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D-2-hydroxyglutarate (D-2-HG) accumulates in primary acute myeloid leukemia (AML) patients with mutated isocitrate dehydrogenase (IDH) and other malignancies. D-2-HG suppresses antitumor T cell immunity but little is known about potential effects on non-malignant myeloid cells. Here we show that D-2-HG impairs human but not murine dendritic cell (DC) differentiation, resulting in a tolerogenic phenotype with low major histocompatibility (MHC) class II expression. In line, IDH-mutated AML blasts exhibited lower expression of HLA-DP and were less susceptible to lysis by HLA-DP-specific T cells. Interestingly, D-2-HG reprogrammed metabolism towards increased lactate production in DCs and AML besides its expected impact on DNA demethylation. Vitamin C accelerated DNA demethylation, but only the combination of vitamin C and glycolytic inhibition lowered lactate levels and supported MHC class II expression. Our results indicate an unexpected link between the immunosuppressive metabolites 2-HG and lactic acid and suggest a potentially novel therapeutic strategy with combinations of anti-glycolytic drugs and epigenetic modulators (hypomethylating agents) or other therapeutics for the treatment of AML.

Background & Aims Intratumoral lactate accumulation and acidosis impair T-cell function and antitumor immunity. Interestingly, expression of the lactate transporter monocarboxylate transporter (MCT) 4, but not MCT1, turned out to be prognostic for the survival of patients with rectal cancer, indicating that single MCT4 blockade might be a promising strategy to overcome glycolysis-related therapy resistance.Methods To determine whether blockade of MCT4 alone is sufficient to improve the efficacy of immune checkpoint blockade (ICB) therapy, we examined the effects of the selective MCT1 inhibitor AZD3965 and a novel MCT4 inhibitor in a colorectal carcinoma (CRC) tumor spheroid model co-cultured with blood leukocytes in vitro and the MC38 murine CRC model in vivo in combination with an antibody against programmed cell death ligand-1(PD-L1).Results Inhibition of MCT4 was sufficient to reduce lactate efflux in three-dimensional (3D) CRC spheroids but not in two-dimensional cell-cultures. Co-administration of the MCT4 inhibitor and ICB augmented immune cell infiltration, T-cell function and decreased CRC spheroid viability in a 3D co-culture model of human CRC spheroids with blood leukocytes. Accordingly, combination of MCT4 and ICB increased intratumoral pH, improved leukocyte infiltration and T-cell activation, delayed tumor growth, and prolonged survival in vivo. MCT1 inhibition exerted no further beneficial impact.Conclusions These findings demonstrate that single MCT4 inhibition represents a novel therapeutic approach to reverse lactic-acid driven immunosuppression and might be suitable to improve ICB efficacy.

IntroductionThe discovery of immune checkpoints and the development of their specific inhibitors was acclaimed as a major breakthrough in cancer therapy. However, only a limited patient cohort shows sufficient response to therapy. Hence, there is a need for identifying new checkpoints and predictive biomarkers with the objective of overcoming immune escape and resistance to treatment. Having been associated with both, treatment response and failure, LDL seems to be a double-edged sword in anti-PD1 immunotherapy. Being embedded into complex metabolic conditions, the impact of LDL on distinct immune cells has not been sufficiently addressed. Revealing the effects of LDL on T cell performance in tumor immunity may enable individual treatment adjustments in order to enhance the response to routinely administered immunotherapies in different patient populations. The object of this work was to investigate the effect of LDL on T cell activation and tumor immunity in-vitro. MethodsExperiments were performed with different LDL dosages (LDLlow = 50 μg/ml and LDLhigh = 200 μg/ml) referring to medium control. T cell phenotype, cytokines and metabolism were analyzed. The functional relevance of our findings was studied in a HCT116 spheroid model in the context of anti-PD-1 blockade.ResultsThe key points of our findings showed that LDLhigh skewed the CD4+ T cell subset into a central memory-like phenotype, enhanced the expression of the co-stimulatory marker CD154 (CD40L) and significantly reduced secretion of IL-10. The exhaustion markers PD-1 and LAG-3 were downregulated on both T cell subsets and phenotypical changes were associated with a balanced T cell metabolism, in particular with a significant decrease of reactive oxygen species (ROS). T cell transfer into a HCT116 spheroid model resulted in a significant reduction of the spheroid viability in presence of an anti-PD-1 antibody combined with LDLhigh.DiscussionFurther research needs to be conducted to fully understand the impact of LDL on T cells in tumor immunity and moreover, to also unravel LDL effects on other lymphocytes and myeloid cells for improving anti-PD-1 immunotherapy. The reason for improved response might be a resilient, less exhausted phenotype with balanced ROS levels.

Abstract Vertically-aligned carbon nanotube (VaCNT) membranes allow water to conduct rapidly at low pressures and open up the possibility for water purification and desalination, although the ultralow viscous stress in hydrophobic and low-tortuosity nanopores prevents surface interactions with contaminants. In this experimental investigation, steroid hormone micropollutant adsorption by VaCNT membranes is quantified and explained via the interplay of the hydrodynamic drag and friction forces acting on the hormone, and the adhesive and repulsive forces between the hormone and the inner carbon nanotube wall. It is concluded that a drag force above 2.2 × 10−3 pN overcomes the friction force resulting in insignificant adsorption, whereas lowering the drag force from 2.2 × 10−3 to 4.3 × 10−4 pN increases the adsorbed mass of hormones from zero to 0.4 ng cm−2. At a low drag force of 1.6 × 10−3 pN, the adsorbed mass of four hormones is correlated with the hormone−wall adhesive (van der Waals) force. These findings explain micropollutant adsorption in nanopores via the forces acting on the micropollutant along and perpendicular to the flow, which can be exploited for selectivity.

Abstract Through silicon vias (TSVs) are a key enabling technology for interconnection and realization of complex three‐dimensional integrated circuit (3D‐IC) components. In order to perform failure analysis without the need of destructive sample preparation, x‐ray microscopy (XRM) is a rising method of analyzing the internal structure of samples. However, there is still a lack of evaluated scan recipes or best practices regarding XRM parameter settings for the study of TSVs in the current state of literature. There is also an increased interest in automated machine learning and deep learning approaches for qualitative and quantitative inspection processes in recent years. Especially deep learning based object detection is a well‐known methodology for fast detection and classification capable of working with large volumetric XRM datasets. Therefore, a combined XRM and deep learning object detection workflow for automatic micrometer accurate defect location on liner‐TSVs was developed throughout this work. Two measurement setups including detailed information about the used parameters for either full IC device scan or detailed TSV scan were introduced. Both are able to depict delamination defects and finer structures in TSVs with either a low or high resolution. The combination of a 0.4×$$ imes $$ objective with a beam voltage of 40 kV proved to be a good combination for achieving optimal imaging contrast for the full‐device scan. However, detailed TSV scans have demonstrated that the use of a 20×$$ imes $$ objective along with a beam voltage of 140 kV significantly improves image quality. A database with 30,000 objects was created for automated data analysis, so that a well‐established object recognition method for automated defect analysis could be integrated into the process analysis. This RetinaNet‐based object detection method achieves a very strong average precision of 0.94. It supports the detection of erroneous TSVs in both top view and side view, so that defects can be detected at different depths. Consequently, the proposed workflow can be used for failure analysis, quality control or process optimization in R&D environments.

This study demonstrates the synthesis and characterisation of electrospun Ta3N5-(O) 1D-nanofibers for electrocatalytic hydrogen evolution reaction (HER) and its performance in a proton exchange membrane (PEM) water electrolyser. 1D nanofibers were synthesized by electrospinning of tantalum ethoxide/polyvinylpyrrolidone (PVP) sol followed by ammonolysis at varied temperatures (800–1000 °C). Elemental distribution of the nanofibers analysed through XPS, and bulk-EDS studies revealed an increase in surface oxygen concentration with an increase in nitridation temperature (from 900 °C to 1000 °C). The nanofibers were characterized to exhibit high electrocatalytic activity for hydrogen evolution reaction (HER) with a low overpotential of 320 mV to deliver 10 mA/cm2 in 0.5 M H2SO4 electrolyte. The Ta3N5-(O) 1D nanofibers were employed as novel electrocatalyst without any conducting supports in a PEM water electrolyser. A current density of 0.1 A/cm2 was achieved at an applied voltage of 2 V which is on par with earth-abundant electrocatalysts like MoS2. Furthermore, the electrospun nano fibers showed excellent stability with negligible losses over 6 h of prolonged operation. The study demonstrates the advantage of nanostructuring the electrocatalysts in enhancing the applicability of Ta3N5 and paves further a path for the development of high performance 1-D electrocatalysts for hydrogen evolution reactions (HER).

The autocatalytic growth of arbitrarily shaped nanostructures fabricated by electron beam-induced deposition (EBID) and electron beam-induced surface activation (EBISA) is studied for two precursors: iron pentacarbonyl, Fe(CO)5, and cobalt tricarbonyl nitrosyl, Co(CO)3NO. Different deposits are prepared on silicon nitride membranes and silicon wafers under ultrahigh vacuum conditions, and are studied by scanning electron microscopy (SEM) and scanning transmission X-ray microscopy (STXM), including near edge X-ray absorption fine structure (NEXAFS) spectroscopy. It has previously been shown that Fe(CO)5 decomposes autocatalytically on Fe seed layers (EBID) and on certain electron beam-activated surfaces, yielding high purity, polycrystalline Fe nanostructures. In this contribution, we investigate the growth of structures from Co(CO)3NO and compare it to results obtained from Fe(CO)5. Co(CO)3NO exhibits autocatalytic growth on Co-containing seed layers prepared by EBID using the same precursor. The growth yields granular, oxygen-, carbon- and nitrogen-containing deposits. In contrast to Fe(CO)5 no decomposition on electron beam-activated surfaces is observed. In addition, we show that the autocatalytic growth of nanostructures from Co(CO)3NO can also be initiated by an Fe seed layer, which presents a novel approach to the fabrication of layered nanostructures.

BACKGROUND: Premenstrual syndrome (PMS) is characterized by a cluster of psychological and somatic symptoms during the late luteal phase of the menstrual cycle that disappear after the onset of menses. Behavioral differences in emotional and cognitive processing have been reported in women with PMS, and it is of particular interest whether PMS affects the parallel execution of emotional and cognitive processing. Related to this is the question of how the performance of women with PMS relates to stress levels compared to women without PMS. Cortisol has been shown to affect emotional processing in general and it has also been shown that women with severe PMS have a particular cortisol profile. METHODS: We measured performance in an emotional conflict task and stress levels in women with PMS (n = 15) and women without PMS (n = 15) throughout their menstrual cycle. RESULTS: We found a significant increase (p = 0.001) in the mean reaction time for resolving emotional conflict from the follicular to the luteal cycle phase in all subjects. Only women with PMS demonstrated an increase in physiological and subjective stress measures during the luteal menstrual cycle phase. CONCLUSIONS: Our findings suggest that the menstrual cycle modulates the integration of emotional and cognitive processing in all women. Preliminary data are supportive of the secondary hypothesis that stress levels are mediated by the menstrual cycle phase only in women with PMS. The presented evidence for menstrual cycle-specific differences in integrating emotional and cognitive information highlights the importance of controlling for menstrual cycle phase in studies that aim to elucidate the interplay of emotion and cognition.