by many pathogens is the human throat. However, there is no universal diagnostic test that can distinguish these pathogens. Metatranscriptomic (MT) analysis of the throat represents an important and novel development in infectious disease detection and characterization, because it is able to identify all pathogens using a fully unbiased approach. Methods: To test the utility of an MT approach to pathogen detection, throat samples were collected from participants before, during, and after an acute sickness. Results: Clear sickness-associated shifts in pathogenic microorganisms were detected in the patients. Important insights into microbial functions and antimicrobial resistance genes were obtained. Conclusion: MT analysis of the throat represents an effective method for the unbiased identification and characterization of pathogens. Because MT data include all microorganisms in the sample, this approach should not only allow the identification of pathogens, but provide an understanding of the effects of the resident throat microbiome in the context of human health and disease.

Supercapacitors have attracted tremendous attention due to their merits of excellent cycling stability, remarkable power density and low cost. Nevertheless, the low energy density of supercapacitors has encumbered their further development for practical applications. Development of advanced high-energy supercapacitors is considered to be of crucial importance. In this work, the capacitance of MOF-derived carbon-based supercapacitor is dramatically improved by addition of soluble redox-active LiBr electrolyte additive. The post analysis of this redox-active electrolytes reveal that the Br−/Br2 couple are the main pseudocapacitance contribution in the early cycles stages (

Objectives A 24-hour urine protein (24hUP) is a key measurement in the management of lupus nephritis (LN); however, trajectories of 24hUP in LN is poorly defined.Methods Two LN cohorts that underwent renal biopsies at Renji Hospital were included. Patients received standard of care in a real-world setting and 24hUP data were collected over time. Trajectory patterns of 24hUP were determined using the latent class mixed modelling (LCMM). Baseline characters were compared among trajectories and multinomial logistic regression was used to determine independent risk factors. Optimal combinations of variables were identified for model construction and user-friendly nomograms were developed.Results The derivation cohort composed of 194 patients with LN with 1479 study visits and a median follow-up of 17.5 (12.2–21.7) months. Four trajectories of 24hUP were identified, that is, Rapid Responders, Good Responders, Suboptimal Responders and Non-Responders, with the KDIGO renal complete remission rates (time to complete remission, months) of 84.2% (4.19), 79.6% (7.94), 40.4% (not applicable) and 9.8% (not applicable), respectively (p0.85. Another nomogram to predict ‘Good Responders’ yielded C-indices of 0.73~0.78, which composed of gender, new-onset LN, glomerulosclerosis and partial remission within 6 months. When applied to the validation cohort with 117 patients and 500 study visits, nomograms effectively sorted out ‘Rapid Responders’ and ‘Good Responders’.Conclusion Four trajectories of LN shed some light to guide the management of LN and further clinical trials design.

The current expansion of building structures has created a demand for efficient and smart surface quality evaluation at the acceptance phase. However, the conventional approach mainly relies on manual work, which is labor-intensive, time-consuming, and unrepeatable. This study presents a systematic and practical solution for surface quality evaluation of indoor building elements during the acceptance phase using point cloud. The practical indoor scanning parameters determination procedure was proposed by analyzing the project requirements, room environment, and apparatus. An improved DBSCAN algorithm was developed by introducing a plane validation and coplanar checking to facilitate the surface segmentation from the point cloud. And a revised Least Median of Square-based algorithm was proposed to identify the best-fit plane. Afterwards, the flatness, verticality, and squareness were evaluated and depicted using a color-coded map based on the segmented point cloud. The experiment on an apartment showcases how the system improves the information flow and accuracy during building acceptance, resulting in a potentially smart acceptance activity.

Introduction: Mushroom-forming fungi comprise diverse species that develop complex multicellular structures. In cultivated species, both ecological adaptation and artificial selection have driven genome evolution. However, little is known about the connections among genotype, phenotype and adaptation in mushroom-forming fungi. Objectives: This study aimed to (1) uncover the population structure and demographic history of Lentinula edodes, (2) dissect the genetic basis of adaptive evolution in L. edodes, and (3) determine if genes related to fruiting body development are involved in adaptive evolution. Methods: We analyzed genomes and fruiting body-related traits (FBRTs) in 133 L. edodes strains and conducted RNA-seq analysis of fruiting body development in the YS69 strain. Combined methods of genomic scan for divergence, genome-wide association studies (GWAS), and RNA-seq were used to dissect the genetic basis of adaptive evolution. Results: We detected three distinct subgroups of L. edodes via single nucleotide polymorphisms, which showed robust phenotypic and temperature response differentiation and correlation with geographical distribution. Demographic history inference suggests that the subgroups diverged 36,871 generations ago. Moreover, L. edodes cultivars in China may have originated from the vicinity of Northeast China. A total of 942 genes were found to be related to genetic divergence by genomic scan, and 719 genes were identified to be candidates underlying FBRTs by GWAS. Integrating results of genomic scan and GWAS, 80 genes were detected to be related to phenotypic differentiation. A total of 364 genes related to fruiting body development were involved in genetic divergence and phenotypic differentiation. Conclusion: Adaptation to the local environment, especially temperature, triggered genetic divergence and phenotypic differentiation of L. edodes. A general model for genetic divergence and phenotypic differentiation during adaptive evolution in L. edodes, which involves in signal perception and transduction, transcriptional regulation, and fruiting body morphogenesis, was also integrated here.

The functional effects of genetic loci associated with autoimmune disease are not well understood. By dissecting an autoimmune disease genetic locus, the authors define an immune cell-type-specific enhancer and the molecular mechanisms underlying the dysregulation of IRF8 expression by lupus risk variants.

IntroductionPost-stroke depression (PSD) is the most common emotional problem following a stroke, which requires early diagnosis to improve the prognosis. Gut microbiota plays important role in the pathological mechanisms of acute ischemic stroke and influences the outcome of patients. However, the relationship between PSD and gut microbiota remains unknown. Here, we explored whether the microbial signatures of gut microbiota in the patients with stroke could be an appropriate predictor of PSD.MethodsFecal samples were collected from 232 acute ischemic stroke patients and determined by 16s rRNA sequencing. All patients then received 17-Hamilton Depression Rating Scale (HAMD-17) assessment 3 months after discharge, and were further divided into PSD group and non-PSD group. We analyzed the differences of gut microbiota between these groups. To identify gut microbial biomarkers, we then established microbial biomarker model.ResultsOur results showed that the composition of gut microbiota in the PSD patients differed significantly from that in non-PSD patients. The genus Streptococcus, Akkermansia, and Barnesiella were significantly increased in PSD patients compared to non-PSD, while the genus Escherichia-Shigella, Butyricicoccus, and Holdemanella were significantly decreased. Correlation analyses displayed that Akkermansia, Barnesiella, and Pyramidobacter were positively correlated with HAMD score, while Holdemanella was negatively correlated with HAMD score. The optimal microbial markers were determined, and the combination achieved an area under the curve (AUC) value of 0.705 to distinguish PSD from non-PSD.ConclusionsOur findings suggest that PSD patients had distinct gut microbiota compared to non-PSD patients, and explore the potential of microbial markers, which might provide clinical decision-making in PSD.

Introduction Hyperkalaemia (HK) is a potentially life-threatening electrolyte imbalance associated with several adverse clinical outcomes. The efficacy and negative effects of currently existing treatment options have made HK management questionable. Sodium zirconium cyclosilicate (SZC), a novel highly selective potassium binder, is approved for the treatment of HK. The present study will be aimed to assess the safety, effectiveness and treatment patterns of SZC in Chinese patients with HK in a real-world clinical setting as it is required by China’s drug review and approval process.Methods and analysis This is a multicentre, prospective cohort study which plans to enrol 1000 patients taking SZC or willing to take SZC from approximately 40 sites in China. Patients ≥18 years of age at the time of signing the written informed consent and with documented serum potassium levels ≥5.0 mmol/L within 1 year before study enrolment day will be included. Eligible patients will receive SZC treatment and will be followed up for 6 months from enrolment day. The primary objective will be to evaluate the safety of SZC for the management of HK in Chinese patients in terms of adverse events (AEs), serious AEs as well as discontinuation of SZC. The secondary objectives will include understanding the SZC dosage information in terms of its effectiveness and treatment patterns under real-world clinical practice and assessing effectiveness of SZC during the observational period.Ethics and dissemination This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (approval number: YJ-JG-YW-2020). All the participating sites have received the ethics approval. Results will be disseminated through national and international presentations and peer-reviewed publications.Trial registration number NCT05271266.

IntroductionPathologic inflammation is a major driver of kidney damage in lupus nephritis (LN), but the immune mechanisms of disease progression and risk factors for end organ damage are poorly understood.MethodsTo characterize molecular profiles through the development of LN, we carried out gene expression analysis of microdissected kidneys from lupus-prone NZM2328 mice. We examined male mice and the congenic NZM2328.R27 strain as a means to define mechanisms associated with resistance to chronic nephritis. Gene expression profiles in lupus mice were compared with those in human LN.ResultsNZM2328 mice exhibited progress from acute to transitional and then to chronic glomerulonephritis (GN). Each stage manifested a unique molecular profile. Neither male mice nor R27 mice progressed past the acute GN stage, with the former exhibiting minimal immune infiltration and the latter enrichment of immunoregulatory gene signatures in conjunction with robust kidney tubule cell profiles indicative of resistance to cellular damage. The gene expression profiles of human LN were similar to those noted in the NZM2328 mouse suggesting comparable stages of LN progression.ConclusionsOverall, this work provides a comprehensive examination of the immune processes involved in progression of murine LN and thus contributes to our understanding of the risk factors for end-stage renal disease. In addition, this work presents a foundation for improved classification of LN and illustrates the applicability of murine models to identify the stages of human disease.

A defining feature of successful vaccination is the ability to induce long-lived antigen-specific memory cells. T follicular helper (Tfh) cells specialize in providing help to B cells in mounting protective humoral immunity in infection and after vaccination. Memory Tfh cells that retain the CXCR5 expression can confer protection through enhancing humoral response upon antigen re-exposure but how they are maintained is poorly understood. CXCR5+ memory Tfh cells in human blood are divided into Tfh1, Tfh2, and Tfh17 cells by the expression of chemokine receptors CXCR3 and CCR6 associated with Th1 and Th17, respectively. Here, we developed a new method to induce Tfh1, Tfh2, and Tfh17-like (iTfh1, iTfh2, and iTfh17) mouse cells in vitro. Although all three iTfh subsets efficiently support antibody responses in recipient mice with immediate immunization, iTfh17 cells are superior to iTfh1 and iTfh2 cells in supporting antibody response to a later immunization after extended resting in vivo to mimic memory maintenance. Notably, the counterpart human Tfh17 cells are selectively enriched in CCR7+ central memory Tfh cells with survival and proliferative advantages. Furthermore, the analysis of multiple human cohorts that received different vaccines for HBV, influenza virus, tetanus toxin or measles revealed that vaccine-specific Tfh17 cells outcompete Tfh1 or Tfh2 cells for the persistence in memory phase. Therefore, the complementary mouse and human results showing the advantage of Tfh17 cells in maintenance and memory function supports the notion that Tfh17-induced immunization might be preferable in vaccine development to confer long-term protection.

Abstract Objective There is an urgent need to identify novel biomarkers of LN to reflect renal histological changes. This study aims to investigate urinary G3BP levels in LN patients and their association with renal disease activity both clinically and pathologically. Methods This is a cross-sectional study. A total of 119 lupus nephritis patients were recruited. Thirty patients with chronic kidney diseases (CKD) and 27 healthy volunteers were also recruited as controls. Urinary G3BP was tested by ELISA. Renal histopathology was reviewed by an experienced renal pathologist. Other clinical variables were collected through chart review. Results The levels of uG3BP were significantly increased in active LN patients compared to those in inactive LN (p 3.0 g/24h, uG3BP levels were higher in proliferative LN than in membranous LN (p=0.04). They could discriminate the two pathogenic types of LN (AUC=0.72), and they also positively correlated with AI (ρ=0.389, p=0.008) and scores of hyaline deposits (ρ=0.418, p=0.006). While in patients with 24-h urine protein ≤ 3.0 g/24h, uG3BP levels were not significantly different between proliferative and membranous LN, and there was no apparent relationship between uG3BP levels with AI or with scores of hyaline deposits, but they correlated positively with scores of cellular/fibrocellular crescents (ρ=0.328, p=0.04). Conclusion uG3BP is a non-invasive biomarker for clinically and histologically reflecting disease activity. It is associated with active histological changes and can be used as a surrogate biomarker when the renal biopsy is impractical.

Exposure to Bisphenol A (BPA) has led to an increased risk of obesity and nonalcoholic fatty liver diseases (NAFLDs). However, it is as yet unclear if the damage caused by BPA is able to be repaired sufficiently after exposure has ceased. Therefore, this project aims to investigate the effects of BPA on the hepatic lipid metabolism function and its potential mechanisms in mice by comparing the BPA exposure model and the BPA exposure + cessation of drug treatment model. Herein, the male C57BL/6 mice were exposed in the dose of 50 μg/kg/day and 500 μg/kg/day BPA for 8 weeks, and then transferred to a standard chow diet for another 8 weeks to recover. Based on our previous RNA-seq study, we examined the expression patterns of some key genes. The results showed that the mice exposed to BPA manifested NAFLD features. Importantly, we also found that there was a significant expression reversion for SCD1, APOD, ANGPT4, PPARβ, LPL and G0S2 between the exposure and recovery groups, especially for SCD1 and APOD (p < 0.01). Notably, BPA could significantly decrease the level of APOD protein (p < 0.01) whereas there was an extremely significant increase after the exposure ceased. Meanwhile, APOD over-expression suppressed TG accumulation in the AML12 cells. In conclusion, the damage caused by BPA is able to be repaired by the upregulation of APOD and exposure to BPA should be carefully examined in chronic liver metabolic disorders or diseases.

Low Earth Orbit (LEO) satellite navigation signal can be used as an opportunity signal in the case of a Global Navigation Satellite System (GNSS) outage, or as an enhancement by means of traditional GNSS positioning algorithms. No matter which service mode is used, signal acquisition is a prerequisite for providing enhanced LEO navigation services. Compared with the medium orbit satellite, the transit time of the LEO satellite is shorter. Thus, it is of great significance to expand the successful acquisition time range of the LEO signal. Previous studies on LEO signal acquisition are based on simulation data. However, signal acquisition research based on real data is crucial. In this work, the signal characteristics of LEO satellites: power space density in free space and the Doppler shift of LEO satellites are individually studied. The unified symbolic definitions of several integration algorithms based on the parallel search signal acquisition algorithm are given. To verify these algorithms for LEO signal acquisition, a Software Defined Receiver (SDR) is developed. The performance of these integration algorithms on expanding the successful acquisition time range is verified by the real data collected from the Luojia-1A satellite. The experimental results show that the integration strategy can expand the successful acquisition time range, and it will not expand indefinitely with the integration duration. The performance of the coherent integration and differential integration algorithms is better than the other two integration algorithms, so the two algorithms are recommended for LEO signal acquisition and a 20 ms integration duration is preferred. The detection threshold of 2.5 is not suitable for all integration algorithms and various integration durations, especially for the Maximum-to-Mean Ratio indicator.