Investigation of U.S. landfill GHG reporting program methane emission models.

As part of its commitment to the United Nations Framework Convention on Climate Change, the U.S. annually develops a national estimate of methane emissions from municipal solid waste (MSW) landfills by aggregating activity data from each facility. Since 2010, the U.S. has reported a 20 % decrease in MSW landfill emissions despite a 21 % increase in tons disposed. Operator-submitted data were investigated to understand the causes of this decline. In the U.S., operators of landfills with a gas collection and control system (GCCS) calculate their facility's emissions via two separate approaches - (1) first-order decay (FOD) and (2) collection efficiency assumption (CEA) - and select either result to feed into the annual inventory. The FOD model predicts methane generation proportional to waste disposal and that approach calculated a 19 % increase in total methane generated from 2010 to 2022, whereas generation via the CEA approach decreased by 8.9 %. The amount of measured methane collected has increased 7.5 % for the same years. Discrepancies between the two models' generated methane, assumed gas collection efficiencies, and oxidized methane compound into substantive differences in national estimates. Operators more frequently select the CEA method, which results in decreased national estimates. If only the FOD method was used, U.S. MSW landfill emissions would be 1.3-1.7 times greater than current estimates which is similar to recent extrapolations from remote sensing campaigns in the U.S. Both models contain parameters with large inherent uncertainty. Without measurement methods that continuously quantify both point-source and diffuse emissions, an assessment of either equation's accuracy cannot be made.

A versatile dilution-treatment-detection microfluidic chip platform for rapid In vitro lung cancer drug combination sensitivity evaluation.

Combination drug therapy represents an effective strategy for treating certain drug-resistant and intractable cancer cases. However, determining the optimal combination of drugs and dosages is challenging due to clonal diversity in patients' tumors and the lack of rapid drug sensitivity evaluation methods. Microfluidic technology offers promising solutions to this issue. In this study, we propose a versatile microfluidic chip platform capable of integrating all processes, including dilution, treatment, and detection, for in vitro drug sensitivity assays. This platform innovatively incorporates several modules, including automated discrete drug logarithmic concentration generation, on-chip cell perfusion culture, and parallel drug treatments of cancer cell models. Moreover, it is compatible with microplate readers or high-content imaging systems for swift detection and automated monitoring, simplifying on-chip drug evaluation. Proof of concept is demonstrated by assessing the in vitro potency of two drugs, cisplatin, and etoposide, against the lung adenocarcinoma A549 cell line, under both single-drug and combination treatment conditions. The findings reveal that, compared to conventional microplate approaches with static cultivation, this on-chip automated perfusion bioassays yield comparable IC50 values with lower variation and a 50 % reduction in drug preparation time. This versatile dilution-treatment-detection microfluidic platform offers a promising tool for rapid and precise drug assessments, facilitating in vitro drug sensitivity evaluation in personalized cancer chemotherapy.

Impacts of free nitrous acid on stabilizing food waste and sewage sludge for anaerobic digestion.

This work investigated the effectiveness of free nitrous acid (FNA) in enhancing organic waste solubilization to improve biogas production in anaerobic digestion (AD). The results indicated that FNA pretreatment can enhance soluble organic content and control H2S odor in tested organic wastes, including food waste, sewage sludge, and their combination. However, a significant decrease (>50 %) in FNA concentration was found in the reactors, possibly due to denitrifier-driven NO2- consumption. Biochemical methane potential (BMP) tests showed a 25 ± 8 % enhancement in CH4 production in the reactors fed with mixed substrate pretreated with 2.9 mg FNA-N/L. However, the presence of NO2- (325.6-2368.0 mg N/L) in some BMP reactors, due to carryover from FNA pretreatment, adversely affected CH4 production (>55 %) and prolonged lag time (>4.2 times). These findings are valuable for researchers and practitioners in waste management, offering insights for implementing FNA pretreatment to enhance the biodegradability of organic wastes in AD.

Sorption and diffusion of per-polyfluoroalkyl substances (PFAS) in high-density polyethylene geomembranes.

The objective of this study is to investigate the fate and transport of per-polyfluoroalkyl substances (PFAS) through a high-density polyethylene (HDPE) geomembrane (GM) that is commonly used in landfill composite liner systems. Tests were conducted to measure the sorption and diffusion of per-polyfluoroalkyl substances (PFAS) with varying number of carbons in chain and functional groups on HDPE GM. Perfluoroalkyl carboxyl acids (PFCAs), perfluoroalkyl sulphonic acids (PFSAs), alkyl-sulfonamidoacetic acids (FOSAAs), fluorotelomer sulfonic acids (FtSAs), alkane sulfonamides (FOSA) and ether carboxylic acids (Gen X) were investigated in this study. The partition coefficients (Kd) on HDPE GM ranged from 3.8 to 98.3 L/kg. PFAS with amide and sulfonic functional groups showed stronger sorption than that of PFAS with carboxylic acid functional groups. Molecular weight directly affected the Kd for long-chained PFAS whereas the Kd of short-chained PFAS was not sensitive to molecular weight. The diffusion coefficients (Dg) of PFCAs and PFSAs through 0.1-mm HDPE GM were found to be in the orders of 10-18 to 10-17 m2/s. The Dg decreased with increasing molar mass and were also observed to be dependent on the functional group. Dg of PFSAs was lower than that of PFCAs for similar number of carbons in the chain. The estimated mass flux for PFAS in an intact 1.5-mm HDPE GM varied from 38.7 to 2080.8 ng/m2/year whereas the estimated diffusive breakthrough time for PFAS in intact 1.5-mm HDPE was 1526 years or longer.

Identification of potential immune-related hub genes in Parkinson's disease based on machine learning and development and validation of a diagnostic classification model.

BACKGROUND: Parkinson's disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown. This study aimed to search for potential immune-related hub genes in Parkinson's disease, find relevant immune infiltration patterns, and develop a categorical diagnostic model. METHODS: We downloaded the GSE8397 dataset from the GEO database, which contains gene expression microarray data for 15 healthy human SN samples and 24 PD patient SN samples. Screening for PD-related DEGs using WGCNA and differential expression analysis. These PD-related DEGs were analyzed for GO and KEGG enrichment. Subsequently, hub genes (dld, dlk1, iars and ttd19) were screened by LASSO and mSVM-RFE machine learning algorithms. We used the ssGSEA algorithm to calculate and evaluate the differences in nigrostriatal immune cell types in the GSE8397 dataset. The association between dld, dlk1, iars and ttc19 and 28 immune cells was investigated. Using the GSEA and GSVA algorithms, we analyzed the biological functions associated with immune-related hub genes. Establishment of a ceRNA regulatory network for immune-related hub genes. Finally, a logistic regression model was used to develop a PD classification diagnostic model, and the accuracy of the model was verified in three independent data sets. The three independent datasets are GES49036 (containing 8 healthy human nigrostriatal tissue samples and 15 PD patient nigrostriatal tissue samples), GSE20292 (containing 18 healthy human nigrostriatal tissue samples and 11 PD patient nigrostriatal tissue samples) and GSE7621 (containing 9 healthy human nigrostriatal tissue samples and 16 PD patient nigrostriatal tissue samples). RESULTS: Ultimately, we screened for four immune-related Parkinson's disease hub genes. Among them, the AUC values of dlk1, dld and ttc19 in GSE8397 and three other independent external datasets were all greater than 0.7, indicating that these three genes have a certain level of accuracy. The iars gene had an AUC value greater than 0.7 in GES8397 and one independent external data while the AUC values in the other two independent external data sets ranged between 0.5 and 0.7. These results suggest that iars also has some research value. We successfully constructed a categorical diagnostic model based on these four immune-related Parkinson's disease hub genes, and the AUC values of the joint diagnostic model were greater than 0.9 in both GSE8397 and three independent external datasets. These results indicate that the categorical diagnostic model has a good ability to distinguish between healthy individuals and Parkinson's disease patients. In addition, ceRNA networks reveal complex regulatory relationships based on immune-related hub genes. CONCLUSION: In this study, four immune-related PD hub genes (dld, dlk1, iars and ttd19) were obtained. A reliable diagnostic model for PD classification was developed. This study provides algorithmic-level support to explore the immune-related mechanisms of PD and the prediction of immune-related drug targets.

Identifying Vital Nodes in Hypergraphs Based on Von Neumann Entropy.

Hypergraphs have become an accurate and natural expression of high-order coupling relationships in complex systems. However, applying high-order information from networks to vital node identification tasks still poses significant challenges. This paper proposes a von Neumann entropy-based hypergraph vital node identification method (HVC) that integrates high-order information as well as its optimized version (semi-SAVC). HVC is based on the high-order line graph structure of hypergraphs and measures changes in network complexity using von Neumann entropy. It integrates s-line graph information to quantify node importance in the hypergraph by mapping hyperedges to nodes. In contrast, semi-SAVC uses a quadratic approximation of von Neumann entropy to measure network complexity and considers only half of the maximum order of the hypergraph's s-line graph to balance accuracy and efficiency. Compared to the baseline methods of hyperdegree centrality, closeness centrality, vector centrality, and sub-hypergraph centrality, the new methods demonstrated superior identification of vital nodes that promote the maximum influence and maintain network connectivity in empirical hypergraph data, considering the influence and robustness factors. The correlation and monotonicity of the identification results were quantitatively analyzed and comprehensive experimental results demonstrate the superiority of the new methods. At the same time, a key non-trivial phenomenon was discovered: influence does not increase linearly as the s-line graph orders increase. We call this the saturation effect of high-order line graph information in hypergraph node identification. When the order reaches its saturation value, the addition of high-order information often acts as noise and affects propagation.

Garcinol protects SH-SY5Y cells against MPP+-induced cell death by activating DJ-1/SIRT1 and PGC-1α mediated antioxidant pathway in sequential stimulation of p-AMPK mediated autophagy.

Parkinson's disease (PD), a chronic and progressive neurodegenerative disease, can reduce the population of dopaminergic neurons in the substantia nigra. The cause of this neuronal death remains unclear. 1-Methyl-4-phenylpyridinium ion (MPP+) is a potent neurotoxin that can destroy dopaminergic (DA) neurons and promote PD. Garcinol, a polyisoprenylated benzophenone derivative, was extracted from Garcinia indica and is an important active compound it has been used as an anticancer, antioxidant, and anti-inflammatory, agent and it can suppress reactive oxygen species (ROS) mediated cell death in a PD model. Human neuroblastoma (SH-SY5Y) cells (1 × 105 cells) were treated with MPP+ (1 mM) for 24 h to induce cellular ROS production. The formation of ROS was suppressed by pretreatment with different concentrations of garcinol (0.5 and 1.0 µM) for 3 h in SH-SY5Y cells. The present study found that MPP+ treatment increased the formation of reactive oxygen species (ROS), and the increased ROS began to promote cell death in SH-SY5Y cells. However, our natural compound garcinol effectively blocked MPP+-mediated ROS formation by activating the DJ-1/SIRT1 and PGC-1α mediated antioxidant pathway. Further findings indicate that the activated SIRT1 can also regulate p-AMPK-mediated autophagy to protect the neurons from the damage it concludes that garcinol sub-sequential regulates intracellular autophagy in this model, and the productive efficacy of garcinol was confirmed by western blot analysis and MitoSOX DCFDA and MTT assays. The results showed garcinol increased protection due to the prevention of MPP+-induced ROS and the promotion of cell survival.

Hydraulic conductivity of GCL overlap permeated with saline solutions.

Hydraulic conductivity of the overlap region of two needle-punched sodium bentonite (Na-B) geosynthetic clay liners (GCLs) permeated with CaCl2 solutions under confining stresses of 20, 100, 250, and 500 kPa were evaluated. One of the GCLs consisted of a uniform layer of Na-B encapsulated between a nonwoven (NW) and a woven (W) geotextile, and the other one consisted of NW geotextiles on both sides. Supplemental bentonite was placed within the overlap region. Experiments were conducted with 10, 20, and 50 mM CaCl2 solutions representing dilute and aggressive leachates. The results indicate that in most of the scenarios there is a possibility that the flow is not completely vertical (meaning flow passes through the overlap region horizontally). As the confining stress increased, the horizontal flow through the overlap region for GCLs reduced effectively when permeated with deionized water and 10 mM CaCl2 solution, whereas the reduction of horizontal flow was limited to 20 mM and 50 mM CaCl2 solutions.

Identification of circulating immune landscape in ischemic stroke based on bioinformatics methods.

Ischemic stroke (IS) is a high-incidence disease that seriously threatens human life and health. Neuroinflammation and immune responses are key players in the pathophysiological processes of IS. However, the underlying immune mechanisms are not fully understood. In this study, we attempted to identify several immune biomarkers associated with IS. We first retrospectively collected validated human IS immune-related genes (IS-IRGs) as seed genes. Afterward, potential IS-IRGs were discovered by applying random walk with restart on the PPI network and the permutation test as a screening strategy. Doing so, the validated and potential sets of IS-IRGs were merged together as an IS-IRG catalog. Two microarray profiles were subsequently used to explore the expression patterns of the IS-IRG catalog, and only IS-IRGs that were differentially expressed between IS patients and controls in both profiles were retained for biomarker selection by the Random Forest rankings. CLEC4D and CD163 were finally identified as immune biomarkers of IS, and a classification model was constructed and verified based on the weights of two biomarkers obtained from the Neural Network algorithm. Furthermore, the CIBERSORT algorithm helped us determine the proportions of circulating immune cells. Correlation analyses between IS immune biomarkers and immune cell proportions demonstrated that CLEC4D was strongly correlated with the proportion of neutrophils (r = 0.72). These results may provide potential targets for further studies on immuno-neuroprotection therapies against reperfusion injury.

Identification of diagnostic signatures associated with immune infiltration in Alzheimer's disease by integrating bioinformatic analysis and machine-learning strategies.

Objective: As a chronic neurodegenerative disorder, Alzheimer's disease (AD) is the most common form of progressive dementia. The purpose of this study was to identify diagnostic signatures of AD and the effect of immune cell infiltration in this pathology. Methods: The expression profiles of GSE109887, GSE122063, GSE28146, and GSE1297 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between AD and control brain samples. Functional enrichment analysis was performed to reveal AD-associated biological functions and key pathways. Besides, we applied the Least Absolute Shrinkage Selection Operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) analysis to screen potential diagnostic feature genes in AD, which were further tested in AD brains of the validation cohort (GSE5281). The discriminatory ability was then assessed by the area under the receiver operating characteristic curves (AUC). Finally, the CIBERSORT algorithm and immune cell infiltration analysis were employed to assess the inflammatory state of AD. Results: A total of 49 DEGs were identified. The functional enrichment analysis revealed that leukocyte transendothelial migration, cytokine receptor interaction, and JAK-STAT signaling pathway were enriched in the AD group. MAF basic leucine zipper transcription factor F (MAFF), ADCYAP1, and ZFP36L1 were identified as the diagnostic biomarkers of AD with high discriminatory ability (AUC = 0.850) and validated in AD brains (AUC = 0.935). As indicated from the immune cell infiltration analysis, naive B cells, plasma cells, activated/resting NK cells, M0 macrophages, M1 macrophages, resting CD4+ T memory cells, resting mast cells, memory B cells, and resting/activated dendritic cells may participate in the development of AD. Additionally, all diagnostic signatures presented different degrees of correlation with different infiltrating immune cells. Conclusion: MAFF, ADCYAP1, and ZFP36L1 may become new candidate biomarkers of AD, which were closely related to the pathogenesis of AD. Moreover, the immune cells mentioned above may play crucial roles in disease occurrence and progression.

Dissecting and analyzing the Subclonal Mutations Associated with Poor Prognosis in Diffuse Glioma.

The prognostic and therapeutic implications in diffuse gliomas are still challenging. In this study, we first performed an integrative framework to infer the clonal status of mutations in glioblastomas (GBMs) and low-grade gliomas (LGGs) by using exome sequencing data from TCGA and observed both clonal and subclonal mutations for most mutant genes. Based on the clonal status of a given gene, we systematically investigated its prognostic value in GBM and LGG, respectively. Focusing on the subclonal mutations, our results showed that they were more likely to contribute to the poor prognosis, which could be hardly figured out without considering clonal status. These risk subclonal mutations were associated with some specific genomic features, such as genomic instability and intratumor heterogeneity, and their accumulation could enhance the prognostic value. By analyzing the regulatory mechanisms underlying the risk subclonal mutations, we found that the subclonal mutations of AHNAK and AHNAK2 in GBM and those of NF1 and PTEN in LGG could influence some important molecules and functions associated with glioma progression. Furthermore, we dissected the role of risk subclonal mutations in tumor evolution and found that advanced subclonal mutations showed poorer overall survival. Our study revealed the importance of clonal status in prognosis analysis, highlighting the role of the subclonal mutation in glioma prognosis.

Long Non-coding RNA RMST Worsens Ischemic Stroke via MicroRNA-221-3p/PIK3R1/TGF-ß Signaling Pathway.

Much efforts have been made to probe the mechanism underlying ischemic stroke (IS). This study was proposed to uncover the role of long non-coding RNA rhabdomyosarcoma 2 related transcript (RMST) in IS through microRNA-221-3p (miR-221-3p)/phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1)/transforming growth factor-ß (TGF-ß) axis. Neurological behavioral function, pathological changes in brain tissue, oxidative stress, and inflammation responses in middle cerebral artery occlusion (MCAO) mice were tested. RMST, miR-221-3p, PIK3R1, and TGF-ß signaling-related protein expression in brain tissues of MCAO mice were detected. RMST and PIK3R1 were elevated, miR-221-3p was downregulated, and TGF-ß pathway was activated in mice after MCAO. Restored miR-221-3p or depleted RMST improved neurological behavioral functions, relieved pathological injury in brain tissue, and repressed oxidative stress and inflammation in mice after MCAO. Depleted PIK3R1 or restored miR-221-3p offsets the negative effects of overexpressed RMST on mice with MCAO. The present work highlights that RMST augments IS through reducing miR-221-3p-mediated regulation of PIK3R1 and activating TGF-ß pathway.

Effect of incineration ash leachates on the hydraulic conductivity of bentonite-polymer composite geosynthetic clay liners.

A study was conducted to evaluate the hydraulic conductivity (k) of six bentonite-polymer composite (BPC) geosynthetic clay liners (GCLs) using five synthetic municipal solid waste incineration ash (IA) leachates with ionic strength (I) ranging from 174 to1978 mM. The BPC GCLs contained a dry blend of bentonite and proprietary polymers and had polymer loading ranging from 0.5 to 5.5%. The polymers used in the BPC GCLs were classified as linear polymer (LP) or crosslinked polymer (CP) based on the swelling characteristics of specimens extracted from the GCLs. Comparable hydraulic conductivity tests were also performed on two conventional bentonite (CB) GCLs as controls. The BPC GCLs had k of 2.6 - 6.7 × 10-11 m/s when permeated with IA leachate with I = 174 mM, whereas the CB GCLs had k > 5.0 × 10-8 m/s when permeated with the same leachate. However, k of the BPC GCLs ranged from the order of 10-10 to 10-7 m/s when permeated with IA leachates with I > 600 mM. BPC GCLs with high polymer loading generally had lower k compared to those with lower polymer loading when permeated with the same IA leachate, regardless of the polymer type. Polymer eluted from the BPC GCLs containing LP during permeation with DI water or IA leachate. Unlike CPs, LPs are water-soluble, therefore, they seem to easily migrate during permeation. There was no correlation between the percentage of polymer retained and the final hydraulic conductivity of the LPB GCLs used in this study.

Dexmedetomidine exerts cerebral protective effects against cerebral ischemic injury by promoting the polarization of M2 microglia via the Nrf2/HO-1/NLRP3 pathway.

INTRODUCTION: Cerebral ischemic injury is associated with long-term disability. Dexmedetomidine (Dex) can exert neuroprotective effects on cerebral ischemic/reperfusion injury. The present study explored the mechanism of Dex in cerebral ischemic injury. MATERIALS AND METHODS: To this end, the permanent middle cerebral artery occlusion (p-MCAO) mouse model was established and treated with Dex or/and Nrf2 inhibitor ML385. Subsequently, microglia were subjected to oxygen-glucose deprivation (OGD) in sugar-free environment and thereafter treated with Dex, Nrf2 inhibitor, and NLRP3 lentiviral overexpression vector, respectively. RESULTS: Dex alleviated the neurobehavioral deficit of p-MCAO mice, reduced brain water content, relieved pathological changes, and reduced cerebral infarction size. Dex promoted the polarization of microglia from M1 to M2, thus ameliorating oxidative stress and inflammatory responses. Our results showed that Dex promoted M2-polarization of microglia in vivo and in vitro by promoting HO-1 expression via Nrf2 nuclear import. Moreover, the Nrf2/HO-1 axis inhibited the activation of NLRP2 inflammasome and NLRP3 overexpression reversed the effect of Dex. CONCLUSION: In conclusion, Dex promoted M2-polarization of microglia and attenuated oxidative stress and inflammation, and thus protected against cerebral ischemic injury by activating the Nrf2/HO-1 pathway and inhibiting NLRP3 inflammasome.

Complete Restoration of Motor Function in Acute Cerebral Stroke Treated with Allogeneic Human Umbilical Cord Blood Monocytes: Preliminary Results of a phase I Clinical Trial.

Stem cell therapy has been explored for the treatment of cerebral stroke. Several types of stem cells have been investigated to ensure the safety and efficacy in clinical trials.Cryopreserved umbilical cord blood (UCB) mononuclear cells (MNCs) obtained from healthy donors have a more stabilized quality, thereby ensuring a successful therapy. A phase I study was conducted on patients aged 45-80 years who sustained acute ischemic stroke. An UCB unit was obtained from a public cord blood bank based on ABO/Rh blood type, HLA matching score (6/6), and cell dose (total MNC count of 0.5-5 × 107 cells/kg). In addition, to facilitate blood brain barrier penetration of UCB, 4 doses of 100 mL mannitol was administered intravenously after 30 min after UCB transplantation and every 4 h thereafter. The primary outcomes were the number of disease (GVHD) within 100 days after transfusion. The secondary outcomes were changes in the National Institutes of Health Stroke Scale (NIHSS), Barthel index, and Berg Balance Scale scores. A 46-year-old male patient with identical ABO/Rh blood type, HLA matching score of 6/6, and MNC count of 2.63 × 108 cells/kg was enrolled. The patient did not present with serious AEs or GVHD during the 12-month study period. The patient's NIHSS score decreased from 9 to 1. Moreover, the Berg Balance Scale score increased from 0 to 48 and the Barthel index score from 0 to 90. This preliminary study showed that an adult patient with hemiplegia due to ischemic stroke completely recovered within 12 months after receiving allogeneic UCB therapy.

The complete mitogenome and phylogenetic analysis of Indian driftfish, Cubiceps squamiceps (Scombriformes: Nomeidae).

The Indian driftfish (Cubiceps squamiceps) is one of the most important commercial fish species in China, Japan and India. The complete mitogenome of Cubiceps squamiceps was determined in this study. The assembled mitogenome was 16,507 bp and consisted of 13 protein-coding genes, 22 tRNAs, two rRNAs, and a control region. Nucleotide composition of the complete mitogenome was 27.5% A, 28.5% C, 17.5% G, and 26.5% T, with an A + T bias of 53.9%. The maximum-likelihood tree based on 13 protein-coding genes showed that Cubiceps pauciradiatus and Psenes pellucidus were the closest to C. squamiceps.

Characterization of the complete mitochondrial genome of Chrysochir aureus and phylogenetic studies of Sciaenidae.

The complete mitochondrial genome of Chrysochir aureus was sequenced. The full length of the mitochondrial genome was 16,501 bp, including 13 protein-coding genes (PCGs), two ribosomal RNAs, 22 transfer RNA genes, a non-coding control region (CR) and one origin of replication on the light-strand (OL). The total nucleotide composition of mitochondrial DNA was 26.95% A, 29.99% C, 26.29% T, and 16.77% G. Twelve PCGs used the canonical ATG as their initiation codon, whereas COI gene started with an alternative start codon GTG. The mitochondrial genome of C. aureus described in this study could be a useful basis for management of this species and laid a foundation for further research involved with phylogenetic relationship within Sciaenidae.

Simple non-invasive scoring systems and histological scores in predicting mortality in patients with non-alcoholic fatty liver disease: A systematic review and meta-analysis.

BACKGROUND AND AIM: There is debate among the hepatology community regarding the simple non-invasive scoring systems and histological scores (even it was developed for histological classification) in predicting clinical outcomes in patients with non-alcoholic fatty liver disease (NAFLD). This study aimed to determine whether the presence of simple non-invasive scoring systems and histological scores could predict all-cause mortality, liver-related mortality, and liver disease decompensation (liver failure, cirrhosis, hepatocellular carcinoma, or decompensated liver disease). METHODS: The pooled hazard ratio of prognostic factors and incidence rate per 1000 person-years in patients with NAFLD was calculated and further adjusted by two different models of handling the duplicated data. RESULTS: A total of 19 longitudinal studies were included. Most simple non-invasive scoring systems (Fibrosis-4 Score, BARD, and aspartate aminotransferase-to-platelet ratio index ) and histological scores (NAFLD activity score, Brunt, and "steatosis, activity, and fibrosis" ) failed in predicting mortality, and only the NAFLD fibrosis score > 0.676 showed prognostic ability to all-cause mortality (four studies, 7564 patients, 118 352 person-years followed up, pooled hazard ratio 1.44, 95% confidence interval [CI] 1.05-1.96). The incidence rate per 1000 person-years of all-cause mortality, liver-related mortality, cardiovascular-related mortality, and liver disease decompensation resulted in a pooled incidence rate per 1000 person-years of 22.65 (14 studies, 95% CI 9.62-53.31), 3.19 (7 studies, 95% CI 1.14-8.93), 6.02 (6 studies, 95% CI 4.69-7.74), and 11.46 (4 studies, 95% CI 5.33-24.63), respectively. CONCLUSION: Non-alcoholic fatty liver disease fibrosis score showed promising prognostic value to all-cause mortality. Most present simple non-invasive scoring systems and histological scores failed to predict clinical outcomes.

Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF-miRNA-gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF-miRNA, miRNA-gene, TF-gene, miRNA-TF, gene-gene and miRNA-miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MG. In addition, the genes, TFs and miRNAs in the CFMSN were also utilized to identify potential drugs. Five related genes, 3 TFs and 13 miRNAs, were extracted from the CFMSN. As the most important TF in the CFMSN, MYC was inferred to play a critical role in MG. Pathway enrichment analysis showed that the genes and miRNAs in the CFMSN were mainly enriched in pathways related to cancer and infections. Furthermore, 21 drugs were identified through the CFMSN, of which estradiol, estramustine, raloxifene and tamoxifen have the potential to be novel drugs to treat MG. The present study provides MG-related TFs by constructing the CFMSN for further experimental studies and provides a novel perspective for new biomarkers and potential drugs for MG.

Work-Function-Tunable Electron Transport Layer of Molecule-Capped Metal Oxide for a High-Efficiency and Stable p-i-n Perovskite Solar Cell.

The composite electron transporting layer (ETL) of metal oxide with [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) prevents perovskite from metal electrode erosion and increases p-i-n perovskite solar cell (PVSC) stability. Although the oxide exhibits protective function, an additional work function modifier is still needed for good device performance. Usually, complicated multistep synthesis is employed to have a highly crystalline film that increases manufacturing cost and inhibits scalability. We report a facile synthesis of a novel organic-molecule-capped metal oxide nanoparticle film for the composite ETL. The nanoparticle film not only has a dual function of electron transport and protection but also exhibits work function tunability. Solvothermal-prepared SnO2 nanoparticles are capped with tetrabutylammonium hydroxide (TBAOH) through ligand exchange. The resulting TBAOH-SnO2 nanoparticles disperse well in ethanol and form a uniform film on PCBM. The power conversion efficiency of the device dramatically increases from 14.91 to 18.77% using this layer because of reduced charge accumulation and aligned band structure. The PVSC thermal stability is significantly enhanced by adopting this layer, which prevents migration of I- and Ag. The ligand exchange method extends to other metal oxides, such as TiO2, ITO, and CeO2, demonstrating its broad applicability. These results provide a cornerstone for large-scale manufacture of high-performance and stable PVSCs.