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Abstract Background Schistosomiasis is still one of the most serious parasitic diseases. Evidence showed that the metabolite profile in serum can potentially act as a marker for parasitic disease diagnosis and evaluate disease progression and prognosis. However, the serum metabolome in patients with Schistosoma japonicum infection is not well defined. In this study, we investigated the metabolite profiles of patients with chronic and with advanced S. japonicum infection. Methods The sera of 33 chronic S. japonicum patients, 15 patients with advanced schistosomiasis and 17 healthy volunteers were collected. Samples were extracted for metabolites and analyzed with ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Results We observed significant differences in metabolite profiles in positive and negative ion modes between patients with advanced and chronic S. japonicum infection. In patients with chronic S. japonicum infection, 199 metabolites were significantly upregulated while 207 metabolites were downregulated in advanced infection. These differential metabolites were mainly concentrated in steroid hormone biosynthesis, cholesterol metabolism and bile secretion pathways. We also found that certain bile acid levels were significantly upregulated in the progression from chronic to advanced S. japonicum infection. In receiver operator characteristic (ROC) analysis, we identified three metabolites with area under the curve (AUC) > 0.8, including glycocholic (GCA), glycochenodeoxycholate (GCDCA) and taurochenodeoxycholic acid (TCDCA) concentrated in cholesterol metabolism, biliary secretion and primary bile acid biosynthesis. Conclusions This study provides evidence that GCA, GCDCA and TCDCA can potentially act as novel metabolite biomarkers to distinguish patients in different stages of S. japonicum infection. This study will contribute to the understanding of the metabolite mechanisms of the transition from chronic to advanced S. japonicum infection, although more studies are needed to validate this potential role and explore the underlying mechanisms. Graphical Abstract

Abstract Thermal regulators are devices that can adopt either the role of a thermal insulator or a thermal conductor, depending on the thermal input conditions, and play an increasingly important role in thermal management systems. In this study, we developed and tested a new passive thermal regulator design that operates around room temperature and achieves high switching ratios. Our regulator is structurally integer, scalable, orientation-independent, resistant to vibration, and can be easily integrated into existing thermal management solutions. The working principle of the passive regulator is simple yet effective, whereby an aluminum plug attached to a bimetallic strip enters and exists a wedge-shaped gap between two conductors. We demonstrate a switching ratio of ≈ 50 $$(_{ - 8}^{ + 34} )$$ ( - 8 + 34 ) :1 for a fully packaged prototype (≈ 320 (± 200):1 for a non-packaged regulator) operated in the open laboratory environment. Through geometric optimization using numerical simulations, we show that a switching ratio of ≈ 100 $$(_{ - 15}^{ + 18} ){ }$$ ( - 15 + 18 ) :1 can be easily obtained, which can be further increased by increasing the cross-sectional area of the input conductor, hence increasing the ON-state heat transfer rate. The OFF-state thermal performance is much less sensitive to the size of the conductor, making the device highly scalable.

Abstract Liver fibrosis is an important pathological process in chronic liver disease and cirrhosis. Recent studies have found a close association between intestinal microbiota and the development of liver fibrosis. To determine whether there are differences in the intestinal microbiota between rhesus macaques with liver fibrosis (MG) and normal rhesus macaques (MN), fecal samples were collected from 8 male MG and 12 male MN. The biological composition of the intestinal microbiota was then detected using 16S rRNA gene sequencing. The results revealed statistically significant differences in ASVs and Chao1 in the alpha-diversity and the beta-diversity of intestinal microbiota between MG and MN. Both groups shared Prevotella and Lactobacillus as common dominant microbiota. However, beneficial bacteria such as Lactobacillus were significantly less abundant in MG (P = 0.02). Predictive functional analysis using PICRUSt2 gene prediction revealed that MG exhibited a higher relative abundance of functions related to substance transport and metabolic pathways. This study may provide insight into further exploration of the mechanisms by which intestinal microbiota affect liver fibrosis and its potential future use in treating liver fibrosis.

Abstract Irritable bowel syndrome (IBS) is a prevalent disorder of gut‐brain interaction without a reliable cure. Evidence suggests that an alteration of the gut microbiome may contribute to IBS pathogenesis, motivating the development of microbiome‐targeted therapies to alleviate IBS symptoms. However, IBS‐specific microbiome signatures are variable across cohorts. A total of 9204 datasets were meta‐analyzed, derived from fourteen IBS microbiome discovery cohorts, three validation cohorts for diet‐microbiome interactions, and five rifaximin therapy cohorts. The consistent bacterial species and functional signatures associated with IBS were identified. Network analysis revealed two distinct IBS‐enriched microbiota clusters; obligate anaerobes that are found commonly in the gut, and facultative anaerobes typically present in the mouth, implying a possible association between oral bacterial translocation to gut and IBS pathogenesis. By analyzing diet‐microbiome interactions, microbiota‐targeted diets that can potentially modulate the altered gut microbiota of IBS subjects toward a healthy status were identified. Furthermore, rifaximin treatment of IBS subjects was linked with a reduction in the abundance of facultatively anaerobic pathobionts. Gut microbiome signatures were identified across IBS cohorts that may inform the development of therapies for microbiome modulation in IBS. The microbiota‐targeted diet patterns described may enable nutritional intervention trials in IBS and for assisting dietary management.

Dysregulation of cholesterol metabolism is an important feature of cancer development. There are limited reports on the involvement of lncRNAs in hepatocellular carcinoma (HCC) progression via the cholesterol metabolism pathway. The present study explored the effect of LINC00618 on HCC growth and metastasis, and elucidated the underlying mechanisms involved in cholesterol metabolism. Here, we found that LINC00618 expression was upregulated in cancerous tissues from 30 patients with HCC compared to that in adjacent normal tissues. High expression of LINC00618 was detected in metastatic HCC tissues. LINC00618 is predominantly localized in the nucleus and overexpression of LINC00618 facilitated HCC cell proliferation, migration and EMT progression by promoting cholesterol biosynthesis. Mechanistically, the 1–101nt region of LINC00618 bound to NSUN2. LINC00618 inhibited ubiquitin-proteasome pathway-induced NSUN2 degradation. NSUN2 stabilized by LINC00618 increased m5C modification of SREBP2 and promoted SREBP2 mRNA stability in a YBX1-dependent manner, thereby promoting cholesterol biosynthesis in HCC cells. Moreover, mouse HCC xenograft and lung metastasis models were established by subcutaneous and tail vein injections of MHCC97 cells transfected with or without sh-LINC00618. Silencing LINC00618 impeded HCC growth and metastasis. In conclusion, LINC00618 promoted HCC growth and metastasis by elevating cholesterol synthesis by stabilizing NSUN2 to enhance SREBP2 mRNA stability in an m5C-dependent manner.

Abstract This study intends to use the basic information and blood routine of schistosomiasis patients to establish a machine learning model for predicting liver fibrosis. We collected medical records of Schistosoma japonicum patients admitted to a hospital in China from June 2019 to June 2022. The method was to screen out the key variables and six different machine learning algorithms were used to establish prediction models. Finally, the optimal model was compared based on AUC, specificity, sensitivity and other indicators for further modeling. The interpretation of the model was shown by using the SHAP package. A total of 1049 patients’ medical records were collected, and 10 key variables were screened for modeling using lasso method, including red cell distribution width-standard deviation (RDW-SD), Mean corpuscular hemoglobin concentration (MCHC), Mean corpuscular volume (MCV), hematocrit (HCT), Red blood cells, Eosinophils, Monocytes, Lymphocytes, Neutrophils, Age. Among the 6 different machine learning algorithms, LightGBM performed the best, and its AUCs in the training set and validation set were 1 and 0.818, respectively. This study established a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum. The model could help improve the early diagnosis and provide early intervention for schistosomiasis patients with liver fibrosis.

Abstract Background The prevalence of neoplastic polyps in gallbladder polyps (GPs) increases sharply with age and is associated with gallbladder carcinoma (GBC). This study aims to predict neoplastic polyps and provide appropriate treatment strategies based on preoperative ultrasound features in patients with different age level. Methods According to the age classification of WHO, 1523 patients with GPs who underwent cholecystectomy from January 2015 to December 2019 at 11 tertiary hospitals in China were divided into young adults group (n=622), middle-aged group (n=665) and elderly group (n=236). Linear scoring models were established based on independent risk variables screened by the Logistic regression model in different age groups. The area under ROC (AUC) to evaluate the predictive ability of linear scoring models, long- and short- diameter of GPs. Results Independent risk factors for neoplastic polyps included the number of polyps, polyp size (long diameter), and fundus in the young adults and elderly groups, while the number of polyps, polyp size (long diameter), and polyp size (short diameter) in the middle-aged groups. In different age groups, the AUCs of its linear scoring model were higher than the AUCs of the long- and short- diameter of GPs for differentiating neoplastic and non-neoplastic polyps (all P0.05). Conclusion The linear scoring models of the young adults, middle-aged and elderly groups can effectively distinguish neoplastic polyps from non-neoplastic polyps based on preoperative ultrasound features.

Abstract Background Schistosomiasis, a neglected tropical disease, remains an important public health problem. Although there are various methods for diagnosing schistosomiasis, many limitations still exist. Early diagnosis and treatment of schistosomiasis can significantly improve survival and prognosis of patients. Methodology Circulating cell-free (cf)DNA has been widely used in the diagnosis of various diseases. In our study, we evaluated the diagnostic value of circulating cfDNA for schistosomiasis caused by Schistosoma japonicum. We focused on the tandem sequences and mitochondrial genes of S. japonicum to identify highly sensitive and specific targets for diagnosis of Schistosomiasis japonica. Results Through data screening and analysis, we ultimately identified four specific tandem sequences (TD-1, TD-2, TD-3. and TD-4) and six mitochondrial genes (COX1(1), COX1(2), CYTB, ATP6, COX3, and ND5). We designed specific primers to detect the amount of circulating cfDNA in S. japonicum-infected mouse and chronic schistosomiasis patients. Our results showed that the number of tandem sequences was significantly higher than that of the mitochondrial genes. A S. japonicum infection model in mice suggested that infection of S. japonicum can be diagnosed by detecting circulating cfDNA as early as the first week. We measured the expression levels of circulating cfDNA (TD-1, TD-2, and TD-3) at different time points and found that TD-3 expression was significantly higher than that of TD-1 or TD-2. We also infected mice with different quantities of cercariae (20 s and 80 s). The level of cfDNA (TD-3) in the 80 s infection group was significantly higher than in the 20 s infection group. Additionally, cfDNA (TD-3) levels increased after egg deposition. Meanwhile, we tested 42 patients with chronic Schistosomiasis japonica and circulating cfDNA (TD-3) was detected in nine patients. Conclusions We have screened highly sensitive targets for the diagnosis of Schistosomiasis japonica, and the detection of circulating cfDNA is a rapid and effective method for the diagnosis of Schistosomiasis japonica. The levels of cfDNA is correlated with cercariae infection severity. Early detection and diagnosis of schistosomiasis is crucial for patient treatment and improving prognosis. Graphical Abstract

Protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and risk of long COVID has been associated with the depletion or over-abundance of specific taxa within the gut microbiome. However, the microbial mechanisms mediating these effects are not yet known. We hypothesized that altered microbial production of tryptophan and its downstream derivatives might contribute to inappropriate immune responses to viral infection. In patients hospitalized with COVID-19 (n = 172), serum levels of tryptophan and indole-3-propionate (IPA) negatively correlated with serum levels of many proinflammatory mediators (including C-reactive protein and Serum amyloid A), while C-glycosyltryptophan (C-Trp), indole-3-lactic acid (ILA) and indole-3-acetic acid (IAA) levels were positively correlated with levels of acute phase proteins, proinflammatory cytokines, alarmins and chemokines. A similar pattern was observed in long COVID patients (n = 20) where tryptophan and IPA were negatively associated with a large number of serum cytokines, while C-Trp and IAA were positively associated with circulating cytokine levels. Metagenomic analysis of the fecal microbiota showed the relative abundance of genes encoding the microbial enzymes required for tryptophan production (e.g. anthranilate synthase) and microbial tryptophan metabolism was significantly lower in patients hospitalized with COVID-19 (n = 380) compared to healthy controls (n = 270). Microbial tryptophan metabolites reduced innate cell proinflammatory responses to cytosolic DNA sensor Stimulator of interferon genes (STING), toll-like receptor (TLR)-3 and TLR-4 stimulation in vitro, while IL-10 secretion was enhanced. Microbial tryptophan metabolites also modified ex vivo human lymphocyte responses by limiting the production of TH1 and TH17 associated cytokines, while enhancing secretion of IL-22. These data suggest that lower levels of tryptophan production and tryptophan metabolism by gut microbes may increase the risk of severe and chronic outcomes to SARS-CoV-2 infection due to impaired innate and adaptive responses to infection. Screening patients for lower-level microbiome capacity for tryptophan metabolism may help identify at-risk individuals.

Objectives Accurate survival predictions and early interventional therapy are crucial for people with clear cell renal cell carcinoma (ccRCC). Methods In this retrospective study, we identified differentially expressed immune-related (DE-IRGs) and oncogenic (DE-OGs) genes from The Cancer Genome Atlas (TCGA) dataset to construct a prognostic risk model using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. We compared the immunogenomic characterization between the high- and low-risk patients in the TCGA and the PUCH cohort, including the immune cell infiltration level, immune score, immune checkpoint, and T-effector cell- and interferon (IFN)-γ-related gene expression. Results A prognostic risk model was constructed based on 9 DE-IRGs and 3 DE-OGs and validated in the training and testing TCGA datasets. The high-risk group exhibited significantly poor overall survival compared with the low-risk group in the training ( P < 0.0001), testing ( P = 0.016), and total ( P < 0.0001) datasets. The prognostic risk model provided accurate predictive value for ccRCC prognosis in all datasets. Decision curve analysis revealed that the nomogram showed the best net benefit for the 1-, 3-, and 5-year risk predictions. Immunogenomic analyses of the TCGA and PUCH cohorts showed higher immune cell infiltration levels, immune scores, immune checkpoint, and T-effector cell- and IFN-γ-related cytotoxic gene expression in the high-risk group than in the low-risk group. Conclusion The 12-gene prognostic risk model can reliably predict overall survival outcomes and is strongly associated with the tumor immune microenvironment of ccRCC.

Rapid evolution of porcine reproductive and respiratory syndrome virus (PRRSV) is the bottleneck for effective prevention and control of PRRS. Thus, understanding the prevalence and genetic background of PRRSV strains in swine-producing regions is important for disease prevention and control. However, there is only limited information about the epizootiological situation of PRRS in the Xinjiang Uygur Autonomous Region, China. In this study, blood or lung tissue samples were collected from 1,411 PRRS-suspected weaned pigs from 9 pig farms in Changji, Shihezi, and Wujiaqu cities between 2020 and 2022. The samples were first tested by RT-quantitative PCR, yielding a PRRSV-2 positive rate of 53.6%. Subsequently, 36 PRRSV strains were isolated through initial adaptation in bone marrow-derived macrophages followed by propagation in grivet monkey Marc-145 cells. Furthermore, 28 PRRSV-positive samples and 20 cell-adapted viruses were selected for high-throughput sequencing (HTS) to obtain the entire PRRSV genome sequences. Phylogenetic analysis based on the nucleotide sequences of the ORF5 gene of the PRRSV strains identified in this study grouped into sub-lineages 1.8 and 8.7 the former being the dominant strain currently circulating in Xinjiang. However, the NSP2 proteins of the Xinjiang PRRSV strains shared the same deletion patterns as sub-lineage 1.8 prototype strain NADC30 with the exception of 4 strains carrying 2-3 additional amino acid deletions. Further analysis confirmed that recombination events had occurred in 27 of 37 PRRSVs obtained here with the parental strains belonging to sub-lineages 1.8 and 8.7, lineages 3 and 5, with the recombination events having occurred most frequently in the 5' and 3' termini of ORF1a and 5' terminus of ORF1b.

Abstract The primary methods of assessing the reliability of distribution networks comprise analytic and simulation methods. However, both approaches require the identification and computation of network topology, which precludes their expression in explicit, continuous functions, consequently impeding the incorporation of reliability constraints into planning and operational optimization models. To tackle this restriction, the present work puts forth a novel linear‐programming‐based reliability assessment method that is mathematically formulated, considering distribution automation (DA) and distributed generations (DGs), consisting of both conventional and renewable energy sources. In this paper, the clustering method and the scenario‐based method are used to model DGs. Next, a mixed integer linear programming (MILP) model, considering the DA and DGs with the System Average Interruption Duration Index (SAIDI) as the optimization objective, is proposed. Finally, the feasibility and effectiveness of the proposed method are verified in a 37‐node distribution network system.

Aiming at the difficulty of sample collection, high cost, and small sample problems caused by many types of defects and difficulty in covering all small samples in the process of industrial steel surface defect detection, a steel surface defect image generation method improved by cycle-consistent generation adversarial network (CycleGAN) was proposed. Firstly, channel attention map (CAM) and spatial attention map (SAM) were embedded in the CycleGAN model to enhance the feature extraction ability of the model. Secondly, the Weight Demodulation (WD) mechanism was introduced to fix feature artifacts and white spots, further improving the quality of the generated images. Thirdly, shape consistency loss was introduced to supervise the generator training process to solve the problem of inherent ambiguity in the process of image geometric transformation. Finally,the model before and after the improvement were experimented on the NEU-DET dataset. The results show that the improved model has more diversity and accuracy in the effect of defect image generation. PSNR and SSIM increase by 13.0% and 7.8% respectively, and FID values are reduced by 33.1%. This method can stably generate high-quality images of various steel surface defects, which can achieve the purpose of increasing training data, and also has reference value for the amplification of other defect datasets.

In order to solve the issue of low efficiency in retired battery clustering, a method for quickly obtaining a charging curve and Incremental Capacity (IC) curve based on Convolutional Neural Networks (CNN) is proposed. By training a CNN model, the method enables accurate prediction of complete IC curves and V-Q curves from local charging curves starting at any beginning. The prediction accuracy was validated using the Oxford battery degradation dataset, and transfer learning was conducted by fine-tuning the model trained on LCO batteries for use with LFP batteries, which reduced the RMSE of the estimation and validated the generalizability of the model. Peak parameters were extracted from both the original and predicted IC curves for clustering, and the t-test was applied to eliminate outliers, which significantly reduced the time required to obtain clustering features and improved clustering efficiency.

Salinity significantly affects shellfish metabolism and growth. In this study, we evaluated the characterization of metabolomic differences in the juvenile black-shelled pearl oyster, Pinctada fucata martensii, under 15‰ (LSG), 25‰ (CG), and 35‰ (HSG) salinity conditions. Non-targeted metabolomics analyses revealed that salinity stress altered the metabolism of pearl oyster. A total of 229 significant differential metabolites (SDMs) were identified between LSG and CG via an in-house MS2 database, 241 SDMs were identified between LSG and HSG, and 50 SDMs were identified between CG and HSG. The pathway analysis showed that 21 metabolic pathways were found between LSG and CG, such as arginine and proline metabolism, glycerophospholipid metabolism, and pentose and glucuronide interconversion. A total of 23 metabolic pathways were obtained between LSG and HSG, such as aspartate, alanine, and glutamate metabolism. Only aminoacyl-tRNA biosynthesis, cysteine and methionine metabolism, and biotin metabolism were enriched between CG and HSG. A further integrated analysis suggested that amino acid metabolism might participate in osmoregulation and energy metabolism to respond to salinity stress in P. f. martensii, and the metabolic pathways differed under varying salinity stress conditions. In addition, low salinity stress might promote apoptosis in pearl oysters. Altogether, these results clarify the salinity tolerance mechanism of pearl oysters.

To study the impact of faults on the enrichment and mobility of shale oil in the Gulong area, representative rock samples were selected in this paper. Based on geochemical data and chemical kinetics methods, coupled with shale oil enrichment and mobility analysis techniques, the shale oil generation quantity and in situ oil content were evaluated from the perspectives of shale oil generation and micro migration, and the mobility of shale oil was revealed. At the same time, the hydrocarbon expulsion efficiency (HEE) of shale was qualitatively and quantitatively characterized, combined with the development of faults. The research results indicate that the study area mainly develops organic-rich felsic (ORF)/organic-containing felsic (OCF) shale, their proportion in both wells exceeds 65%, and the resource amount is the largest in this type of lithofacies. The development of a fault controls the enrichment of shale oil, and the in situ oil content and oil saturation index (OSI) of the shale in well Y58, which is close to the fault, are significantly worse than those in well S2. Well Y58 has 9.52 mg/g and 424.83 mg/g TOC respectively, while well S2 has 11.34 mg/g and 488.73 mg/g TOC respectively. The fault enhanced the migration of shale oil, increasing the efficiency of oil expulsion. As a result, the components with weak polarity or small molecules, such as saturated hydrocarbons and low carbon number n-alkanes, are prone to migration, reducing the mobility of shale oil.

Abstract Background Disability in activities of daily living (ADL) significantly increases the risk of mortality among patients undergoing hemodialysis. Malnutrition and decreased exercise capacity are closely correlated with ADL disability. Phase angle (PhA) has been proposed as a measure of nutritional status and exercise capacity. This study aims to investigate the prevalence of ADL disability in hemodialysis patients and its association with PhA. Methods A prospective, observational study was conducted, involving hemodialysis patients treated between November 2019 and January 2020 in an affiliated hospital of Chinese university. ADL was measured using both basic ADL (BADL) scales and instrumental ADL (IADL) scales. PhA measurements were obtained using a BIA device while the patients were in the supine position after dialysis. Results A total of 237 hemodialysis patients with a mean age of 60.01 ± 13.55 years were included in this study. The prevalence of disability in ADL was 43.5%. Multivariable analysis results showed a robust association between low PhA and disability in both BADL and IADL (for each unit decrease in PhA: odds ratio 4.83 [95% CI: 2.56–9.0], and 3.57 [95% CI: 2.14–5.95], respectively). The optimal cut-off values of PhA for disability in BADL and IADL were 4.8 and 5.4, with the area under the ROC curve (AUC) were 0.783 (0.727, 0.835) and 0.799 (0.743, 0.848), respectively. Conclusions Low PhA is strongly associated with disability in ADL in hemodialysis patients. These findings suggest that PhA may serve as a potentially objective measure of ADL disability in hemodialysis patients.

Abstract Background Schistosomiasis, also known as bilharzia, is a devastating parasitic disease. This progressive and debilitating helminth disease is often associated with poverty and can lead to chronic poor health. Despite ongoing research, there is currently no effective vaccine for schistosomiasis, and praziquantel remains the only available treatment option. According to the progression of schistosomiasis, infections caused by schistosomes are classified into three distinct clinical phases: acute, chronic and advanced schistosomiasis. However, the underlying immune mechanism involved in the progression of schistosomiasis remains poorly understood. Methods We employed single-cell RNA sequencing (scRNA-seq) to profile the immune landscape of Schistosomiasis japonica infection based on peripheral blood mononuclear cells (PBMCs) from a healthy control group (n = 4), chronic schistosomiasis group (n = 4) and advanced schistosomiasis group (n = 2). Results Of 89,896 cells, 24 major cell clusters were ultimately included in our analysis. Neutrophils and NK/T cells accounted for the major proportion in the chronic group and the healthy group, and monocytes dominated in the advanced group. A preliminary study showed that NKT cells were increased in patients with schistosomiasis and that CXCR2 + NKT cells were proinflammatory cells. Plasma cells also accounted for a large proportion of B cells in the advanced group. MHC molecules in monocytes were notably lower in the advanced group than in the chronic group or the healthy control group. However, monocytes in the advanced group exhibited high expression of FOLR3 and CCR2. Conclusions Overall, this study enhances our understanding of the immune mechanisms involved in schistosomiasis. It provides a transcriptional atlas of peripheral immune cells that may contribute to elimination of the disease. This preliminary study suggests that the increased presence of CCR2 + monocyte and CXCR2 + NKT cells might participate in the progression of schistosomiasis. Graphical Abstract

Abstract With the rapid development of wind power, the pressure on peak regulation of the power grid is increased. Electrochemical energy storage is used on a large scale because of its high efficiency and good peak shaving and valley filling ability. The economic benefit evaluation of participating in power system auxiliary services has become the focus of attention since the development of grid-connected hundred megawatt-scale electrochemical energy storage systems (ESS). Based on the relationship between power and capacity in the process of peak shaving and valley filling, a dynamic economic benefit evaluation model of peak shaving assisted by hundred megawatt-scale electrochemical ESS considering the equivalent life of the battery is proposed. The model considers the investment cost of energy storage, power efficiency, and operation and maintenance costs, and analyzes the dynamic economic benefits of different energy storage technologies participating in the whole life cycle of the power grid. Then, according to the current ESS market environment, the auxiliary service compensation price, peak-valley price difference and energy storage cost unit price required to make the energy storage technology achieve the balance of payments are calculated, and the economic balance points of different energy storage types are clarified. Finally, based on the measured data of different provincial power grids, the economies of six energy storage types applied to three provincial power grids are compared and analyzed, and the rationality and effectiveness of the relevant models proposed are verified. The work has theoretical guiding significance for the economic benefit evaluation of hundred megawatt-scale electrochemical energy storage.

Abstract Background Schistosoma infection is a significant public health issue, affecting over 200 million individuals and threatening 700 million people worldwide. The species prevalent in China is Schistosoma japonicum. Recent studies showed that both gut microbiota and metabolome are closely related to schistosomiasis caused by S. japonicum, but clinical study is limited and the underlying mechanism is largely unclear. This study aimed to explore alterations as well as function of gut microbiota and metabolite profile in the patients with S. japonicum infection. Methods This study included 20 patients diagnosed with chronic schistosomiasis caused by S. japonicum, eight patients with advanced schistosomiasis caused by S. japonicum and 13 healthy volunteers. The fresh feces of these participators, clinical examination results and basic information were collected. 16S ribosomal RNA gene sequencing was used to investigate gut microbiota, while ultraperformance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to explore the metabolome of patients in different stages of schistosomiasis. Results The study found that gut microbiota and metabolites were altered in patients with different stages of S. japonicum infection. Compared with healthy control group, the gut microbial diversity in patients with chronic S. japonicum infection was decreased significantly. However, the diversity of gut microbiota in patients with chronic schistosomiasis was similar to that in patients with advanced schistosomiasis. Compared with uninfected people, patients with schistosomiasis showed decreased Firmicutes and increased Proteobacteria. As disease progressed, Firmicutes was further reduced in patients with advanced S. japonicum infection, while Proteobacteria was further increased. In addition, the most altered metabolites in patients with S. japonicum infection were lipids and lipid-like molecules as well as organo-heterocyclic compounds, correlated with the clinical manifestations and disease progress of schistosomiasis caused by S. japonicum. Conclusions This study suggested that the gut microbiota and metabolome altered in patients in different stages of schistosomiasis, which was correlated with progression of schistosomiasis caused by S. japonicum. This inter-omics analysis may shed light on a better understanding of the mechanisms of the progression of S. japonicum infection and contribute to identifying new potential targets for the diagnosis and prognosis of S. japonicum infection. However, a large sample size of validation in clinic is needed, and further study is required to investigate the underlying mechanism.

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein’s unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD.

Hydrothermal activity is widespread in sedimentary basins, but its dual effects (chemistry and temperature) on shale reservoirs are rarely discussed. In this research, we systematically collected 33 well core samples from Q1 to Q9 units in Gulong Sag, Songliao Basin, and analyzed them using a variety of analytical techniques, including a field emission scanning electron microscopy (FE-SEM), an energy-dispersive spectrometer (EDS), X-ray diffraction (XRD), and stable C-O isotopes. Combined with the collected vitrinite reflectance (Ro), total organic carbon (TOC), and soluble hydrocarbon content data, which is the sum of free oil (pyrolysis S1) and sorb oil content (pyrolysis S2), the results show that (1) Q4 and Q8 units have large amounts of hydrothermal minerals, and its C-O isotope obviously shifts to negative, which implied those units are the main hydrothermal fluid influence area; (2) the hydrothermal activity occurred in the late depositional period of Q1–Q9 units such that its geochemistry has little effect on the proliferation of algae blooms, but its high temperature calculated by δ18O temperature formulas (around 208 °C) promoted the organic matter maturation process around Q4 and Q8; and (3) the overpressure caused by hydrothermal activity protected the shale reservoir and minimized the decrease in mineral reservoir brittleness index caused by hydrothermal fluid influence. We suggest that the shale reservoir affected by hydrothermal fluid will become a good geology “dessert”, and its upper and/or lower bounds can form an engineering “dessert” due to the precipitation of large amounts of brittle carbonate minerals.

Based on the oil and gas exploration practice in the Songliao Basin, combined with the latest exploration and development data such as seismic, well logging and geochemistry, the basic geological conditions, oil and gas types and distribution characteristics, reservoir-forming dynamics, source-reservoir relationship and hydrocarbon accumulation model of the whole petroleum system in shallow and medium strata in the northern part of Songliao Basin are systematically studied. The shallow–medium strata in northern Songliao Basin have the conditions for the formation of whole petroleum system, with sufficient oil and gas sources, diverse reservoir types and well-developed transport system, forming a whole petroleum system centered on the source rocks of the Cretaceous Qingshankou Formation. Different types of oil and gas resources in the whole petroleum system are correlated with each other in terms of depositional system, lithologic association and physical property changes, and they, to a certain extent, have created the spatial framework with orderly symbiosis of shallow–medium conventional oil reservoirs, tight oil reservoirs and shale oil reservoirs in northern Songliao Basin. Vertically, the resources are endowed as conventional oil above source, shale oil/tight oil within source, and tight oil below source. Horizontally, conventional oil, tight oil, interlayer-type shale oil, and pure shale-type shale oil are developed in an orderly way, from the margin of the basin to the center of the depression. Three hydrocarbon accumulation models are recognized for the whole petroleum system in northern Songliao Basin, namely, buoyancy-driven charging of conventional oil above source, retention of shale oil within source, and pressure differential-driven charging of tight oil below source.

Abstract Schistosomiasis is a chronic parasitic disease, which affects the quality of daily life of patients and imposes a huge burden on society. Hepatic fibrosis in response to continuous insult of eggs to the liver is a significant cause of morbidity and mortality. However, the mechanisms of hepatic fibrosis in schistosomiasis are largely undefined. The purpose of our study is to detect the indicator to hepatic fibrosis in schistosomiasis. A total of 488 patients with chronic schistosomiasis japonica were enrolled in our study. The patients were divided into two groups according to liver ultrasound examination, which could indicate liver fibrosis of schistosomiasis with unique reticular changes. Logistic regression analysis showed that globulin, albumin/globulin, GGT levels and anti-Schistosoma IgG were independently associated with liver fibrosis in patients with schistosomiasis and IgG was the largest association of liver fibrosis (OR 2.039, 95% CI 1.293–3.213). We further compared IgG+ patients with IgG− patients. IgG+ patients (ALT 25 U/L, GGT 31 U/L) slightly higher than IgG− patients (ALT 22 U/L, GGT 26 U/L) in ALT and GGT. However, the fibrosis of liver in IgG+ patients (Grade II(19.7%), Grade III(7.3%)) were more severe than that in IgG− patients(Grade II(12.5%), Grade III(2.9%)) according to the grade of liver ultrasonography. Our results showed anti-Schistosoma IgG was independently associated with liver fibrosis in patients with chronic schistosomiasis japonica and patients with persistent anti-Schistosoma IgG might have more liver fibrosis than negative patients despite no obvious clinical signs or symptoms.

Abstract Background Acute-on-chronic liver failure (ACLF) is a severe syndrome with high short-term mortality, but the pathophysiology still remains largely unknown. Immune dysregulation and metabolic disorders contribute to the progression of ACLF, but the crosstalk between immunity and metabolism during ACLF is less understood. This study aims to depict the immune microenvironment in the liver during ACLF, and explore the role of lipid metabolic disorder on immunity. Methods Single-cell RNA-sequencing (scRNA-seq) was performed using the liver non-parenchymal cells (NPCs) and peripheral blood mononuclear cells (PBMCs) from healthy controls, cirrhosis patients and ACLF patients. A series of inflammation-related cytokines and chemokines were detected using liver and plasma samples. The lipid metabolomics targeted free fatty acids (FFAs) in the liver was also detected. Results The scRNA-seq analysis of liver NPCs showed a significant increase of monocytes/macrophages (Mono/Mac) infiltration in ACLF livers, whereas the resident Kupffer cells (KCs) were exhausted. A characterized TREM2+ Mono/Mac subpopulation was identified in ACLF, and showed immunosuppressive function. Combined with the scRNA-seq data from PBMCs, the pseudotime analysis revealed that the TREM2+ Mono/Mac were differentiated from the peripheral monocytes and correlated with lipid metabolism-related genes including APOE, APOC1, FABP5 and TREM2. The targeted lipid metabolomics proved the accumulation of unsaturated FFAs associated with α-linolenic acid (α-LA) and α-LA metabolism and beta oxidation of very long chain fatty acids in the ACLF livers, indicating that unsaturated FFAs might promote the differentiation of TREM2+ Mono/Mac during ACLF. Conclusions The reprogramming of macrophages was found in the liver during ACLF. The immunosuppressive TREM2+ macrophages were enriched in the ACLF liver and contributed to the immunosuppressive hepatic microenvironment. The accumulation of unsaturated FFAs in the ACLF liver promoted the reprogramming of the macrophages. It might be a potential target to improve the immune deficiency of ACLF patients through regulating lipid metabolism.

Microorganisms are important sources of various natural products that have been commercialized for human medicine and animal healthcare. Bacitracin is an important antibacterial natural product predominantly produced by Bacillus licheniformis and Bacillus subtilis, and it is characterized by a broad antimicrobial spectrum, strong activity and low resistance, thus bacitracin is extensively applied in animal feed and veterinary medicine industries. In recent years, various strategies have been proposed to improve bacitracin production. Herein, we systematically describe the regulation of bacitracin biosynthesis in genus Bacillus and its associated mechanism, to provide a theoretical basis for bacitracin overproduction. The metabolic engineering strategies applied for bacitracin production are explored, including improving substrate utilization, using an enlarged precursor amino acid pool, increasing ATP supply and NADPH generation, and engineering transcription regulators. We also present several approaches of fermentation process optimization to facilitate the industrial large-scale production of bacitracin. Finally, the challenges and prospects associated with microbial bacitracin synthesis are discussed to facilitate the establishment of high-yield and low-cost biological factories.

Compared with other OECD countries, Bermuda ranks third globally in terms of income inequality globally. During the COVID-19 pandemic, anecdotal evidence suggested, significant fluctuations in the food demand and supply. We aimed to examine the impact of the COVID-19 pandemic on food insecurity, with a focus on the availability and affordability of various foods in Bermuda. We utilized a cross-sectional study design to investigate potential drivers of food insecurity within the local population. To gauge the level of household food insecurity we relied on the Bermuda Omnibus survey (N = 400) undertaken by Total Research Associates Ltd via telephone. To assess changes in food availability and affordability we conducted semi-structured interviews with key stakeholders who played pivotal roles in shaping food accessibility availability and affordability of food in Bermuda. These interviews were systematically analysed using the framework method. We performed analyses of food retail and import data to evaluate fluctuations in food prices and their impact on food availability and affordability. We found statistically significant associations between changes in food consumption, household income, and government aid. Food aid beneficiaries ate fewer fruits and vegetables by 50% [95% CI:17%-83%] and less fresh meat and fish by 39% [95 CI:3%-75%] compared with residents who did not receive any aid during the COVID-19 period from March 2020 to March 2021. Although we did not identify statistically significant food price increases feeding programmes played a pivotal role in preventing food insecurity during the pandemic in Bermuda. However, a lack of monitoring regarding the nutritional quality within the programmes, allowed a wide availability of foods high in sugar, salts, and fats, disproportionately affected low-income populations. In conclusion, food availability in Bermuda remained largely unaffected during the pandemic. Nevertheless, the surge in demand for feeding programs underscores underlying food security challenges in Bermuda and warrants further attention.

The Grain for Green Program (GFGP) is an important policy implemented by the Chinese government to restore degraded forests. However, there is a limited understanding of the eco-economic benefits of GFGP in Sichuan province. In this study, the ecosystem service value (ESV) in Sichuan from 2001 to 2019 was evaluated dynamically based on the improved value equivalent method. Then, the impact of climate and human activities on ESV was explored. Finally, the eco-economic benefit model of afforestation was constructed to calculate its value efficiency in 183 counties and the return rate on afforestation investment in Sichuan. Our results indicated that the forest ESV (R2 = 0.82, P

ABSTRACTAlthough many recent studies have examined associations between the gut microbiome and COVID-19 disease severity in individual patient cohorts, questions remain on the robustness across international cohorts of the biomarkers they reported. Here, we performed a meta-analysis of eight shotgun metagenomic studies of COVID-19 patients (comprising 1,023 stool samples) and 23 > 16S rRNA gene amplicon sequencing (16S) cohorts (2,415 total stool samples). We found that disease severity (as defined by the WHO clinical progression scale) was associated with taxonomic and functional microbiome differences. This alteration in gut microbiome configuration peaks at days 7–30 post diagnosis, after which the gut microbiome returns to a configuration that becomes more similar to that of healthy controls over time. Furthermore, we identified a core set of species that were consistently associated with disease severity across shotgun metagenomic and 16S cohorts, and whose abundance can accurately predict disease severity category of SARS-CoV-2 infected subjects, with Actinomyces oris abundance predicting population-level mortality rate of COVID-19. Additionally, we used relational diet-microbiome databases constructed from cohort studies to predict microbiota-targeted diet patterns that would modulate gut microbiota composition toward that of healthy controls. Finally, we demonstrated the association of disease severity with the composition of intestinal archaeal, fungal, viral, and parasitic communities. Collectively, this study has identified robust COVID-19 microbiome biomarkers, established accurate predictive models as a basis for clinical prognostic tests for disease severity, and proposed biomarker-targeted diets for managing COVID-19 infection.

Abstract Background African swine fever (ASF) is a highly fatal disease in domestic pigs caused by ASF virus (ASFV), for which there is currently no commercial vaccine available. The genome of ASFV encodes more than 150 proteins, some of which have been included in subunit vaccines but only induce limited protection against ASFV challenge. Methods To enhance immune responses induced by ASFV proteins, we expressed and purified three fusion proteins with each consisting of bacterial lipoprotein OprI, 2 different ASFV proteins/epitopes and a universal CD4+ T cell epitope, namely OprI-p30-modified p54-TT, OprI-p72 epitopes-truncated pE248R-TT, and OprI-truncated CD2v-truncated pEP153R-TT. The immunostimulatory activity of these recombinant proteins was first assessed on dendritic cells. Then, humoral and cellular immunity induced by these three OprI-fused proteins cocktail formulated with ISA206 adjuvant (O-Ags-T formulation) were assessed in pigs. Results The OprI-fused proteins activated dendritic cells with elevated secretion of proinflammatory cytokines. Furthermore, the O-Ags-T formulation elicited a high level of antigen-specific IgG responses and interferon-γ-secreting CD4+ and CD8+ T cells after stimulation in vitro. Importantly, the sera and peripheral blood mononuclear cells from pigs vaccinated with the O-Ags-T formulation respectively reduced ASFV infection in vitro by 82.8% and 92.6%. Conclusions Our results suggest that the OprI-fused proteins cocktail formulated with ISA206 adjuvant induces robust ASFV-specific humoral and cellular immune responses in pigs. Our study provides valuable information for the further development of subunit vaccines against ASF.

BackgroundThe intestinal microbiota is known to play a role in the development of liver disease, there is a limited understanding of the intestinal microbiota associated with chronic schistosomiasis japonica. This study sought to explore the characteristics of the intestinal microbiota in patients with chronic schistosomiasis japonica and identify potential biomarkers that could aid diagnosis.MethodsA total of 40 residents of Qingshan Island in Yueyang (Hunan, China) were enrolled in this cross-sectional study. These individuals were divided into two groups for analysis of the intestinal microbiota: patients with chronic schistosomiasis japonica-induced liver fibrosis group (CSJ group, n = 10) and a healthy control group (HC group, n = 30). Feces were collected from each participant and analyzed by 16S rRNA gene sequencing, which included species composition analysis at the phylum and family levels, α and β diversity analysis, LEfSe, Kyoto Encyclopedia of Genes and Genome (KEGG) and Clusters of Orthologous Groups of proteins (COG) analysis.ResultsOur results indicated that Schistosoma japonicum infection changed the composition and abundance of intestinal microbiota at the phylum and family levels. Compared with the HC group, the α and β diversity results showed that CSJ group had low diversity of species of the intestinal microbiome. LEfSe and relative abundance analysis found that the Prevotella 7, Alloprevotella, and Holdemanella genera were significantly higher in the CSJ group than in the HC group. Meanwhile, the ROC analysis showed that the area under the curve (AUC) of Prevotella 7, Alloprevotella, and Holdemanella genera was 0.779, 0.769, and 0.840, respectively. KEGG and COG analysis showed that the Replication and Repair, and Defense Mechanism pathways correlated strongly with chronic schistosomiasis japonica infection.ConclusionThe current study was the first to explore differences in the intestinal microbiota of patients with chronic schistosomiasis japonica-induced liver fibrosis and healthy people from Qingshan Island, which indicated that Prevotella 7, Alloprevotella, and Holdemanella genera could have a potential value in non-invasive diagnosis of chronic schistosomiasis japonica-induced fibrosis.

Background During hepatic ischemia-reperfusion injury, the excessive release of inflammatory cytokines can activate the intracellular signal transduction cascade to induce hepatocyte injury. Apoptosis is an important way of cell death after I/R injury. Berberine, a common quaternary ammonium alkaloid, has anti-inflammatory, anti-oxidative stress, and anti-apoptotic effects. An increasing number of studies have revealed the importance of non-coding RNAs, including microRNA, long non-coding RNAs and circular RNAs (circRNAs), as regulators of the effects of berberine. Purpose In this study, we investigated the mechanism of berberine against liver ischemia-reperfusion injury in vitro. Study Design and Methods In this study, hypoxia-reoxygenation (H/R)-treated L02 cells were pretreated with berberine to study the role and mechanism of berberine in resisting hepatic ischemia-reperfusion injury. Results The results show that berberine pre-treatment increased the cell viability of H/R-challenged cells, reduced H/R-induced apoptosis and ROS production, reversed H/R-increased on IL-6, IL-1β, TNF-α, and H/R-decreased IL-10 expression. Mechanically, berberine protect hepatocyte from H/R injury, at least partially, through circDNTTIP2. In addition, circDNTTIP2 can bind to the TATA box of caspase3 promoter, thereby promoting caspase 3-related cell apoptosis and the release of inflammatory cytokines. Conclusion This study found that berberine has a protective effect on H/R-induced hepatocyte damage by inhibiting a novel circRNA, circDNTTIP2. This study provides potential treatment strategies and treatment targets for liver ischemia-reperfusion injury.

Based on drilling geological, geochemical, geophysical and production test data, the characteristics of source rocks, reservoir rocks and caprocks, as well as the process of hydrocarbon generation, trap evolution and oil accumulation of the oil-bearing assemblage composed of the Cretaceous Yingcheng Formation (K1yc) and Denglouku Formation (K1d) in the Shuangcheng area, northern Songliao Basin, NE China, were analyzed by using the research methods for petroleum systems. The source rocks mainly exist in K1yc, with the organic matters mainly originated from lower aquatic organisms and algae, and reaching the grade of high-quality source rock in terms of organic abundance. The crude oil, which is characterized by low density, high freezing point and high wax content, is believed to have generated by the K1yc source rocks. The reservoir rocks include K1d sandstones and K1yc glutenites. The mudstone in the fourth member of K1d serves as the direct caprock of the oil reservoir. The oil was generated during the period between Yaojia Formation and Nenjiang Formation, and then accumulated during the periods of Nenjiang Formation and Paleogene–Neogene. The traps evolved in three stages: the late Yingcheng Formation, the late Quantou Formation and the late Nenjiang Formation, forming structural and structural-lithologic reservoirs. It is concluded that good source-reservoir-caprock assemblage, late hydrocarbon charging, short migration distance and stable tectonic setting are favorable factors for the formation of oil reservoirs.

Audio denoising is a task to improve the perceptual quality of noisy audio signals. There is still residual noise after the denoising of noisy signals, which will affect the quality of audio data. Traditional and deep learning-based methods are still limited to the manual addition of artificial noise or low-frequency noise. Recently, audio denoising has been transformed into an image segmentation problem, and deep neural networks have been applied to solve this problem. However, its performance is limited to shallow image segmentation models. This paper proposes a novel vision transformer model for visual bird sound denoising, combining a pyramid transformer and DeepLabV3+ network (named PtDeepLab) to filter out the noise. The proposed PtDeepLab model is based on the pyramid transformer, which generates long-range and multi-scale representations. The PtDeepLab model can achieve intuitive noise reduction in audio, which helps to separate clean audio from the mixture signal. Extensive experimental results showed that the proposed model has a better denoising performance than state-of-the-art methods.

Abstract Background Schistosoma japonicum infection is an important public health problem, imposing heavy social and economic burdens in 78 countries worldwide. However, the mechanism of transition from chronic to advanced S. japonicum infection remains largely unknown. Evidences suggested that gut microbiota plays a role in the pathogenesis of S. japonicum infection. However, the composition of the gut microbiota in patients with chronic and advanced S. japonicum infection is not well defined. In this study, we compared the composition of the intestinal flora in patients with chronic and advanced S. japonicum infection. Methods The feces of 24 patients with chronic S. japonicum infection and five patients with advanced S. japonicum infection from the same area were collected according to standard procedures, and 16S rRNA sequencing technology was used to analyze the intestinal microbial composition of the two groups of patients. Results We found that alteration occurs in the gut microbiota between the groups of patients with chronic and advanced S. japonicum infections. Analysis of alpha and beta diversity indicated that the diversity and abundance of intestinal flora in patients with advanced S. japonicum infection were lower than those in patients with chronic S. japonicum infection. Furthermore, Prevotella 9, Subdoligranulum, Ruminococcus torques, Megamonas and Fusicatenibacter seemed to have potential to discriminate different stages of S. japonicum infection and to act as biomarkers for diagnosis. Function prediction analysis revealed that microbiota function in the chronic group was focused on translation and cell growth and death, while that in the advanced group was concentrated on elevating metabolism-related functions. Conclusions Our study demonstrated that alteration in gut microbiota in different stages of S. japonicum infection plays a potential role in the pathogenesis of transition from chronic to advanced S. japonicum infection. However, further validation in the clinic is needed, and the underlying mechanism requires further study.

Molecular level control is required to capture the folding and supramolecular assembly of collagen in mimetic materials. Here, the authors report on the creation of a synthetic collagen which assembles into banded fibers, recaptures structural properties of natural collagen and which can act as a testbed for design and experimentation

Polar format algorithm (PFA) is a widely used high-resolution SAR imaging algorithm that can be implemented in advanced widefield staring synthetic aperture radar (WFS-SAR). However, existing algorithms have limited analysis in wavefront curvature error (WCE) and are challenging to apply to WFS-SAR with high-resolution and large-swath scenes. This paper proposes an extended polar format algorithm for joint envelope and phase error correction in WFS-SAR imaging with maneuvering trajectory. The impact of the WCE and residual acceleration error (RAE) are analyzed in detail by deriving the specific wavenumber domain signal based on the mapping relationship between the geometry space and wavenumber space. Subsequently, this paper improves the traditional WCE compensation function and introduces a new range cell migration (RCM) recalibration function for joint envelope and phase error correction. The 2D precisely focused SAR image is acquired based on the spatially variant inverse filtering in the final. Simulation experiments validate the effectiveness of the proposed method.

Abstract Background Liver fibrosis is thought to have a close relationship with lipid profile. The possible association between lipids and liver fibrosis of different etiologies has been widely explored. However, the association between lipids and liver fibrosis in patients infected with Schistosoma japonicum remains unclear. In the present study we undertook a preliminary exploration of the association between lipid profile and liver fibrosis, and developed a new predictive index for liver fibrosis in S. japonicum-infected patients. Methods A total of 1503 patients diagnosed with S. japonicum at Xiangyue Hospital, China were enrolled in this retrospective study. The patients were divided into two groups, i.e., those with and those without liver fibrosis, by two experienced schistosomiasis specialists, according to the results of liver ultrasound examination. Demographic, clinical, and laboratory data were collected. Multivariable logistic models were used to estimate the independent associations between lipid profile and liver fibrosis. Receiver operating characteristic (ROC) curves were used to assess the discriminative ability of the new index in predicting liver fibrosis in patients with schistosomiasis. Results Logistic regression analysis showed that high-density lipoprotein (HDL) [adjusted odds ratio (aOR), 95% confidence interval (CI) 7.334, 5.051–10.649; P

Abstract Two-dimensional high-throughput data have become increasingly common in functional genomics studies, which raises new challenges in data analysis. Here, we introduce a new statistic called Zeta, initially developed to identify global splicing regulators from a two-dimensional RNAi screen, a high-throughput screen coupled with high-throughput functional readouts, and ZetaSuite, a software package to facilitate general application of the Zeta statistics. We compare our approach with existing methods using multiple benchmarked datasets and then demonstrate the broad utility of ZetaSuite in processing public data from large-scale cancer dependency screens and single-cell transcriptomics studies to elucidate novel biological insights.

Sinter composition optimization is an important process of iron and steel companies. To increase companies’ profits, they often rely on innovative technology or the workers’ operating experience to improve final productions. However, the former is costly because of patents, and the latter is error-prone. In addition, traditional linear programming optimization methods of sinter compositions are inefficient in the face of large-scale problems and complex nonlinear problems. In this paper, we are the first to propose a regressive convolutional neural network (RCNN) approach for the sinter composition optimization (SCORN). Our SCORN is a single input and multiple outputs regression model. Sinter plant production is used as the input of the SCORN model, and the outputs are the optimized sintering compositions. The SCORN model can predict the optimal sintering compositions to reduce the input of raw materials consumption to save costs and increase profits. By constructing a new neural network structure, the RCNN model is trained to increase its feature extraction capability for sintering production. The SCORN model has a better performance compared with several regressive approaches. The practical application of this predictive model can not only formulate corresponding production plans without feeding materials but also give better input parameters of sintered raw materials during the sintering process.

Background/Aims Binge drinking leads to many disorders, including alcoholic hepatosteatosis, which is characterized by intrahepatic neutrophil infiltration and increases the risk of hepatocellular carcinoma (HCC). Molecular mechanisms may involve the migration of bacterial metabolites from the gut to the liver and the activation of neutrophil extracellular traps (NETs). Methods Serum samples from both binge drinking and alcohol-avoiding patients were analyzed. Mouse models of chronic plus binge alcohol-induced hepatosteatosis and HCC models were used. Results A marker of NETs formation, lipopolysaccharide (LPS), was significantly higher in alcoholic hepatosteatosis and HCC patients and mice than in controls. Intrahepatic inflammation markers and HCC-related cytokines were decreased in mice with reduced NET formation due to neutrophil elastase (NE) deletion, and liver-related symptoms of alcohol were also alleviated in NE knockout mice. Removal of intestinal bacteria with antibiotics led to decreases in markers of NETs formation and inflammatory cytokines upon chronic alcohol consumption, and development of alcoholic hepatosteatosis and HCC was also attenuated. These functions were restored upon supplementation with the bacterial product LPS. When mice lacking toll-like receptor 4 (TLR4) received chronic alcohol feeding, intrahepatic markers of NETs formation decreased, and hepatosteatosis and HCC were alleviated. Conclusions Formation of NETs following LPS stimulation of TLR4 upon chronic alcohol use leads to increased alcoholic steatosis and subsequent HCC.

Abstract Fusarium crown rot and wheat sharp eyespot are major soil-borne diseases of wheat, causing serious losses to wheat yield in China. We applied high-throughput sequencing combined with qPCR to determine the effect of winter wheat seed dressing, with either Trichoderma atroviride HB20111 spore suspension or a chemical fungicide consisting of 6% tebuconazole, on the fungal community composition and absolute content of pathogens Fusarium pseudograminearum and Rhizoctonia cerealis in the rhizosphere at 180 days after planting. The results showed that the Trichoderma and chemical fungicide significantly reduced the amount of F. pseudograminearum in the rhizosphere soil (p

BackgroundLeft ventricular hypertrophy (LVH) is the most frequent cardiac complication among end-stage kidney disease (ESKD) patients, which has been identified as predictive of adverse outcomes. Emerging evidence has suggested that immune system is implicated in the development of cardiac hypertrophy in multiple diseases. We applied machine learning models to exploring the relation between immune status and LVH in ESKD patients.MethodsA cohort of 506 eligible patients undergoing immune status assessment and standard echocardiography simultaneously in our center were retrospectively analyzed. The association between immune parameters and the occurrence of LVH were evaluated through univariate and multivariate logistic analysis. To develop a predictive model, we utilized four distinct modeling approaches: support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP), and random forest (RF).ResultsIn comparison to the non-LVH group, ESKD patients with LVH exhibited significantly impaired immune function, as indicated by lower cell counts of CD3+ T cells, CD4+ T cells, CD8+ T cells, and B cells. Additionally, multivariable Cox regression analysis revealed that a decrease in CD3+ T cell count was an independent risk factor for LVH, while a decrease in NK cell count was associated with the severity of LVH. The RF model demonstrated superior performance, with an average area under the curve (AUC) of 0.942.ConclusionOur findings indicate a strong association between immune parameters and LVH in ESKD patients. Moreover, the RF model exhibits excellent predictive ability in identifying ESKD patients at risk of developing LVH. Based on these results, immunomodulation may represent a promising approach for preventing and treating this disease.

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease (CKD) and a growing public health problem worldwide. Losartan potassium (Los), an angiotensin II receptor blocker, has been used to treat DKD clinically. Recently, multi-herbal formula has been shown to exhibit therapeutic activities in DKD in China. Thus, we aimed to explore the protective effects of combination of Los and Qi-Bang-Yi-Shen formula (QBF) on DKD rats. Streptozotocin (STZ) injection was used to establish a rat model of DKD. Next, the bloodurea nitrogen (BUN), creatinine (CRE) and uric acid (UA) levels were detected in serum samples from DKD rats. Hematoxylin and eosin (H&E), periodic Acid Schiff (PAS) and Masson staining were performed to observe glomerular injury and glomerular fibrosis in DKD rats. In this study, we found that QBF or Los treatment could decrease serum BUN, CRE, UA levels and reduce urine albumin-to-creatinine ratio (ACR) in DKD rats. Additionally, QBF or Los treatment obviously inhibited glomerular mesangial expansion and glomerular fibrosis, attenuated glomerular injury in kidney tissues of DKD rats. Moreover, QBF or Los treatment significantly reduced PI3K, AKT and ERK1/2 protein expressions, but increased PPARγ level in kidney tissues of DKD rats. As expected, combined treatment of QBF and Los could exert enhanced reno-protective effects compared with the single treatment. Collectively, combination of QBF and Los could ameliorate renal injury and fibrosis in DKD rats via regulating PI3K/AKT, ERK and PPARγ signaling pathways. These findings highlight the therapeutic potential of QBF to prevent DKD progression.

Abstract Deep learning (DL) is currently revolutionizing peptide drug development due to both computational advances and the substantial recent expansion of digitized biological data. However, progress in oligopeptide drug development has been limited, likely due to the lack of suitable datasets and difficulty in identifying informative features to use as inputs for DL models. Here, we utilized an unsupervised deep learning model to learn a semantic pattern based on the intrinsically disordered regions of ~171 known osteogenic proteins. Subsequently, oligopeptides were generated from this semantic pattern based on Monte Carlo simulation, followed by in vivo functional characterization. A five amino acid oligopeptide (AIB5P) had strong bone-formation-promoting effects, as determined in multiple mouse models (e.g., osteoporosis, fracture, and osseointegration of implants). Mechanistically, we showed that AIB5P promotes osteogenesis by binding to the integrin α5 subunit and thereby activating FAK signaling. In summary, we successfully established an oligopeptide discovery strategy based on a DL model and demonstrated its utility from cytological screening to animal experimental verification.

Objective: Disuse osteoporosis is a major type of bone loss disease characterized by regional bone loss and microstructure alterations. The condition is induced by a marked decrease in weight bearing over time, which usually occurs due to limb immobilization, therapeutic bed rest or space flight. To date, the most commonly used mouse model of disuse osteoporosis is constructed using the classical tail suspension method, which causes tail injury, movement inconvenience and mental stress. This study aimed to propose a noninvasive and effective method for the establishment of a mouse model of disuse osteoporosis and compared this method with the tail suspension method. Methods: 3D printing technology was applied to construct a movable unloading device. A movable noninvasive 3D-printed unloading device (3D-ULD) was used to unload the hindlimbs of the mice. The bone microstructure and bone volume of unloaded femurs were analysed through micro-CT and H&E staining, and von Kossa staining was performed for the detection of bone mineralization in the femurs. TRAP staining, IHC-CTSK and Q-PCR were performed for evaluation of the bone resorption ability, and double labelling, IHC-DMP1, ALP staining and Q-PCR assays were conducted to assess the osteogenic ability. The mechanical properties of disused bone were detected using the three-point bending test. The body, thymus and spleen weights of the mice were recorded, and the serum corticosterone level of the mice was assayed by enzyme-linked immunosorbent assay (ELISA). Results: The micro-CT results showed significant trabecular bone loss, and 3D-ULD induced cortical bone loss in disused femurs as well as a decrease in the bone mineral density in the unloaded mice. TRAP staining and IHC-CTSK staining results indicated increases in the osteoclast number per bone perimeter (Oc.N/B.Pm) and the osteoclast surface per bone surface (Oc.S/BS) in the unloaded mice. The Ctsk, Trap and Mmp9 expression levels were significantly increased in the unloaded mice. Decreases in the ratio of the mineral surface to bone surface (MS/BS), mineral apposition rate (MAR) and bone formation rate per bone surface (BFR/BS) were found in unloaded mice in the 3D-ULD by double labelling. The IHC-DMP1 and ALP staining results showed decreases in the osteoblast number per bone perimeter (Ob.N/B.Pm) and osteoblast surface per bone surface (Ob. S/BS) in the mice unloaded in the 3D-ULD, and these mice also showed decreased Runx2, Alp and Dmp1 expression levels. Three-point bending test results showed that the mechanical properties were attenuated in the disused femurs of the unloaded mice. Less skin rupture and rare alterations in the thymus and spleen weights were found in the unloaded mice in the 3D-ULD. The ELISA results indicated the serum corticosterone level of the mice unloaded in the 3D-ULD was significantly lower than that of mice suspended by their tail. Conclusion: This new disuse osteoporosis mouse model based on 3D-ULD could induce effective disuse bone loss with significantly alleviated side effects. Translational potential of this article: This study proposes a new disuse osteoporosis mouse model based on 3D-ULD that can be used to better understand disuse bone loss in the future.

The road transportation of explosives is highly concerning due to its substantial impact on social safety. For the safety management of explosive transportation, e.g., transport route planning and emergency rescue, explosion consequence evaluation is of paramount importance. The consequence evaluation of explosion accidents is affected by many factors, especially spatial features, such as the location of transport vehicles, the distribution of buildings, and the presence of individuals around the road, etc. However, there is still a lack of quantification methods for building damage evaluation, human casualty evaluation that considers real-time population density, and efficient interactive damage evaluation methods. In this paper, we formalize three typical scenarios of damage evaluation for explosive road transportation accidents, i.e., explosion point-based, road segment-based, and route-based damage evaluation. For each scenario, we propose a Height-aware Hierarchical Building Damage (HHBD) model and a Shelter-aware Human Casualty (SHC) model for building damage evaluation and human casualty evaluation, respectively. We also develop a GIS-based interactive visualization platform that integrates multi-source geospatial data and that enables efficient geospatial computation. In addition, a case study of liquefied natural gas (LNG) transportation in Wuhan is demonstrated in order to verify the effectiveness and efficiency of the proposed system. The research results can support the decision-making process of explosive transportation safety warnings and emergency rescue.

Pectobacterium brasiliense (Pbr) has caused significant economic losses in major vegetable production areas in Northern China by causing bacterial soft rot in cash crops such as potatoes and cucumbers. This study aimed to establish a PMA-qPCR detection method for Pbr by screening specific and sensitive primers based on the glu gene and the conserved region of the 23S rRNA gene. Based on the optimized PMA pretreatment conditions, a standard curve was designed and constructed for PMA-qPCR detection (y = −3.391x + 36.28; R2 = 0.99). The amplification efficiency reached 97%, and the lowest detection limit of viable cells was approximately 2 × 102 CFU·mL−1. The feasibility of the PMA-qPCR method was confirmed through a manually simulated viable/dead cell assay under various concentrations. The analysis of potato tubers and cucumber seeds revealed that nine naturally collected seed samples contained a range from 102 to 104 CFU·g−1 viable Pbr bacteria. Furthermore, the system effectively identified changes in the number of pathogenic bacteria in cucumber and potato leaves affected by soft rot throughout the disease period. Overall, the detection and prevention of bacterial soft rot caused by Pbr is crucial.

Abstract Background Perineural invasion (PNI) and autophagy are two common features in the tumor microenvironment of pancreatic cancer (PanCa) and have a negative effect on prognosis. Potential mediator cells and the molecular mechanism underlying their relationships need to be fully elucidated. Methods To investigate the autophagy of Schwann cells (SCs) in PNI, we reproduced the microenvironment of PNI by collecting clinical PNI tissue, performing sciatic nerve injection of nude mice with cancer cells and establishing a Dorsal root ganglion (DRG) coculture system with cancer cell lines. Autophagy was detected by IHC, IF, transmission electron microscopy (TEM) and western blotting assays. Apoptosis was detected by IF, TEM and western blotting. NGF targeting molecular RO 08–2750(RO) and the autophagy inhibitor Chloroquine (CQ) were utilized to evaluate the effect on autophagy and apoptosis in SCs and PanCa cells in PNI samples. Results SC autophagy is activated in PNI by paracrine NGF from PanCa cells. Autophagy-activated Schwann cells promote PNI through a) enhanced migration and axon guidance toward PanCa cells and b) increased chemoattraction to PanCa cells. The NGF-targeting reagent RO and autophagy inhibitor CQ inhibited Schwann cell autophagic flux and induced Schwann cell apoptosis. Moreover, RO and CQ could induce PanCa cell apoptosis and showed good therapeutic effects in the PNI model. Conclusions PanCa cells can induce autophagy in SCs through paracrine pathways such as the NGF/ATG7 pathway. Autophagic SCs exert a “nerve-repair like effect”, induce a high level of autophagy of cancer cells, provide a “beacon” for the invasion of cancer cells to nerve fibers, and induce directional growth of cancer cells. Targeting NGF and autophagy for PNI treatment can block nerve infiltration and is expected to provide new directions and an experimental basis for the research and treatment of nerve infiltration in pancreatic cancer.