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Despite accounting for a significant portion of the Earth’s prokaryotic biomass, controls on the abundance and biodiversity of microorganisms residing in the continental subsurface are poorly understood. To redress this, we compiled cell concentration and microbial diversity data from continental subsurface localities around the globe. Based on considerations of global heat flow, surface temperature, depth and lithology, we estimated that the continental subsurface hosts 2 to 6 × 1029 cells and found that other variables such as total organic carbon and groundwater cellular abundances do not appear to be predictive of cell concentrations in the continental subsurface. Although we were unable to identify a reliable predictor of species richness in the continental subsurface, we found that bacteria are more abundant than archaea and that their community composition was correlated to sample lithology. Using our updated continental subsurface cellular estimate and existing literature, we estimate that the total global prokaryotic biomass is approximately 23 to 31 Pg of carbon C (PgC), roughly 4 to 10 times less than previous estimates.

A number of patient-specific and leukemia-associated factors are related to the poor outcome in older patients with acute myeloid leukemia (AML). However, comprehensive studies regarding the impact of genetic alterations in this group of patients are limited. In this study, we compared relevant mutations in 21 genes between AML patients aged 60 years or older and those younger and exposed their prognostic implications. Compared with the younger patients, the elderly had significantly higher incidences of PTPN11 , NPM1 , RUNX1 , ASXL1 , TET2 , DNMT3A and TP53 mutations but a lower frequency of WT1 mutations. The older patients more frequently harbored one or more adverse genetic alterations. Multivariate analysis showed that DNMT3A and TP53 mutations were independent poor prognostic factors among the elderly, while NPM1 mutation in the absence of FLT3 /ITD was an independent favorable prognostic factor. Furthermore, the status of mutations could well stratify older patients with intermediate-risk cytogenetics into three risk groups. In conclusion, older AML patients showed distinct genetic alterations from the younger group. Integration of cytogenetics and molecular mutations can better risk-stratify older AML patients. Development of novel therapies is needed to improve the outcome of older patients with poor prognosis under current treatment modalities.

Key Points Mathematical models have become an integral part of cancer biology. They are useful tools for deriving a mechanistic understanding of dynamic processes in cancer. The somatic evolutionary process, which maintains tissues and can initiate cancer, has served as a hallmark of mathematical descriptions of tumours. Mathematical models have helped in the understanding of interactions among homeostatic mechanisms, environmental factors and mutation accumulation that drive tumorigenesis. Using cell-based hierarchical models of tissue structure, theoretical insights have influenced the prediction of the cell of origin of human cancers, which may drive an understanding of metastasis and treatment response. The temporal order of events during tumour development can be recapitulated using mathematical modelling and genomics data sets. Mathematical models have also been used to explore the role of the tumour microenvironment in cancer progression. Such models help to elucidate important microenvironmental barriers to effective cancer treatment and how to overcome them. Metastasis evolution and immunotherapy have attracted increasing interest but still offer a wide range of opportunities for mathematical modelling. In combination with pharmacological considerations, quantitative models have a decisive role in the exploration of novel treatment modalities of cancer. This includes drug scheduling and the effect of combination therapy to avoid the evolution of resistance. The key role of mathematical modelling in the future will not only be to describe what is known, but also to point to gaps in our understanding of which complex interactions drive tumour growth, treatment dynamics and resistance evolution. This Review discusses mathematical modelling approaches in cancer research. These models can complement experimental and clinical studies, but can also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research. Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology.

Somatostatin (SST) deficits are common pathological features in depression and other neurological disorders with mood disturbances, but little is known about the contribution of SST deficits to mood symptoms or causes of these deficits. Here we show that mice lacking SST ( Sst KO ) exhibit elevated behavioral emotionality, high basal plasma corticosterone and reduced gene expression of Bdnf , Cortistatin and Gad67 , together recapitulating behavioral, neuroendocrine and molecular features of human depression. Studies in Sst KO and heterozygous ( Sst HZ ) mice show that elevated corticosterone is not sufficient to reproduce the behavioral phenotype, suggesting a putative role for Sst cell-specific molecular changes. Using laser capture microdissection, we show that cortical SST-positive interneurons display significantly greater transcriptome deregulations after chronic stress compared with pyramidal neurons. Protein translation through eukaryotic initiation factor 2 (EIF2) signaling, a pathway previously implicated in neurodegenerative diseases, was most affected and suppressed in stress-exposed SST neurons. We then show that activating EIF2 signaling through EIF2 kinase inhibition mitigated stress-induced behavioral emotionality in mice. Taken together, our data suggest that (1) low SST has a causal role in mood-related phenotypes, (2) deregulated EIF2-mediated protein translation may represent a mechanism for vulnerability of SST neurons and (3) that global EIF2 signaling has antidepressant/anxiolytic potential.

Prostate cancer cells escape growth inhibition from transforming growth factor β (TGFβ) by downregulating TGFβ receptors. However, the mechanism by which cancer cells downregulate TGFβ receptors in prostate is not clear. Here, we showed that coordinated action of miR-21 and androgen receptor (AR) signaling had a critical role in inhibiting TGFβ receptor II (TGFBR2) expression in prostate cancer cells. Our results revealed that miR-21 suppresses TGFBR2 levels by binding to its 3′-UTR and AR signaling further potentiates this effect in both untransformed and transformed human prostate epithelial cells as well as in human prostate cancers. Analysis of primary prostate cancers showed that increased miR-21/AR expression parallel a significantly reduced expression of TGFBR2. Manipulation of androgen signaling or the expression levels of AR or miR-21 negatively altered TGFBR2 expression in untransformed and transformed human prostate epithelial cells, human prostate cancer xenografts and mouse prostate glands. Importantly, we demonstrated that miR-21 and AR regulated each other’s expression resulting in a positive feedback loop. Our results indicated that miR-21/AR mediate its tumor-promoting function by attenuating TGFβ-mediated Smad2/3 activation, cell growth inhibition, cell migration and apoptosis. Together, these results suggest that the AR and miR-21 axis exerts its oncogenic effects in prostate tumors by downregulating TGFBR2, hence inhibiting the tumor-suppressive activity of TGFβ pathway. Targeting miR-21 alone or in combination with AR may restore the tumor inhibitory activity of TGFβ in prostate cancer.

Infection by hepatitis B virus (HBV) accounts for 50–80% of hepatocellular carcinoma (HCC) development worldwide, in which the HBV-encoded X protein (HBx) has critical role in the induction of carcinogenesis. Several studies have shown that thyroid hormone (TH) suppresses HCC development and protects hepatocytes from HBx-induced damage, thus it is of interest to examine whether TH can protect hepatocytes from HBx-induced carcinogenesis. By treating HBx- transgenic mice with or without TH, we confirmed the protective effects of TH on HBx-induced hepatocarcinogenesis, which was achieved via reduction of reactive oxygen species (ROS) inflicted DNA damage. We further found that TH induced biogenesis of mitochondria (MITO) and autophagy of HBx-targeted MITO simultaneously, consequently leading to suppression of HBx-promoted ROS and carcinogenesis. Using microarray data analysis, this protective effect of TH was found to be mediated via activation of PTEN-induced kinase 1 (PINK1) in hepatocytes. PINK1, in turn, activated and recruited Parkin, an E3 ligase, to ubiquitinate MITO-associated HBx protein and trigger selective mitophagy. The pathological significance of the TH/PINK1 pathway in liver protection was confirmed by the concomitant decrease in expression of both TR and PINK1 in matched HCC tumor tissues and negatively correlated with aggressive progression of cancer and poor prognosis. Our data indicate that TH/PINK1/Parkin pathway has a critical role in protecting hepatocytes from HBx-induced carcinogenesis. Notably, several liver-targeting therapeutic derivatives of TH facilitating prevention or therapy of steatosis have been identified. Furthermore, our proof-of-concept experiments suggest that application of T 3 constitutes an effective novel therapeutic or preventive option for HCC. Thus, the utilization of the agonists of TRs could be the meaningful strategy in liver relative diseases, ranging from simple hepatic steatosis to HCC.

A bstract The mass spectrum of 1 + 1-dimensional SU( N ) gauge theory coupled to a Majorana fermion in the adjoint representation has been studied in the large N limit using Light-Cone Quantization. Here we extend this approach to theories with small values of N , exhibiting explicit results for N = 2 , 3, and 4. In the context of Discretized Light-Cone Quantization, we develop a procedure based on the Cayley-Hamilton theorem for determining which states of the large N theory become null at finite N . For the low-lying bound states, we find that the squared masses divided by g 2 N , where g is the gauge coupling, have very weak dependence on N . The coefficients of the 1 /N 2 corrections to their large N values are surprisingly small. When the adjoint fermion is massless, we observe exact degeneracies that we explain in terms of a Kac-Moody algebra construction and charge conjugation symmetry. When the squared mass of the adjoint fermion is tuned to g 2 N/π , we find evidence that the spectrum exhibits boson-fermion degeneracies, in agreement with the supersymmetry of the model at any value of N .

Adjectives are essential in how people describe, evaluate, and reason about others. They differ along meaningful semantic dimensions such as desirability (e.g., “friendly” is more positive than “rude”) and breadth (e.g., “punctual” is narrower than “reliable”). Adjectival breadth has received limited empirical attention, partly because existing resources are sparse and outdated. We introduce a new database with subjective ratings from approximately 1,500 Americans for 1,214 adjectives on both breadth and desirability. Unlike existing resources, this updated database is more comprehensive and diverse, allowing for detailed analysis of adjectival use in academic and applied contexts. We validate this database with a large-scale analysis of online product reviews, showing how variation in adjective breadth is a common feature of natural language use. This database should prove valuable for research on semantic representation, social inference, and evaluative communication across various fields.

Background: Sorafenib is the only drug approved for the treatment of hepatocellular carcinoma (HCC). The bioenergetic propensity of cancer cells has been correlated to anticancer drug resistance, but such correlation is unclear in sorafenib resistance of HCC. Methods: Six sorafenib-naive HCC cell lines and one sorafenib-resistant HCC cell line (Huh-7R; derived from sorafenib-sensitive Huh-7) were used. The bioenergetic propensity was calculated by measurement of lactate in the presence or absence of oligomycin. Dichloroacetate (DCA), a pyruvate dehydrogenase kinase (PDK) inhibitor, and siRNA of hexokinase 2 (HK2) were used to target relevant pathways of cancer metabolism. Cell viability, mitochondrial membrane potential, and sub-G1 fraction were measured for in vitro efficacy. Reactive oxygen species (ROS), adenosine triphosphate (ATP) and glucose uptake were also measured. A subcutaneous xenograft mouse model was used for in vivo efficacy. Results: The bioenergetic propensity for using glycolysis correlated with decreased sorafenib sensitivity ( R 2 =0.9067, among sorafenib-naive cell lines; P =0.003, compared between Huh-7 and Huh-7 R). DCA reduced lactate production and increased ROS and ATP, indicating activation of oxidative phosphorylation (OXPHOS). DCA markedly sensitised sorafenib-resistant HCC cells to sorafenib-induced apoptosis (sub-G1 (combination vs sorafenib): Hep3B, 65.4±8.4% vs 13±2.9%; Huh-7 R, 25.3± 5.7% vs 4.3±1.5%; each P <0.0001), whereas siRNA of HK2 did not. Sorafenib (10 mg kg −1 per day) plus DCA (100 mg kg −1 per day) also resulted in superior tumour regression than sorafenib alone in mice (tumour size: −87% vs −36%, P <0.001). Conclusion: The bioenergetic propensity is a potentially useful predictive biomarker of sorafenib sensitivity, and activation of OXPHOS by PDK inhibitors may overcome sorafenib resistance of HCC.

The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.