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Liver cancers give rise to a heavy burden on healthcare worldwide. Understanding the tumour microenvironment (TME) underpins the development of precision therapy. Single-cell RNA sequencing (scRNA-seq) technology has generated high-quality cell atlases of the TME, but its wider application faces enormous costs for various clinical circumstances. Fortunately, a variety of deconvolution algorithms can instead repurpose bulk RNA-seq data, alleviating the need for generating scRNA-seq datasets. In this study, we reviewed major public omics databases for relevance in this study and utilised eight RNA-seqs and one microarray dataset from clinical studies. To decipher the TME of liver cancer, we estimated the fractions of liver cell components by deconvoluting the samples with Cibersortx using three reference scRNA-seq atlases. We also confirmed that Cibersortx can accurately deconvolute cell types/subtypes of interest. Compared with non-tumorous liver, liver cancers showed multiple decreased cell types forming normal liver microarchitecture, as well as elevated cell types involved in fibrogenesis, abnormal angiogenesis, and disturbed immune responses. Survival analysis shows that the fractions of five cell types/subtypes significantly correlated with patient outcomes, indicating potential therapeutic targets. Therefore, deconvolution of bulk RNA-seq data with scRNA-seq atlas references can be a useful tool to help understand the TME.

Across the transition from childhood to adolescence the human brain experiences profound functional changes, shifting from an organizational framework anchored within somatosensory/motor and visual regions into one that is balanced through interactions with later-maturing aspects of association cortex1–3. Here, we provide consistent evidence linking this profile of large-scale functional reorganization to the development of attention network connectivity across independent datasets4,5. We demonstrate that maturational changes in cortical organization are preferential to the salience/ventral attention network6–9with heightened degree centrality and within-network connectivity, while connectivity within these network-linked vertices predicts cognitive ability such as fluid intelligence, perceptual reasoning and verbal ability10. Maturational refinement of the attention network closely links to the transition in cortical hierarchy, children with low ventral attention network connectivity exhibit adolescent-like topographical profiles, suggesting attentional systems may be critically important for understanding how brain functions are refined across development. These data highlight a core role for attention networks in supporting age-dependent shifts in cortical organization and cognition across childhood and adolescence, with the pruning in its between-network functional connections reflecting intricate interactions across multiple systems, rather than the segregation of an isolated network. The development of cortical hierarchy in children is driven by the ventral attention network, and the refinement of network connectivity within this system is linked to an accelerated pattern of cortical maturation.

Cancer stem cells (CSCs) or tumor-initiating cells (TICs) are thought to be the main drivers for disease progression and treatment resistance across various cancer types. Identifying and targeting these rare cancer cells, however, remains challenging with respect to therapeutic benefit. Here, we report the enrichment of LGR5 expressing cells, a well-recognized stem cell marker, in mouse liver tumors, and the upregulation of LGR5 expression in human hepatocellular carcinoma. Isolated LGR5 expressing cells from mouse liver tumors are superior in initiating organoids and forming tumors upon engraftment, featuring candidate TICs. These cells are resistant to conventional treatment including sorafenib and 5-FU. Importantly, LGR5 lineage ablation significantly inhibits organoid initiation and tumor growth. The combination of LGR5 ablation with 5-FU, but not sorafenib, further augments the therapeutic efficacy in vivo. Thus, we have identified the LGR5+ compartment as an important TIC population, representing a viable therapeutic target for combating liver cancer., Cancer stem cells (CSCs) are thought to be the main drivers for disease progression and treatment resistance in liver cancer. This study identifies the LGR5+ compartment as an important CSC population, representing a viable therapeutic target for combating liver cancer.

Large-scale biophysical circuit models provide mechanistic insights into the micro-scale and macro-scale properties of brain organization that shape complex patterns of spontaneous brain activity. We developed a spatially heterogeneous large-scale dynamical circuit model that allowed for variation in local synaptic properties across the human cortex. Here we show that parameterizing local circuit properties with both anatomical and functional gradients generates more realistic static and dynamic resting-state functional connectivity (FC). Furthermore, empirical and simulated FC dynamics demonstrates remarkably similar sharp transitions in FC patterns, suggesting the existence of multiple attractors. Time-varying regional fMRI amplitude may track multi-stability in FC dynamics. Causal manipulation of the large-scale circuit model suggests that sensory-motor regions are a driver of FC dynamics. Finally, the spatial distribution of sensory-motor drivers matches the principal gradient of gene expression that encompasses certain interneuron classes, suggesting that heterogeneity in excitation-inhibition balance might shape multi-stability in FC dynamics., Spontaneous fluctuations in brain activity exhibit complex spatiotemporal patterns across animal species. Here the authors show that sensory-motor regions and spatial heterogeneity in excitation-inhibition balance might shape multi-stability in brain dynamics.

Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n = 297) and the Healthy Brain Network (HBN, n = 551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.

Background Hepatitis delta virus (HDV) coinfects with hepatitis B virus (HBV) causing the most severe form of viral hepatitis. However, its exact global disease burden remains largely obscure. We aim to establish the global epidemiology, infection mode-stratified disease progression, and clinical outcome of HDV infection. Methods We conducted a meta-analysis with a random-effects model and performed data synthesis. Results The pooled prevalence of HDV is 0.80% (95% confidence interval [CI], 0.63–1.00) among the general population and 13.02% (95% CI, 11.96–14.11) among HBV carriers, corresponding to 48–60 million infections globally. Among HBV patients with fulminant hepatitis, cirrhosis, or hepatocellular carcinoma, HDV prevalence is 26.75% (95% CI, 19.84–34.29), 25.77% (95% CI, 20.62–31.27), and 19.80% (95% CI, 10.97–30.45), respectively. The odds ratio (OR) of HDV infection among HBV patients with chronic liver disease compared with asymptomatic controls is 4.55 (95% CI, 3.65–5.67). Hepatitis delta virus-coinfected patients are more likely to develop cirrhosis than HBV-monoinfected patients with OR of 3.84 (95% CI, 1.79–8.24). Overall, HDV infection progresses to cirrhosis within 5 years and to hepatocellular carcinoma within 10 years, on average. Conclusions Findings suggest that HDV poses a heavy global burden with rapid progression to severe liver diseases, urging effective strategies for screening, prevention, and treatment., Forty-eight to 60 million individuals are infected with HDV around the globe, and Asia and Africa are the worst-hit areas. HDV infection predisposes to rapid progression into severe liver diseases, particularly liver cirrhosis.

Summary Hepatitis delta virus (HDV), as a defective sub‐virus that co‐infects with hepatitis B virus, imposes an emerging global health burden. However, genetic characteristics and molecular classification of HDV remain under investigated. In this study, we have systematically retrieved and analysed a large set of HDV full‐length genome sequences and identified novel recombinants. Based on phylogenetic and genetic analyses, we have established an updated classification system for HDV when recombinants were excluded. Furthermore, we have mapped the global distribution of different genotypes and subtypes. Finally, we have compiled a complete set of reference genomes for each subtype and proposed criteria for future identification of novel genotypes and subtypes. Of note, the global distribution map indicates that currently available HDV genetic data remain limited, and thus our proposed classification will likely evolve as future epidemiological data will accumulate. These results will facilitate the future research on the diagnosis, screening, epidemiology, evolution, prevention and clinical management of HDV infection.

Hepatitis E virus (HEV) is one of the major pathogens causing acute viral hepatitis. The infectious particle consists of an RNA genome and capsid proteins. The 7.2 kb genome encodes three open reading frames (ORF) and ORF2 is translated into the capsid protein. The knowledge of structure and function of the ORF2 protein is essential for understanding the evolution and life cycle of HEV. However, biophysical research in this respect remains limited due to technical challenges. We have carried out a series of computational analysis on HEV ORF2. We have identified 144 conserved sites among the 660 amino acid (AA) residues. 43 models based on the previously proposed reference sequences and a cell culture adapted infectious clone were successfully built by 3D protein structure prediction and refinement. Structure alignment of domains revealed structural conservation of the S and M domains, but to a lesser extent of the P domain. Moreover, molecular docking has predicted distinct binding affinities of a monoclonal antibody towards ORF2 across different genotypes. Thus, we have expanded the information on ORF2 at both sequence and structure levels. These findings may help to better understand the evolution and life cycle of HEV, but also facilitate the development of genetically engineered vaccines or antibodies.

Summary Hepatitis virus infections affect a large proportion of the global population. The host responds rapidly to viral infection by orchestrating a variety of cellular machineries, in particular, the mitochondrial compartment. Mitochondria actively regulate viral infections through modulation of the cellular innate immunity and reprogramming of metabolism. In turn, hepatitis viruses are able to modulate the morphodynamics and functions of mitochondria, but the mode of actions are distinct with respect to different types of hepatitis viruses. The resulting mutual interactions between viruses and mitochondria partially explain the clinical presentation of viral hepatitis, influence the response to antiviral treatment, and offer rational avenues for novel therapy. In this review, we aim to consider in depth the multifaceted interactions of mitochondria with hepatitis virus infections and emphasize the implications for understanding pathogenesis and advancing therapeutic development.

Metabolic reprogramming universally occurs in cancer. Mitochondria act as the hubs of bioenergetics and metabolism. The morphodynamics of mitochondria, comprised of fusion and fission processes, are closely associated with mitochondrial functions and are often dysregulated in cancer. In this study, we aim to investigate the mitochondrial morphodynamics and its functional consequences in human liver cancer. We observed excessive activation of mitochondrial fusion in tumor tissues from hepatocellular carcinoma (HCC) patients and in vitro cultured tumor organoids from cholangiocarcinoma (CCA). The knockdown of the fusion regulator genes, OPA1 (Optic atrophy 1) or MFN1 (Mitofusin 1), inhibited the fusion process in HCC cell lines and CCA tumor organoids. This resulted in inhibition of cell growth in vitro and tumor formation in vivo, after tumor cell engraftment in mice. This inhibitory effect is associated with the induction of cell apoptosis, but not related to cell cycle arrest. Genome-wide transcriptomic profiling revealed that the inhibition of fusion predominately affected cellular metabolic pathways. This was further confirmed by the blocking of mitochondrial fusion which attenuated oxygen consumption and cellular ATP production of tumor cells. In conclusion, increased mitochondrial fusion in liver cancer alters metabolism and fuels tumor cell growth.

Hepatitis E virus (HEV) infection has emerged as a global health problem. However, no approved medication is available, and the infection biology remains largely elusive. Electron transport chain (ETC), a key component of the mitochondria, is the main site that produces ATP and reactive oxygen species (ROS). By profiling the role of the different complexes of the mitochondrial ETC, we found that pharmacological inhibition of complex III, a well-defined drug target for the treatment of malaria and Pneumocystis pneumonia, potently restricts HEV replication. This effect demonstrated in our HEV models is equivalent to the anti-HEV potency of ribavirin, a widely used off-label treatment for patients with chronic HEV. Mechanistically, we found that this effect is independent of ATP production, ROS level, and pyridine depletion. By using pharmacological inhibitors and genetic approaches, we found that mitochondrial permeability transition pore (MPTP), a newly identified component of ETC, provides basal defense against HEV infection. HEV interferes with the opening of the MPTP. Furthermore, inhibition of the MPTP attenuated the anti-HEV effect of complex III inhibitors, suggesting that the MPTP mediates the antiviral effects of these inhibitors. These findings reveal new insights on HEV-host interactions and provide viable anti-HEV targets for therapeutic development.-Qu, C., Zhang, S., Wang, W., Li, M., Wang, Y., van der Heijde-Mulder, M., Shokrollahi, E., Hakim, M. S., Raat, N. J. H., Peppelenbosch, M. P., Pan, Q. Mitochondrial electron transport chain complex III sustains hepatitis E virus replication and represents an antiviral target.