An early diagnosis of hepatocellular carcinoma (HCC) followed by effective treatment is currently critical for improving the prognosis and reducing the associated economic burden. Alpha-fetoprotein ...(AFP) is the most widely used biomarker for HCC diagnosis. Based on elevated serum AFP levels as well as typical imaging features, AFP-positive HCC (APHC) can be easily diagnosed, but AFP-negative HCC (ANHC) is not easily detected due to lack of ideal biomarkers and thus mainly reliance on imaging. Imaging for the diagnosis of ANHC is probably insufficient in sensitivity and/or specificity because most ANHC tumors are small and early-stage HCC, and it is involved in sophisticated techniques and high costs. Moreover, ANHC accounts for nearly half of HCC and exhibits a better prognosis compared with APHC. Therefore, the diagnosis of ANHC in clinical practice has been a critical issue for the early treatment and prognosis improvement of HCC. In recent years, tremendous efforts have been made to discover new biomarkers complementary to AFP for HCC diagnosis. In this review, we systematically review and discuss the recent advances of blood biomarkers for HCC diagnosis, including DNA biomarkers, RNA biomarkers, protein biomarkers, and conventional laboratory metrics, focusing on their diagnostic evaluation alone and in combination, in particular on their diagnostic performance for ANHC.
Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot ...effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.
Large‐diameter, tall‐stature, and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence play an important role in climate ...change mitigation strategies. Here, we hypothesized that the effects of large‐diameter, tall‐stature, and big‐crown trees overrule the effects of species richness and remaining trees attributes on aboveground biomass in tropical forests (i.e., we term the “big‐sized trees hypothesis”). Specifically, we assessed the importance of: (a) the “top 1% big‐sized trees effect” relative to species richness; (b) the “99% remaining trees effect” relative to species richness; and (c) the “top 1% big‐sized trees effect” relative to the “99% remaining trees effect” and species richness on aboveground biomass. Using environmental factor and forest inventory datasets from 712 tropical forest plots in Hainan Island of southern China, we tested several structural equation models for disentangling the relative effects of big‐sized trees, remaining trees attributes, and species richness on aboveground biomass, while considering for the full (indirect effects only) and partial (direct and indirect effects) mediation effects of climatic and soil conditions, as well as interactions between species richness and trees attributes. We found that top 1% big‐sized trees attributes strongly increased aboveground biomass (i.e., explained 55%–70% of the accounted variation) compared to species richness (2%–18%) and 99% remaining trees attributes (6%–10%). In addition, species richness increased aboveground biomass indirectly via increasing big‐sized trees but via decreasing remaining trees. Hence, we show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.
Large‐diameter, tall‐stature and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence, play an important role in climate change mitigation strategies. We show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.
The present study aimed to systematically evaluate the diagnostic value of an isoform of alpha-fetoprotein (AFP), AFP-L3, for early hepatocellular carcinoma (HCC) by a meta-analysis.
Diagnostic ...reports of AFP-L3% in early HCC were searched in the PubMed, Web of Science, Cochrane Library, and Embase databases up to December 2019. The retrieved literature was reviewed, and eligible articles were selected. Data were extracted from the eligible articles, and the risk of bias was evaluated according to the Quality Assessment of Diagnostic Accuracy Studies scale. Statistical analyses were conducted by MetaDiSc1.4 and RevMan5.3 software. The sensitivities, specificities, and diagnostic odds ratios were pooled. The summary receiver operating characteristic curve was drawn, and the area under the curve was calculated.
Six studies with acceptable quality were included in the meta-analysis involving 2447 patients. No threshold effect was observed among the 6 studies, but there was obvious heterogeneity. The pooled sensitivity, specificity, and positive and negative likelihood ratios of AFP-L3% for the diagnosis of early HCC were 0.34 (95% CI 0.30-0.39, P < .0001), 0.92 (95% CI 0.91-0.93, P < .0001), 4.46 (95% CI 2.94-6.77, P = .0033), and 0.71 (95% CI 0.61-0.82, P = .0004), respectively. The diagnostic odds ratio was 6.78 (95% CI 4.02-11.44, P = .0074). The the area under the curve of the summary receiver operating characteristic was 0.755 (95% CI 0.57-0.94).
AFP-L3% has high specificity but low sensitivity for diagnose early HCC, suggesting that AFP-L3% is more valuable for excluding HCC in conditions with elevated AFP than for diagnosing early HCC. In addition, a hypersensitive detection method can improve the diagnostic accuracy of AFP-L3% for early HCC.
•Cytoplasmic LPS can activate macrophage via TLR4-independent pathway that results in activation of the enzyme caspase-11.•The negative regulators associated with endotoxin tolerance in KCs include ...IRAK-M, SHIP1, and SCOS1 and Twist-2.•KCs are responsible for the initiation of the pro-inflammatory response in IRI.•KCs are involved in liver immune tolerance through inducing apoptosis of T cells.•KCs release IL-1β that promotes development of NAFLD by activating TLR4, TLR9 and NLRP3 inflammasome pathways.
Kupffer cells (KCs) constitute 80–90% of the tissue macrophages present in the body. Essential to innate and adaptive immunity, KCs are responsible for the swift containment and clearance of exogenous particulates and immunoreactive materials which are perceived as foreign and harmful to the body. Similar to other macrophages, KCs also sense endogenous molecular signals that may result from perturbed homeostasis of the host. KCs have been implicated in host defense and the pathogenesis of various hepatic diseases, including endotoxin tolerance, liver transplantation, nonalcoholic fatty liver disease, and alcoholic liver disease. In this review, we summarized some novel findings associated with the role of KCs in hepatic diseases, such as the origin and mechanisms KCs polarization, molecular basis for caspase-1 activation called “non-canonical inflammasome pathway” involving the cleavage of Gsdmd by caspase-11, the important role of microRNA in liver transplantation, and so on. A better understanding of KCs biological characteristics and immunologic function in liver homeostasis and pathology may pave the way to investigate new diagnostic and therapeutic approaches for hepatic diseases.
Maintenance of genome stability is an essential requirement for all living organisms. Formaldehyde and UV‐B irradiation cause DNA damage and affect genome stability, growth and development, but the ...interplay between these two genotoxic factors is poorly understood in plants. We show that Arabidopsis adh2/gsnor1 mutant, which lacks alcohol dehydrogenase 2/S‐nitrosoglutathione reductase 1 (ADH2/GSNOR1), are hypersensitive to low fluence UV‐B irradiation or UV‐B irradiation‐mimetic chemicals. Although the ADH2/GSNOR1 enzyme can act on different substrates, notably on S‐hydroxymethylglutathione (HMG) and S‐nitrosoglutathione (GSNO), our study provides several lines of evidence that the sensitivity of gsnor1 to UV‐B is caused mainly by UV‐B‐induced formaldehyde accumulation rather than other factors such as alteration of the GSNO concentration. Our results demonstrate an interplay between formaldehyde and UV‐B that exacerbates genome instability, leading to severe DNA damage and impaired growth and development in Arabidopsis, and show that ADH2/GSNOR1 is a key player in combating these effects.
Nanosecond pulse discharge plasma has many prospects in industrial applications, and high-voltage repetitive nanosecond pulse generators with compact design and light weight have become one of the ...key issues limiting its development in some applications. This paper presents a high voltage series-connected silicon carbide (SiC) metal-oxide -semiconductor field effect transistor ( MOSFET s) module which can be served as the main switch in a repetitive high-voltage nanosecond pulse generator. This kind of series-connected MOSFET s module with only single external gate driver requiring very few components is very suitable for compact assembly. By analyzing the working principle, three topologies of series-connected MOSFET s module are proposed. The switching behaviors of the three different topologies with four SiC MOSFET s series-connected are compared experimentally. The variation of switching characteristics of series-connection SiC MOSFET s module with different numbers of devices are investigated. The layout is also optimized to shorten pulse front time and improve output pulse quality. Furthermore, a 10 kV SiC MOSFET s module with a turn- on transition time ∼10 ns is developed. The double pulse test result demonstrates excellent switching performances. Finally, a compact and high-voltage pulse generator composed of three 10 kV SiC MOSFET s module is tailored, with a typical rise time ∼40 ns and peak voltage of ∼30 kV.
Pursuant to the Paris Agreement, China committed itself to peak its carbon emissions by around 2030 and to increase the non-fossil share of primary energy to 20% at the same time. The government has ...supported the international agreement by setting and strengthening the domestic policy targets for an earlier peak and faster reduction, aiming to contain the average global temperature increase to well below 2 °C. We develop a Kaya Inequality method to assess the time of peak and pace of reduction of China's energy-related CO2 emissions based on the national energy policy targets for 2030. We find that, despite the minor fluctuations, the current plateau essentially represents the peak emissions and should enter a phase of steady decline by around 2025, given current trends in energy consumption and decarbonization. Such developments would be consistent with the strengthened national policy target to achieve 50% of renewable power generation by 2030. However, the basic policy targets – a 20% share of non-fossil energy and 6 Gtce in total energy consumption by 2030 – would be insufficient to peak carbon emissions by around 2030. The synergy and interplay between domestic policy target setting and international climate commitments shed light on the need to elevate national climate ambitions under the Paris Agreement and beyond.
Tumor clonal structure is closely related to future progression, which has been mainly investigated as mutation abundance clustering in bulk samples. With relatively limited studies at single‐cell ...resolution, a systematic comparison of the two approaches is still lacking. Here, using bulk and single‐cell mutational data from the liver and colorectal cancers, we checked whether co‐mutations determined by single‐cell analysis had corresponding bulk variant allele frequency (VAF) peaks. While bulk analysis suggested the absence of subclonal peaks and, possibly, neutral evolution in some cases, the single‐cell analysis identified coexisting subclones. The overlaps of bulk VAF ranges for co‐mutations from different subclones made it difficult to separate them. Complex subclonal structures and dynamic evolution could be hidden under the seemingly clonal neutral pattern at the bulk level, suggesting single‐cell analysis is necessary to avoid underestimation of tumor heterogeneity.
In this study, we demonstrated that bulk‐level analyses may be ill‐suited for revealing tumor clonal structure due to differences between mutation cluster and tumor subclone. The absence of subclonal mutation clusters does not necessarily support clonal neutral evolution, and tumor clonal structure and evolution history can be better revealed by single‐cell analysis.
Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate ...serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets.
A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments.
Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells.
Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.
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