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Patients with colorectal liver metastasis (CLM) present with heterogenous clinical outcomes and improved classification is needed to ameliorate the therapeutic output. Macrophages (Mϕ) hold promise as prognostic classifiers and therapeutic targets. Here, stemming from a single-cell analysis of mononuclear phagocytes infiltrating human CLM, we identified two Mϕ markers associated with distinct populations with opposite clinical relevance. The invasive margin of CLM was enriched in pro-inflammatory monocyte-derived Mϕ (MoMϕ) expressing the monocytic marker SERPINB2, and a more differentiated population, tumor-associated Mϕ (TAM), expressing glycoprotein nonmetastatic melanoma protein B (GPNMB). SERPINB2+ MoMϕ had an early inflammatory profile, whereas GPNMB+ TAMs were enriched in pathways of matrix degradation, angiogenesis, and lipid metabolism and were found closer to the tumor margin, as confirmed by spatial transcriptomics on CLM specimens. In a cohort of patients, a high infiltration of SERPINB2+ cells independently associated with longer disease-free survival (DFS; P = 0.033), whereas a high density of GPNMB+ cells correlated with shorter DFS (P = 0.012) and overall survival (P = 0.002). Cell–cell interaction analysis defined opposing roles for MoMϕ and TAMs, suggesting that SERPINB2+ and GPNMB+ cells are discrete populations of Mϕ and may be exploited for further translation to an immune-based stratification tool. This study provides evidence of how multi-omics approaches can identify nonredundant, clinically relevant markers for further translation to immune-based patient stratification tools and therapeutic targets. GPNMB has been shown to set Mϕ in an immunosuppressive mode. Our high dimensional analyses provide further evidence that GPNMB is a negative prognostic indicator and a potential player in the protumor function of Mϕ populations.

The landscape and function of the immune infiltrate of intrahepatic cholangiocarcinoma (iCCA), a rare, yet aggressive tumor of the biliary tract, remains poorly characterized, limiting development of successful immunotherapies. Herein, we aimed to define the molecular characteristics of tumor-infiltrating leukocytes with a special focus on CD4+ regulatory T cells (Tregs).We used high-dimensional single-cell technologies to characterize the T-cell and myeloid compartments of iCCA tissues, comparing these with their tumor-free peritumoral and circulating counterparts. We further used genomics and cellular assays to define the iCCA-specific role of a novel transcription factor, mesenchyme homeobox 1 (MEOX1), in Treg biology.We found poor infiltration of putative tumor-specific CD39+ CD8+ T cells accompanied by abundant infiltration of hyperactivated CD4+ Tregs. Single-cell RNA-sequencing identified an altered network of transcription factors in iCCA-infiltrating compared to peritumoral T cells, suggesting reduced effector functions by tumor-infiltrating CD8+ T cells and enhanced immunosuppression by CD4+ Tregs. Specifically, we found that expression of MEOX1 was highly enriched in tumor-infiltrating Tregs, and demonstrated that MEOX1 overexpression is sufficient to reprogram circulating Tregs to acquire the transcriptional and epigenetic landscape of tumor-infiltrating Tregs. Accordingly, enrichment of the MEOX1-dependent gene program in Tregs was strongly associated with poor prognosis in a large cohort of patients with iCCA.We observed abundant infiltration of hyperactivated CD4+ Tregs in iCCA tumors along with reduced CD8+ T-cell effector functions. Interfering with hyperactivated Tregs should be explored as an approach to enhance antitumor immunity in iCCA.Immune cells have the potential to slow or halt the progression of tumors. However, some tumors, such as intrahepatic cholangiocarcinoma, are associated with very limited immune responses (and infiltration of cancer-targeting immune cells). Herein, we show that a specific population of regulatory T cells (a type of immune cell that actually suppresses the immune response) are hyperactivated in intrahepatic cholangiocarcinoma. Targeting these cells could enable cancer-targeting immune cells to act more effectively and should be looked at as a potential therapeutic approach to this aggressive cancer type.

Liquid biopsy (LB) for prostate cancer (PCa) detection could represent an alternative to biopsy. Seminal fluid (SF) is a source of PCa-specific biomarkers, as 40% of ejaculate derives from the prostate. We tested the feasibility of an SF-based LB by evaluating the yield of semen self-sampling in a cohort of >750 patients with clinically localized PCa. The overall SF collection yield was 18.2% (39% when considering only compliant patients), with about a half of the patients (53.15%) not consenting to SF donation. Independent favorable predictors for SF collection were younger age and lower prostate volume. We implemented a protocol to enrich prostate-derived cells by multi-color flow cytometry and applied it on SF and urine samples from 100 patients. The number of prostate-enriched cells (SYTO-16+ PSMA+ CD45−) was variable, with higher numbers of cells isolated from SF than urine (p value < 0.001). Putative cancer cells (EpCAMhigh) were 2% of isolated cells in both specimens. The fraction of EpCAMhigh cells over prostate-enriched cells (PSMA+) significantly correlated with patient age in both semen and urine, but not with other clinical parameters, such as Gleason Score, ISUP, or TNM stage. Hence, enumeration of prostate-derived cells is not sufficient to guide PCa diagnosis; additional molecular analyses to detect patient-specific cancer lesions will be needed.

Supplementary Figures 1-4, Tables S1 and S5

Supplementary Table S4

Patients with colorectal liver metastasis (CLM) present with heterogenous clinical outcomes and improved classification is needed to ameliorate the therapeutic output. Macrophages (Mϕ) hold promise as prognostic classifiers and therapeutic targets. Here, stemming from a single-cell analysis of mononuclear phagocytes infiltrating human CLM, we identified two Mϕ markers associated with distinct populations with opposite clinical relevance. The invasive margin of CLM was enriched in pro-inflammatory monocyte-derived Mϕ (MoMϕ) expressing the monocytic marker SERPINB2, and a more differentiated population, tumor-associated Mϕ (TAM), expressing glycoprotein nonmetastatic melanoma protein B (GPNMB). SERPINB2+ MoMϕ had an early inflammatory profile, whereas GPNMB+ TAMs were enriched in pathways of matrix degradation, angiogenesis, and lipid metabolism and were found closer to the tumor margin, as confirmed by spatial transcriptomics on CLM specimens. In a cohort of patients, a high infiltration of SERPINB2+ cells independently associated with longer disease-free survival (DFS; P = 0.033), whereas a high density of GPNMB+ cells correlated with shorter DFS (P = 0.012) and overall survival (P = 0.002). Cell–cell interaction analysis defined opposing roles for MoMϕ and TAMs, suggesting that SERPINB2+ and GPNMB+ cells are discrete populations of Mϕ and may be exploited for further translation to an immune-based stratification tool. This study provides evidence of how multi-omics approaches can identify nonredundant, clinically relevant markers for further translation to immune-based patient stratification tools and therapeutic targets. GPNMB has been shown to set Mϕ in an immunosuppressive mode. Our high dimensional analyses provide further evidence that GPNMB is a negative prognostic indicator and a potential player in the protumor function of Mϕ populations.

Supplementary figure legends

Monocytes are critical cells of the immune system but their role as effectors is relatively poorly understood, as they have long been considered only as precursors of tissue macrophages or dendritic cells. Moreover, it is known that this cell type is heterogeneous, but our understanding of this aspect is limited to the broad classification in classical/intermediate/non-classical monocytes, commonly based on their expression of only two markers, i.e. CD14 and CD16. We deeply dissected the heterogeneity of human circulating monocytes in healthy donors by transcriptomic analysis at single-cell level and identified 9 distinct monocyte populations characterized each by a profile suggestive of specialized functions. The classical monocyte subset in fact included five distinct populations, each enriched for transcriptomic gene sets related to either inflammatory, neutrophil-like, interferon-related, and platelet-related pathways. Non-classical monocytes included two distinct populations, one of which marked specifically by elevated expression levels of complement components. Intermediate monocytes were not further divided in our analysis and were characterized by high levels of human leukocyte antigen (HLA) genes. Finally, we identified one cluster included in both classical and non-classical monocytes, characterized by a strong cytotoxic signature. These findings provided the rationale to exploit the relevance of newly identified monocyte populations in disease evolution. A machine learning approach was developed and applied to two single-cell transcriptome public datasets, from gastrointestinal cancer and Coronavirus disease 2019 (COVID-19) patients. The dissection of these datasets through our classification revealed that patients with advanced cancers showed a selective increase in monocytes enriched in platelet-related pathways. Of note, the signature associated with this population correlated with worse prognosis in gastric cancer patients. Conversely, after immunotherapy, the most activated population was composed of interferon-related monocytes, consistent with an upregulation in interferon-related genes in responder patients compared to non-responders. In COVID-19 patients we confirmed a global activated phenotype of the entire monocyte compartment, but our classification revealed that only cytotoxic monocytes are expanded during the disease progression. Collectively, this study unravels an unexpected complexity among human circulating monocytes and highlights the existence of specialized populations differently engaged depending on the pathological context.

More than 50% of all patients with colorectal cancer (CRC) develop liver metastases (CLM), a clinical condition characterized by poor prognosis and lack of reliable prognostic markers. Vδ1 cells are a subset of tissue-resident gamma delta (γδ) T lymphocytes endowed with a broad array of antitumor functions and showing a natural high tropism for the liver. However, little is known about their impact in the clinical outcomes of CLM.We isolated human γδ T cells from peripheral blood (PB) and peritumoral (PT) tissue of 93 patients undergone surgical procedures to remove CLM. The phenotype of freshly purified γδ T cells was assessed by multiparametric flow cytometry, the transcriptional profiles by single cell RNA-sequencing, the functional annotations by Gene Ontology enrichment analyses and the clonotype by γδ T cell receptor (TCR)-sequencing.The microenvironment of CLM is characterized by a heterogeneous immune infiltrate comprising different subsets of γδ tumor-infiltrating lymphocytes (TILs) able to egress the liver and re-circulate in PB. Vδ1 T cells represent the largest population of γδ TILs within the PT compartment of CLM that is greatly enriched in Vδ1 T effector (TThe enrichment of tissue-resident CD69

We propose a novel scheme for the generation of optimal squeezed states for Ramsey interferometry. The scheme consists of an alternating series of one-axis twisting pulses and rotations, both of which are straightforward to implement experimentally. The resulting states show a metrological gain proportional to the Heisenberg limit. We demonstrate that the Heisenberg scaling is maintained even when placing constraints on the amplitude of the pulses implementing the one-axis twisting and when taking into account realistic losses due to photon scattering.

State-of-the-art atomic clocks are based on the precise detection of the energy difference between two atomic levels, which is measured in terms of the quantum phase accumulated over a given time interval1–4. The stability of optical-lattice clocks (OLCs) is limited both by the interrupted interrogation of the atomic system by the local-oscillator laser (Dick noise5) and by the standard quantum limit (SQL) that arises from the quantum noise associated with discrete measurement outcomes. Although schemes for removing the Dick noise have been recently proposed and implemented4,6–8, performance beyond the SQL by engineering quantum correlations (entanglement) between atoms9–20 has been demonstrated only in proof-of-principle experiments with microwave clocks of limited stability. The generation of entanglement on an optical-clock transition and operation of an OLC beyond the SQL represent important goals in quantum metrology, but have not yet been demonstrated experimentally16. Here we report the creation of a many-atom entangled state on an OLC transition, and use it to demonstrate a Ramsey sequence with an Allan deviation below the SQL after subtraction of the local-oscillator noise. We achieve a metrological gain of $$4.{4}_{-0.4}^{+0.6}$$ decibels over the SQL by using an ensemble consisting of a few hundred ytterbium-171 atoms, corresponding to a reduction of the averaging time by a factor of 2.8 ± 0.3. Our results are currently limited by the phase noise of the local oscillator and Dick noise, but demonstrate the possible performance improvement in state-of-the-art OLCs1–4 through the use of entanglement. This will enable further advances in timekeeping precision and accuracy, with many scientific and technological applications, including precision tests of the fundamental laws of physics21–23, geodesy24–26 and gravitational-wave detection27. A many-atom state of trapped 171Yb atoms that are entangled on an optical atomic-clock transition overcomes the standard quantum limit, providing a proof-of-principle demonstration towards entanglement-based optical atomic clocks.

Potential Energy (PE) between 2 bodies with mass, refers to the relative gravitational pull between them. Analogously, in the context of a graph, nodes can thought of as objects where a) the product of the degrees of nodes acts as a proxy for mass, b) the clustering coefficients of common neighbours as a proxy for gravitational acceleration, and c) the inverse of the shortest distance between nodes as a proxy for distance in space, which allows for PE calculation as introduced in prior work. In this work, we are investigating the effects of incorporating PE in Link Prediction (LP) with Relational Graph Convolutional Networks (R-GCN). Specifically, we explore the benefits of including PE calculation as an informative prior to the LP task and in a follow-up experiment as a learnable feature to predict. We performed several experiments and show that considering PE in the LP process has certain advantages and find that the information PE provides was not captured by the embeddings produced by the R-GCN.

We introduce a Magnetic Particle Imaging Susceptometer (MPIS) that uses a high- sensitivity atomic magnetometer (AM) for recording the spatial distribution of fluid- suspended magnetic nanoparticles. We have evaluated the MPIS performance by one-dimensional scans of structured nanoparticle phantoms, demonstrating, in particular, resolutions of ≈2.5 mm prior to deconvolution and ≪1 mm after deconvolution. Our instrument conceptually follows the general principle of Magnetic Particle Imaging (MPI) for encoding spatial distributions into magnetic flux density variations. Conversely to previously demonstrated MPI methods, MPIS works in time- space by recording time series of the sample’s magnetic response including all Fourier components. The device deploys a specifically designed system of coils, a low-frequency excitation scheme, and a simple source localization algorithm. The difference of the AM’s frequency response with respect to the conventional receive coil detection allows us to work at much lower driving frequencies. We demonstrate operation at frequencies on the order of 100 Hz, enabling the beneficial use of larger nanoparticles. The spatial distribution encoded into the particles’ susceptibility needs a much lower excitation field amplitude compared to conventional MPI scanners. These two features make MPIS least harmful for biological samples and subjects compared to conventional MPI scanners. We also address performance characteristics and other possible applications of MPIS.

The aim of this work is to evaluate the potential application of a new sustainable technology, called Acid Gas to Syngas, on steam reforming process in order to reduce the carbon dioxide emissions. Indeed, steam reforming has high emissions of carbon dioxide, at almost 7 kg of carbon dioxide per 1 kg of hydrogen produced. The key idea of the new technology is to convert carbon dioxide and hydrogen sulfide coming from natural gas desulfurization into additional hydrogen. Coupling different software, i.e. Aspen HYSYS and MATLAB, a complete plant model, able to manage the recycle of unconverted acid gases, has been developed. The importance of introduced innovations is highlighted and a comparison between the old process and the new one with Acid Gas to Syngas technology is built up. With Acid Gas to Syngas technology the natural gas consumption and carbon dioxide emissions can be reduced up to 3%.

Hepatocellular carcinoma and cholangiocarcinoma are the most common primary malignant liver tumors. Since the liver plays a key role in lipid metabolism, the study of serum phospholipid (PL) profiles may provide a better understanding of alterations in hepatic lipid metabolism. In this study, we used a high-resolution HILIC-LC-MS lipidomic approach to establish the serum phospholipidome profile of patients with liver cancer before (T0) and after tumor resection (T1) and a control group (CT) of healthy individuals. After the analysis of PL profiles, we observed that the phospholipidome of patients with liver cancer was significantly modified after the tumor resection procedure. We observed an upregulation of some phosphatidylcholine (PtdCho) species, namely, PtdCho(36:6), PtdCho(42:6), PtdCho(38:5), PtdCho(36:5), PtdCho(38:6) and choline plasmalogens (PlsCho), and/or 1-O-alkyl-2-acyl-glycerophosphocholine (PakCho) in patients with liver cancer at T0 compared to the CT group, and a downregulation after tumor resection (T1) when compared to T0. These results show that LC-MS can detect different serum PL profiles in patients with liver cancer, before and after tumor resection, by defining a specific PL fingerprint that was used to determine the effect of tumor and tumor resection on lipid metabolism.

Recent developments in atomic physics have enabled the experimental generation of many-body entangled states to boost the performance of quantum sensors beyond the Standard Quantum Limit (SQL). This limit is imposed by the inherent projection noise of a quantum measurement. In this perspective article, we describe the commonly used experimental methods to create many-body entangled states to operate quantum sensors beyond the SQL. In particular, we focus on the potential of applying quantum entanglement to state-of-the-art optical atomic clocks. In addition, we present recently developed time-reversal protocols that make use of complex states with high quantum Fisher information without requiring sub-SQL measurement resolution. We discuss the prospects for reaching near-Heisenberg limited quantum metrology based on such protocols., Comment: 8 pages, 7 figures, perspective article

Tumor-associated macrophages (TAMs) are correlated with the progression of prostatic adenocarcinoma (PCa). The mechanistic basis of this correlation and therapeutic strategies to target TAMs in PCa remain poorly defined. Here, single-cell RNA sequencing was used to profile the transcriptional landscape of TAMs in human PCa, leading to identification of a subset of macrophages characterized by dysregulation in transcriptional pathways associated with lipid metabolism. This subset of TAMs correlates positively with PCa progression and shorter disease-free survival and is characterized by an accumulation of lipids that is dependent on Marco. Mechanistically, cancer cell–derived IL-1β enhances Marco expression on macrophages, and reciprocally, cancer cell migration is promoted by CCL6 released by lipid-loaded TAMs. Moreover, administration of a high-fat diet to tumor-bearing mice raises the abundance of lipid-loaded TAMs. Finally, targeting lipid accumulation by Marco blockade hinders tumor growth and invasiveness and improves the efficacy of chemotherapy in models of PCa, pointing to combinatorial strategies that may influence patient outcomes.

The exploration and production of hydrocarbons is undeniably a high-risk venture. Uncertainties are in every activity, from the exploration phase up to facilities construction and plants operation. To allow decision makers understanding the uncertainty associated with the decisions they were asked to face, in the 70ies of the past century, when the oil shockwaves upset the entire business world (Bood & Postma, 1997), it was introduced the use of scenario analysis. Since then, stochastic analyses, such as Monte Carlo simulations, started permeating the oil & gas world. Yet, as Lewis et al. (2004) highlighted, despite the benefit greatly outweighs the effort generally required to perform these analyses, managers not seldom refrained themselves from using these tools to support their decision-making processes. And this, as highlighted by Judah (2016), despite risk mitigation is the very core of the oil & gas business as risks at stake are many, namely: drilling risk, subsurface risk, cost & schedule risk, procurement risk, performance risk, health, safety, and environment (HSE) risk, geopolitical risk, and price risk. Today, the energy transition is imposing new challenges to the oil & gas sector. Even amongst those companies that have embraced (quantitative) structured approaches to support their investment decisions, there is another challenge to face: the integration of all risks in one approach capable of capturing the overall complexity of oil & gas projects and highlighting the effects of variations of both endogenous and exogenous risks on the overall profitability of the opportunity at stake (or the portfolio of opportunities). Risks are typically assessed separately by each function with different quantitative approaches that leave grey zones of interpretation where inter-functional risks can grow and create decisional inefficiencies. Aware of this, Eni integrated risk management, started last year a project aimed at enhancing the project risk management process. The innovative approach followed leverages on artificial logic and allows to consider the full life cycle of an investment proposal. In line with the evolution of company's mission and vision, the aim was to assess the project risk in a more comprehensive way by considering endogenous risks (such as permits, drilling, engineering, procurement, construction) jointly with exogenous ones (such as climate change, cyber security, credit, and country). The manuscript explains the methodology used, the results achieved, and the expected benefit for the company in adopting the innovative approach to risk engineering in supporting investments decisions.