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Abstract Self-rectifying memristive devices have emerged as promising contenders for low-power in-memory computing, presenting numerous advantages. However, characterizing the functional behavior of passive crossbar arrays incorporating these devices remains challenging due to sophisticated parasitic currents stemming from rich memristive dynamic behavior. Conventional methods using read margin assessments to evaluate functional behavior in passive crossbars are hindered by the voltage divider effect from the pull-up resistor. In this study, we propose a novel performance metric, $$\Delta$$ Δ SC, harnessing sneak path currents to assess functional behavior. Through the application of a pair of negative rectification factors, $$\text {RF}_\text {n, L}$$ RF n, L and $$\text {RF}_\text {n, H}$$ RF n, H , we comprehensively delineate dynamic rectification behavior in both positive and negative bias regimes, as well as in low-resistance state and high-resistance state, deviating from conventional metrics such as on/off ratios, nonlinearity, and rectifying factors. Notably, $$\Delta$$ Δ SC provides a quantitative evaluation of the interaction between sneak path currents and read margin, demonstrating its efficacy and addressing a pivotal research gap in the field. For instance, employing self-rectifying BiFeO $$_3$$ 3 memristive cells featuring $$\text {RF}_\text {n, L}$$ RF n, L = 1.22E3 and $$\text {RF}_\text {n, H}$$ RF n, H = 9.27, we showcase the successful functional performance of a passive crossbar array, achieving $$\Delta$$ Δ SC < 2.19E−2, while ensuring a read margin > 0.

Abstract Resistive Random Access Memory (RRAM) has gained considerable momentum due to its non-volatility and energy efficiency. Material and device scientists have been proposing novel material stacks that can mimic the “ideal memristor” which can deliver performance, energy efficiency, reliability and accuracy. However, designing RRAM-based systems is challenging. Engineering a new material stack, designing a device, and experimenting takes significant time for material and device researchers. Furthermore, the acceptability of the device is ultimately decided at the system level. We see a gap here where there is a need for facilitating material and device researchers with a “push button” modeling framework that allows to evaluate the efficacy of the device at system level during early device design stages. Speed, accuracy, and adaptability are the fundamental requirements of this modelling framework. In this paper, we propose a digital twin (DT)-like modeling framework that automatically creates RRAM device models from device measurement data. Furthermore, the model incorporates the peripheral circuit to ensure accurate energy and performance evaluations. We demonstrate the DT generation and DT usage for multiple RRAM technologies and applications and illustrate the achieved performance of our GPU implementation. We conclude with the application of our modeling approach to measurement data from two distinct fabricated devices, validating its effectiveness in a neural network processing an Electrocardiogram (ECG) dataset and incorporating Fault Aware Training (FAT).

Abstract Due to their exceptional solubility and stability, nanobodies have emerged as powerful building blocks for research tools and therapeutics. However, their generation in llamas is cumbersome and costly. Here, by inserting an engineered llama immunoglobulin heavy chain (IgH) locus into IgH-deficient mice, we generate a transgenic mouse line, which we refer to as ‘LamaMouse’. We demonstrate that LamaMice solely express llama IgH molecules without association to Igκ or λ light chains. Immunization of LamaMice with AAV8, the receptor-binding domain of the SARS-CoV-2 spike protein, IgE, IgG2c, and CLEC9A enabled us to readily select respective target-specific nanobodies using classical hybridoma and phage display technologies, single B cell screening, and direct cloning of the nanobody-repertoire into a mammalian expression vector. Our work shows that the LamaMouse represents a flexible and broadly applicable platform for a facilitated selection of target-specific nanobodies.

Immune exhaustion is a hallmark of ovarian cancer. Using multiparametric flow cytometry, the study aimed to analyze protein expression of novel immunological targets on CD3+ T cells isolated from the peripheral blood (n = 20), malignant ascites (n = 16), and tumor tissue (n = 6) of patients with ovarian cancer (OVCA). The study revealed an increased proportion of effector memory CD8+ T cells in OVCA tissue and malignant ascites. An OVCA-characteristic PD-1high CD8+ T cell population was detected, which differed from PD-1lowCD8+ T cells by increased co-expression of TIGIT, CD39, and HLA-DR. In addition, these OVCA-characteristic CD8+ T cells showed reduced expression of the transcription factor TCF-1, which may also indicate reduced effector function and memory formation. On the contrary, the transcription factor TOX, which significantly regulates terminal T cell-exhaustion, was found more frequently in these cells. Further protein and gene analysis showed that CD39 and CD73 were also expressed on OVCA tumor cells isolated from solid tumors (n = 14) and malignant ascites (n = 9). In the latter compartment, CD39 and CD73 were also associated with the expression of the “don’t eat me” molecule CD24 on tumor cells. Additionally, ascites-derived CD24+EpCAM+ tumor cells showed a higher frequency of CD39+ or CD73+ cells. Furthermore, CD39 expression was associated with unfavorable clinical parameters. Expression of CD39 on T cells was upregulated through CD3/CD28 stimulation and its blockade by a newly developed nanobody construct resulted in increased proliferation (eFluor), activation (CD25 and CD134), and production of cytotoxic cytokines (IFN-γ, TNF-α, and granzyme-B) of CD8+ T cells.

CD39 is the major enzyme controlling the levels of extracellular adenosine triphosphate (ATP) via the stepwise hydrolysis of ATP to adenosine diphosphate (ADP) and adenosine monophosphate (AMP). As extracellular ATP is a strong promoter of inflammation, monoclonal antibodies (mAbs) blocking CD39 are utilized therapeutically in the field of immune-oncology. Though anti-CD39 mAbs are highly specific for their target, they lack deep penetration into the dense tissue of solid tumors, due to their large size. To overcome this limitation, we generated and characterized nanobodies that targeted and blocked human CD39. From cDNA-immunized alpacas we selected 16 clones from seven nanobody families that bind to two distinct epitopes of human CD39. Among these, clone SB24 inhibited the enzymatic activity of CD39. Of note, SB24 blocked ATP degradation by both soluble and cell surface CD39 as a 15kD monomeric nanobody. Dimerization via fusion to an immunoglobulin Fc portion further increased the blocking potency of SB24 on CD39-transfected HEK cells. Finally, we confirmed the CD39 blocking properties of SB24 on human PBMCs. In summary, SB24 provides a new small biological antagonist of human CD39 with potential application in cancer therapy.

Computing‐in‐memory (CIM) is a promising approach for overcoming the memory‐wall problem in conventional von‐Neumann architectures. This is done by performing certain computation tasks directly in the storage subsystem without transferring data between storage and processing units. Stateful and non‐stateful CIM concepts are recently attracting lots of interest, which are demonstrated as logical complete, energy efficient, and compatible with dense crossbar structures. However, sneak‐path currents in passive resistive random access memory (RRAM) crossbars degrade the operation reliability and require the usage of active 1 Transistor–1 Resistance (1T‐1R) bitcell designs. In this article, the arithmetic performance and reliability are investigated based on experimental measurements and variability‐aware circuit simulations. Herein, it is aimed for the evaluation of logic operations specifically with fully integrated 1T–1R crossbar devices. Based on these operations, an N‐bit full adder with optimized energy consumption and latency is demonstrated by combining stateful and non‐stateful CIM logic styles with regard to the specific conditions in active 1T–1R RRAM crossbars.

Abstract Memristive devices with valence change mechanism (VCM) show promise for neuromorphic data processing, although emulation of synaptic behavior with analog weight updates remains a challenge. Standard filamentary and area‐dependent resistive switching exhibit characteristic differences in the transition from the high to low resistance state, which is either abrupt with inherently high variability or gradual and allows quasi‐analog operation. In this study, the two switching modes are clearly correlated to differences in the microstructure and electronic structure for Pt/Al2O3/TiOx/Cr/Pt devices made from amorphous layers of 1.2 nm Al2O3 and 7 nm TiOx by atomic layer deposition. For the filamentary mode, operando spectromicroscopy experiments identify a localized region of ≈50 nm in diameter of reduced titania surrounded by crystalline rutile‐like TiO2, highlighting the importance of Joule heating for this mode. In contrast, both oxide layers remain in their amorphous state for the interfacial mode, which proves that device temperature during switching stays below 670 K, which is the TiO2 crystallization temperature. The analysis of the electronic conduction behavior confirms that the interfacial switching occurs by modulating the effective tunnel barrier width due to accumulation and depletion of oxygen vacancies at the Al2O3/TiOx interface. The results are transferable to other bilayer stacks.

Resistive switching devices are candidates to be used as weight for the future hardware realization of neuronal networks. Herein, these resistive switches base on oxygen vacancy migration and can be toggled between different resistance states. Internal processes lead to a variability over time in these states. To understand this, a dynamical model is developed, which links the internal physical mechanism to the current response. Thereby, the electronic current is calculated by tunneling processes over oxygen vacancies. The model allows to understand the physical transport properties and the current–voltage dependence. Integrating ionic hopping processes clarifies the variability in the electronic conduction. The derived model does not require empirical input parameters and only depends on the properties of the materials. This allows to use literature values and independently compare them to electrical measurements. The model predicts the experiments correctly. Thereupon, the physical properties of the conduction are investigated with respect to the transport over discrete energy levels, which change under the hopping of oxygen vacancies. Afterwards, the current level and variability are simulated for increasing oxygen vacancy concentrations to investigate analog switching, which is required for neuronal network layers. Finally, the variability is tested with multiple interacting cells in a neuronal layer.

Resistively switching electrochemical metallization memory cells are gaining huge interest since they are seen as promising candidates and basic building blocks for future computation-in-memory applications. However, especially filamentary-based memristive devices suffer from inherent variability, originating from their stochastic switching behavior. A variability-aware compact model of electrochemical metallization memory cells is presented in this study and verified by showing a fit to experimental data. It is an extension of the deterministic model. Since this extension consists of several different features allowing for a realistic variability-aware fit, it depicts a unique model comprising physics-based, stochastically and experimentally originating variabilities and reproduces them well. In addition, a physics-based model parameter study is executed, which enables a comprehensive view into the device physics and presents guidelines for the compact model fitting procedure.

Analog compute schemes and compute-in-memory (CIM) have emerged in an effort to reduce the increasing power hunger of convolutional neural networks (CNNs), which exceeds the constraints of edge devices. Memristive device types are a relatively new offering with interesting opportunities for unexplored circuit concepts. In this work, the use of memristive devices in cascaded time-domain CIM (TDCIM) is introduced with the primary goal of reducing the size of fully unrolled architectures. The different effects influencing the determinism in memristive devices are outlined together with reliability concerns. Architectures for binary as well as multibit multiply and accumulate (MAC) cells are presented and evaluated. As more involved circuits offer more accurate compute result, a tradeoff between design effort and accuracy comes into the picture. To further evaluate this tradeoff, the impact of variations on overall compute accuracy is discussed. The presented cells reach an energy/OP of 0.23 fJ at a size of $1.2~{\mu{ }}\text{m}^{2}$ for binary and 6.04 fJ at $3.2~\mu \text{m}^{2}$ for $4\times 4$ bit MAC operations.

In this work, we experimentally characterize the endurance of 2 Mbit resistive switching random access memories (ReRAMs) from a 16 MBit test-chip. Here, very rare failure events where the memory cells become stuck in the low-resistive state (LRS) are observed. As this failure mechanism is the limiting one concerning the endurance of this ReRAM implementation, extensive investigations are conducted and presented. The experimental findings are detailed via a voltage divider model, illustrating why memory cells can become stuck in the LRS. It is proposed, that an insufficient voltage dropping over the cell due to an unfavorable combination of cell- and transistor resistances is responsible for stuck-at-LRS bits. Furthermore, predictions for the origin of these suboptimal combinations are given. Additionally, a one-dimensional Kinetic Monte Carlo (KMC) model that allows a statistical investigation of large numbers of cells with regard to rare random events has been developed. Here, our proposed explanation for the observed failure mechanism is fortified by the simulation and evaluation of the switching process of the memory. All simulations are in very good agreement with the experimental data. Finally, based on our findings, we give suggestions for the improvement of switching algorithms.

The proliferation of machine learning algorithms in everyday applications such as image recognition or language translation has increased the pressure to adapt underlying computing architectures towards these algorithms. Application specific integrated circuits (ASICs) such as the Tensor Processing Units by Google, Hanguang by Alibaba or Inferentia by Amazon Web Services were designed specifically for machine learning algorithms and have been able to outperform CPU based solutions by great margins during training and inference. As newer generations of chips allow handling of and computation on more and more data, the size of neural networks has dramatically increased, while the challenges they are trying to solve have become more complex. Neuromorphic computing tries to take inspiration from biological information processing systems, aiming to further improve the efficiency with which these networks can be trained or the inference can be performed. Enhancing neuromorphic computing architectures with memristive devices as non-volatile storage elements could potentially allow for even higher energy efficiencies. Their ability to mimic synaptic plasticity dynamics brings neuromorphic architectures closer to the biological role models. So far, memristive devices are mainly investigated for the emulation of the weights of neural networks during training and inference as their non-volatility would enable both processes in the same location without data transfer. In this paper, we explore realisations of different synapses build from memristive ReRAM devices, based on the Valence Change Mechanism. These synapses are the 1R synapse, the NR synapse and the 1T1R synapse. For the 1R synapse, we propose three dynamical regimes and explore their performance through different synapse criteria. For the NR synapse, we discuss how the same dynamical regimes can be addressed in a more reliable way. We also show experimental results measured on ZrOx devices to support our simulation based claims. For the 1T1R synapse, we explore the trade offs between the connection direction of the ReRAM device and the transistor. For all three synapse concepts we discuss the impact of device-to-device and cycle-to-cycle variability. Additionally, the impact of the stimulation mode on the observed behavior is discussed.

Abstract Background: Hamburg is a city state of approximately 1.9 Mio inhabitants in Northern Germany. Currently, the COVID‐19 epidemic that had largely subsided during last summer is resurging in Hamburg and in other parts of the world, underlining the need for additional tools to monitor SARS‐CoV‐2 antibody responses. Aim: We aimed to develop and validate a simple, low‐cost assay for detecting antibodies against the native coronavirus 2 spike protein (CoV‐2 S) that does not require recombinant protein or virus. Method: We transiently co‐transfected HEK cells or CHO cells with expression vectors encoding CoV‐2 S and nuclear GFP. Spike protein‐specific antibodies in human serum samples bound to transfected cells were detected with fluorochrome conjugated secondary antibodies by flow cytometry orimmunofluorescence microscopy. We applied this assay to monitor antibody development in COVID‐19 patients, household contacts, and hospital personnel during the ongoing epidemic in the city state of Hamburg. Results: All recovered COVID‐19 patients showed high levels of CoV‐2 S‐specific antibodies. With one exception, all household members that did not develop symptoms also did not develop detectable antibodies. Similarly, lab personnel that worked during the epidemic and followed social distancing guidelines remained antibody‐negative. Conclusion: We conclude that high‐titer CoV‐2 S‐specific antibodies are found in most recovered COVID‐19 patients and in symptomatic contacts, but only rarely in asymptomatic contacts. The assay may help health care providers to monitor disease progression and antibody responses in vaccination trials, to identify health care personnel that likely are resistant to re‐infection, and recovered individuals with high antibody titers that may be suitable asplasma and/or antibody donors.

Adenosine triphosphate (ATP) represents a danger signal that accumulates in injured tissues, in inflammatory sites, and in the tumor microenvironment. ATP promotes tumor growth but also anti-tumor immune responses notably via the P2X7 receptor. ATP can also be catabolized by CD39 and CD73 ecto-enzymes into immunosuppressive adenosine. P2X7, CD39 and CD73 have attracted much interest in cancer as targets offering the potential to unleash anti-tumor immune responses. These membrane proteins represent novel purinergic checkpoints that can be targeted by small drugs or biologics. Here, we investigated nanobody-based biologics targeting mainly P2X7, but also CD73, alone or in combination therapies. Blocking P2X7 inhibited tumor growth and improved survival of mice in cancer models that express P2X7. P2X7-potentiation by a nanobody-based biologic was not effective alone to control tumor growth but enhanced tumor control and immune responses when used in combination with oxaliplatin chemotherapy. We also evaluated a bi-specific nanobody-based biologic that targets PD-L1 and CD73. This novel nanobody-based biologic exerted a potent anti-tumor effect, promoting tumor rejection and improving survival of mice in two tumor models. Hence, this study highlights the importance of purinergic checkpoints in tumor control and open new avenues for nanobody-based biologics that may be further exploited in the treatment of cancer.

This review provides a comprehensive examination of the state-of-the-art research on resistive switching (RS) in BiFeO3 (BFO)-based memristive devices. By exploring possible fabrication techniques for preparing the functional BFO layers in memristive devices, the constructed lattice systems and corresponding crystal types responsible for RS behaviors in BFO-based memristive devices are analyzed. The physical mechanisms underlying RS in BFO-based memristive devices, i.e., ferroelectricity and valence change memory, are thoroughly reviewed, and the impact of various effects such as the doping effect, especially in the BFO layer, is evaluated. Finally, this review provides the applications of BFO devices and discusses the valid criteria for evaluating the energy consumption in RS and potential optimization techniques for memristive devices.

Abstract The inevitable variability within electronic devices causes strict constraints on operation, reliability and scalability of the circuit design. However, when a compromise arises among the different performance metrics, area, time and energy, variability then loosens the tight requirements and allows for further savings in an alternative design scope. To that end, unconventional computing approaches are revived in the form of approximate computing, particularly tuned for resource-constrained mobile computing. In this paper, a proof-of-concept of the approximate computing paradigm using memristors is demonstrated. Stochastic memristors are used as the main building block of probabilistic logic gates. As will be shown in this paper, the stochasticity of memristors’ switching characteristics is tightly bound to the supply voltage and hence to power consumption. By scaling of the supply voltage to appropriate levels stochasticity gets increased. In order to guide the design process of approximate circuits based on memristors a realistic device model needs to be elaborated with explicit emphasis of the probabilistic switching behavior. Theoretical formulation, probabilistic analysis, and simulation of the underlying logic circuits and operations are introduced. Moreover, the expected output behavior is verified with the experimental measurements of valence change memory cells. Hence, it is shown how the precision of the output is varied for the sake of the attainable gains at different levels of available design metrics. This approach represents the first proposition along with physical verification and mapping to real devices that combines stochastic memristors into unconventional computing approaches.

Abstract Understanding the interplay of genetic factors with haemoglobin expression and pathological processes in sickle cell disease is important for pharmacological and gene‐therapeutic interventions. In our nascent study cohort of Nigerian patients, we found that three major disease‐modifying factors, HbF levels, α‐thalassaemia deletion and BCL11A genotype, had expected beneficial haematological effects. A key BCL11A variant, while improving HbF levels (5.7%–9.0%), also led to a small, but significant decrease in HbA2. We conclude that in general, interventions boosting HbF are likely to reduce HbA2 in patients’ erythroid cells and that such therapeutic strategies might benefit from a parallel stimulation of HbA2 through independent mechanisms.

Abstract Background Though case reports and limited case series of Sickle cell disease in Sri Lanka have been reported previously, no attempt has been made hitherto to undertake a comprehensive genotypic-phenotypic analysis of this “rare” group of patients. Results All accessible Sickle cell disease patients, totaling 60, including, 51 Sickle β-thalassaemia and 9 homozygous sickle patients were enrolled from seven thalassaemia treatment centres between December 2016–March 2019. The majority of patients were of Sinhalese ethnicity (n = 52, 86.67%). Geographically, two prominent clusters were identified and the distribution of Sickle haemoglobin in the island contrasted markedly with the other haemoglobinopathies. 3/ 9 homozygous sickle patients and 3/ 51 Sickle β-thalassaemia patients were receiving regular transfusion. Joint pain was the commonest clinical symptom among all sickle cell disease patients (n = 39, 65.0%). Dactylitis was significantly more common in homozygous sickle patients compared with the Sickle β-thalassaemia groups (p 0.027). Two genetic backgrounds sickle mutation were identified namely, Arab Indian and Benin. Among the regulators of Foetal hemoglobin in Sickle patients of the present study rs1427407 G > T seemed to be the most prominent modifier, with a significant association with Foetal haemoglobin levels (p 0.04). Conclusions Overall, the clinical course of the Asian version of Sickle cell disease in Sri Lanka appears to be milder than that described in India.

Abstract Background Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common genetic variants which differ across populations and hence do not fully account for HbF variation. Methods We investigated rare and common genetic variants that influence HbF levels in 14 SCD patients to elucidate variants and pathways in SCD patients with extreme HbF levels (≥7.7% for high HbF) and (≤2.5% for low HbF) in Tanzania. We performed targeted next generation sequencing (Illumina_Miseq) covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. Results Results revealed a range of genetic variants, including bi-allelic and multi-allelic SNPs, frameshift insertions and deletions, some of which have functional importance. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletions in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. Conclusions This study provides new insights in selecting essential variants and identifying potential biological pathways associated with extreme HbF levels in SCD interrogating multiple genomic variants associated with HbF in SCD.

Antigen recognition by the T-cell receptor induces a cytosolic Ca2+ signal that is crucial for T-cell function. The Ca2+ channel TRPM2 (transient receptor potential cation channel subfamily M member 2) has been shown to facilitate influx of extracellular Ca2+ through the plasma membrane of T cells. Therefore, it was suggested that TRPM2 is involved in T-cell activation and differentiation. However, these results are largely derived from in vitro studies using T-cell lines and non-physiologic means of TRPM2 activation. Thus, the relevance of TRPM2-mediated Ca2+ signaling in T cells remains unclear. Here, we use TRPM2-deficient mice to investigate the function of TRPM2 in T-cell activation and differentiation. In response to TCR stimulation in vitro, Trpm2-/- and WT CD4+ and CD8+ T cells similarly upregulated the early activation markers NUR77, IRF4, and CD69. We also observed regular proliferation of Trpm2-/- CD8+ T cells and unimpaired differentiation of CD4+ T cells into Th1, Th17, and Treg cells under specific polarizing conditions. In vivo, Trpm2-/- and WT CD8+ T cells showed equal specific responses to Listeria monocytogenes after infection of WT and Trpm2-/- mice and after transfer of WT and Trpm2-/- CD8+ T cells into infected recipients. CD4+ T-cell responses were investigated in the model of anti-CD3 mAb-induced intestinal inflammation, which allows analysis of Th1, Th17, Treg, and Tr1-cell differentiation. Here again, we detected similar responses of WT and Trpm2-/- CD4+ T cells. In conclusion, our results argue against a major function of TRPM2 in T-cell activation and differentiation.

Memristive devices based on the Valence Change Mechanism (VCM) are promising devices for storage class memory, neuromorphic computing and logic-in-memory (LIM) applications. They are suited for such a wide range of applications, due to their possibility for extreme dense integration, low power consumption and multilevel capabilities. Through LIM concepts, Boolean logic operations can be performed directly in memory. In many of these concepts, the resistance state of the device is interpreted as the logical input and output of the logic function, which is why these concepts are called ‘stateful’ logic. Most of the proposed ideas, however, are defined based on only binary switching VCM devices and neglect their multi-level capabilities. Extending LIM concepts towards multinary logic, e.g. a ternary logic, would increase the data density inside the memory array and reduce the number of devices required to perform a certain operation. In this work, we discuss two possibilities of realizing a ternary logic based on the analog switching in the RESET or in the SET direction. For both directions we verify the logic functionality by showing the basic operations of implication, negation and false operation, which together form a functionally complete logic. Additionally, for both switching directions, we discuss a 41-Trit ( ${\approx}$ 64-Bit) addition. For all investigations the physics-based compact model JART VCM v1b is used, which has been verified on the RESET direction multilevel properties of the TaO $_{\mathrm{x}}$ devices.

Electrochemical metallization (ECM) cells are based on the principle of voltage controlled formation or dissolution of a nanometer-thin metallic conductive filament (CF) between two electrodes separated by an insulating material, e.g. an oxide. The lifetime of the CF depends on factors such as materials and biasing. Depending on the lifetime of the CF—from microseconds to years—ECM cells show promising properties for use in neuromorphic circuits, for in-memory computing, or as selectors and memory cells in storage applications. For enabling those technologies with ECM cells, the lifetime of the CF has to be controlled. As various authors connect the lifetime with the morphology of the CF, the key parameters for CF formation have to be identified. In this work, we present a 2D axisymmetric physical continuum model that describes the kinetics of volatile and non-volatile ECM cells, as well as the morphology of the CF. It is shown that the morphology depends on both the amplitude of the applied voltage signal and CF-growth induced mechanical stress within the oxide layer. The model is validated with previously published kinetic measurements of non-volatile Ag/SiO _2 /Pt and volatile Ag/HfO _2 /Pt cells and the simulated CF morphologies are consistent with previous experimental CF observations.

CD38 is the major NAD+-hydrolyzing ecto-enzyme in most mammals. As a type II transmembrane protein, CD38 is also a promising target for the immunotherapy of multiple myeloma (MM). Nanobodies are single immunoglobulin variable domains from heavy chain antibodies that naturally occur in camelids. Using phage display technology, we isolated 13 mouse CD38-specific nanobodies from immunized llamas and produced these as recombinant chimeric mouse IgG2a heavy chain antibodies (hcAbs). Sequence analysis assigned these hcAbs to five distinct families that bind to three non-overlapping epitopes of CD38. Members of families 4 and 5 inhibit the GDPR-cyclase activity of CD38. Members of families 2, 4 and 5 effectively induce complement-dependent cytotoxicity against CD38-expressing tumor cell lines, while all families effectively induce antibody dependent cellular cytotoxicity. Our hcAbs present unique tools to assess cytotoxicity mechanisms of CD38-specific hcAbs in vivo against tumor cells and potential off-target effects on normal cells expressing CD38 in syngeneic mouse tumor models, i.e. in a fully immunocompetent background.

Mouse T cells express the ecto-ADP-ribosyltransferase ARTC2.2, which can transfer the ADP-ribose group of extracellular nicotinamide adenine dinucleotide (NAD+) to arginine residues of various cell surface proteins thereby influencing their function. Several targets of ARTC2.2, such as P2X7, CD8a and CD25 have been identified, however a comprehensive mouse T cell surface ADP-ribosylome analysis is currently missing. Using the Af1521 macrodomain-based enrichment of ADP-ribosylated peptides and mass spectrometry, we identified 93 ADP-ribsoylated peptides corresponding to 67 distinct T cell proteins, including known targets such as CD8a and CD25 but also previously unknown targets such as CD73. We evaluated the impact of ADP-ribosylation on the capability of CD73 to generate adenosine from adenosine monophosphate. Our results show that extracellular NAD+ reduces the enzymatic activity of CD73 HEK cells co-transfected with CD73/ARTC2.2. Importantly, NAD+ significantly reduced CD73 activity on WT CD8 T cells compared to ARTC2ko CD8 T cells or WT CD8 T cells treated with an ARTC2.2-blocking nanobody. Our study provides a comprehensive list of T cell membrane proteins that serve as targets for ADP-ribosylation by ARTC2.2 and whose function may be therefore affected by ADP-ribosylation.

With the arrival of the Internet of Things (IoT) and the challenges arising from Big Data, neuromorphic chip concepts are seen as key solutions for coping with the massive amount of unstructured data streams by moving the computation closer to the sensors, the so-called “edge computing.” Augmenting these chips with emerging memory technologies enables these edge devices with non-volatile and adaptive properties which are desirable for low power and online learning operations. However, an energy- and area-efficient realization of these systems requires disruptive hardware changes. Memristor-based solutions for these concepts are in the focus of research and industry due to their low-power and high-density online learning potential. Specifically, the filamentary-type valence change mechanism (VCM memories) have shown to be a promising candidate In consequence, physical models capturing a broad spectrum of experimentally observed features such as the pronounced cycle-to-cycle (c2c) and device-to-device (d2d) variability are required for accurate evaluation of the proposed concepts. In this study, we present an in-depth experimental analysis of d2d and c2c variability of filamentary-type bipolar switching HfO2/TiOx nano-sized crossbar devices and match the experimentally observed variabilities to our physically motivated JART VCM compact model. Based on this approach, we evaluate the concept of parallel operation of devices as a synapse both experimentally and theoretically. These parallel synapses form a synaptic array which is at the core of neuromorphic chips. We exploit the c2c variability of these devices for stochastic online learning which has shown to increase the effective bit precision of the devices. Finally, we demonstrate that stochastic switching features for a pattern classification task that can be employed in an online learning neural network.

Abstract Background We aimed to evaluate the long-term clinical and socioeconomic outcome of structured transition care in adolescents with inflammatory bowel disease (IBD). Methods We compared the clinical long-term course of 24 patients with and 11 patients without structured transition care within 24 months before and 24 months after transfer from paediatric to adult health care. Socio-economic parameters and quality of life were assessed by IBD Questionnaire (IBDQ-32) and additional items. Treatment costs were calculated for medication, surgery and hospitalisation. Results The percentage of transfer group patients with an IBD-related intestinal complication was higher compared to the transition group (64% vs. 21%, p = 0.022). We also found a tendency towards a higher number of IBD-related surgery in the transfer group compared to the transition group (46% vs. 13%, p = 0.077). Transfer group patients received higher mean cumulated doses of radiation compared with the transition group (4.2 ± 5.3 mSv vs. 0.01 ± 0.01 mSv, p = 0.036). Delayed puberty was only noted in the transfer group (27%, p = 0.025). Mean expenditures for surgeries and hospitalisation tended to be lower in the transition group compared to transfer group patients (744 ± 630€ vs. 2,691 ± 4,150€, p = 0.050). Sexual life satisfaction was significantly higher (p = 0.023) and rates of loose bowel movements tended to be lower (p = 0.053) in the transition group. Conclusions Structured transition of adolescents with IBD from paediatric into adult health care can lead to important clinical and economic benefits.

Murine T cells express the GPI-anchored ADP-ribosyltransferase 2.2 (ARTC2.2) on the cell surface. In response to T cell activation or extracellular NAD+ or ATP-mediated gating of the P2X7 ion channel ARTC2.2 is shed from the cell surface as a soluble enzyme. Shedding alters the target specificity of ARTC2.2 from cell surface proteins to secreted proteins. Here we demonstrate that shed ARTC2.2 potently ADP-ribosylates IFN-γ in addition to other cytokines. Using mass spectrometry, we identify arginine 128 as the target site of ADP-ribosylation. This residue has been implicated to play a key role in binding of IFN-γ to the interferon receptor 1 (IFNR1). Indeed, binding of IFN-γ to IFNR1 blocks ADP-ribosylation of IFN-γ. Moreover, ADP-ribosylation of IFN-γ inhibits the capacity of IFN-γ to induce STAT1 phosphorylation in macrophages and upregulation of the proteasomal subunit ß5i and the proteasomal activator PA28-α in podocytes. Our results show that ADP-ribosylation inhibits the signaling functions of IFN-γ and point to a new regulatory mechanism for controlling signaling by IFN-γ.

Phenotypic characterization of γδ T cells in the MALs (malignant ascites lymphocytes), TILs (tumor infiltrating lymphocytes), and PBLs (peripheral blood lymphocytes) of ovarian cancer (OvCA) patients is lacking. Therefore, we quantified γδ T cell prevalence in MAL, TIL, and PBL specimens from n = 18 OvCA patients and PBL from age-matched healthy donors (HD, n = 14). Multicolor flow cytometry was performed to evaluate the expression of inhibitory receptors (TIGIT, PD-1 and TIM-3), stimulatory receptors (Ox40), and purinergic ectoenzymes (CD39 and CD73) on γδ T cell subsets. We identified an abundant infiltration of Vδ1 T cells in the MALs and TILs. These cells varied in their differentiation: The majority of Vδ1 TILs displayed an effector memory (EM) phenotype, whereas Vδ1 MALs had a more mature phenotype of terminally differentiated effector memory cells (TEMRA) with high CD45RA expression. TIGIT and TIM-3 were abundantly expressed in both MALs and PBLs, whereas Vδ1 TILs exhibited the highest levels of PD-1, CD39, and Ox40. We also observed specific clusters on mature differentiation stages for the analyzed molecules. Regarding co-expression, Vδ1 TILs showed the highest levels of cells co-expressing TIGIT with PD-1 or CD39 compared to MALs and PBLs. In conclusion, the Vδ1 T cell population showed a high prevalence in the MALs and primary tumors of OvCA patients. Due to their (co-)expression of targetable immune receptors, in particular TIGIT with PD-1 and CD39 in TILs, Vδ1 T cell-based approaches combined with the inhibition of these targets might represent a promising strategy for OvCA.

This work studies a computation in‐memory concept for binary multiply‐accumulate operations based on complementary resistive switches (CRS). By exploiting the in‐memory boolean exclusive OR (XOR) operation of single CRS devices, the Hamming Distance (HD) can be calculated if the center electrodes of multiple CRS cells are connected. This HD is linearly encoded in the voltage drop of the common electrode, and from it the result of a binary multiply‐accumulate operation can be calculated. A small‐scale demonstration is experimentally realized and the feasibility of the in‐memory computation concept is confirmed. A simulation study identifies the low resistance state (LRS) variability as the main reason for the variations in the output voltage. The application as a potential hardware accelerator for the inference step of binary neural networks is investigated. Therefore, a 1‐layer fully connected neural network is trained on a binarized version of the MNIST data set and the inference step of the test data set is simulated. The concept achieves a prediction accuracy of approximately 86%.

ADP-ribosylation of the P2X7k splice variant on mouse T cells by Ecto-ADP-ribosyltransferase ARTC2.2 in response to its substrate extracellular nicotinamide adenine dinucleotide (NAD+) triggers cell death. Since NAD+ is released as a danger signal during tissue damage, this NAD+-induced cell death (NICD) may impact the survival of other cell populations co-expressing P2X7 and of one of the ARTC2 isoforms (ARTC2.1, ARTC2.2). NICD of brain-resident, non-T cell populations has only been rudimentarily investigated. In this study, we evaluated the susceptibility of two glia cell populations, astrocytes and microglia, towards NICD. We found that astrocytes and microglia strongly upregulate cell surface levels of ARTC2.1 and ADP-ribosylation of cell surface proteins in response to treatment with lipopolysaccharide (LPS) and the mitogen-activated protein kinase kinase (MEK) 1 and 2 inhibitor U0126, but do not respond to extracellular NAD+ with P2X7 activation and induction of cell death. Furthermore, we found that astrocytes and microglia preferentially express the ADP-ribosylation-insensitive P2X7a splice variant, likely accounting for the resistance of these cells to NICD.

Abstract: Fetal hemoglobin (HbF) is a strong modifier of sickle cell disease (SCD) severity and is associated with 3 common genetic loci. Quantifying the genetic effects of the 3 loci would specifically address the benefits of HbF increases in patients. Here, we have applied statistical methods using the most representative variants: rs1427407 and rs6545816 in BCL11A, rs66650371 (3-bp deletion) and rs9376090 in HMIP-2A, rs9494142 and rs9494145 in HMIP-2B, and rs7482144 (Xmn1-HBG2 in the β-globin locus) to create g(HbF), a genetic quantitative variable for HbF in SCD. Only patients aged ≥5 years with complete genotype and HbF data were studied. Five hundred eighty-one patients with hemoglobin SS (HbSS) or HbSβ0 thalassemia formed the “discovery” cohort. Multiple linear regression modeling rationalized the 7 variants down to 4 markers (rs6545816, rs1427407, rs66650371, and rs7482144) each independently contributing HbF-boosting alleles, together accounting for 21.8% of HbF variability (r2) in the HbSS or HbSβ0 patients. The model was replicated with consistent r2 in 2 different cohorts: 27.5% in HbSC patients (N = 186) and 23% in 994 Tanzanian HbSS patients. g(HbF), our 4-variant model, provides a robust approach to account for the genetic component of HbF in SCD and is of potential utility in sickle genetic and clinical studies.

This study aimed to characterize different natural killer (NK) cell phenotypes on bone marrow and peripheral blood cells from acute myeloid leukemia (AML) patients and healthy donors (HDs). Our data show that CD56dimCD16− and CD56brightCD16− NK cells represent the predominant NK cell subpopulations in AML, while the CD56dimCD16+ NK cells are significantly reduced compared to HDs. Moreover, TIGIT+ and PVRIG+ cells cluster on the CD56dimCD16+ subset whereas CD39+ and CD38+ cells do so on CD56brightCD16− NK cells in AML. Furthermore, functional effects of (co-)blockade of TIGIT and CD39 or A2AR on NK cell functionality were analyzed. These experiments revealed that the single blockade of the TIGIT receptor results in an increased NK-92 cell-mediated killing of AML cells in vitro. Combined targeting of CD39 or A2AR significantly augments the anti-TIGIT-mediated lysis of AML cells. Our data indicate that distinct NK cell subsets in AML exhibit different immunosuppressive patterns (via the TIGIT/PVRIG receptors and the purinergic pathway). In summary, we conclude that TIGIT, CD39, and A2AR constitute relevant inhibitory checkpoints of NK cells in AML patients. A combinatorial blockade synergistically strengthens NK-92 cell-mediated cytotoxicity. As inhibitors of TIGIT, CD39, and A2AR are clinically available, studies on their combined use could be conducted in the near future.

Abstract Mammalian ecto-ADP-ribosyltransferases (ecto-ARTs or also ARTCs) catalyze the ADP-ribosylation of cell surface proteins using extracellular nicotinamide adenine dinucleotide (NAD+) as substrate. By this post-translational protein modification, ecto-ARTs modulate the function of various target proteins. A functional role of ARTC2 has been demonstrated for peripheral immune cells such as T cells and macrophages. Yet, little is known about the role of ecto-ARTs in the central nervous system and on microglia. Here, we identified ARTC2.1 as the major ecto-ART expressed on murine microglia. ARTC2.1 expression was strongly upregulated on microglia upon co-stimulation with LPS and an ERK1/2 inhibitor or upon IFNβ stimulation. We identified several target proteins modified by ARTC2.1 on microglia with a recently developed mass spectrometry approach, including two receptors for immunoglobulin G (IgG), FcγR1 and FcγR2B. Both proteins were verified as targets of ARTC2.1 in vitro using a radiolabeling assay with 32P-NAD+ as substrate. Moreover, ADP-ribosylation of both targets strongly inhibited their capacity to bind IgG. In concordance, ARTC2.1 induction in WT microglia and subsequent cell surface ADP-ribosylation significantly reduced the phagocytosis of IgG-coated latex beads, which was unimpaired in NAD+/DTT treated microglia from ARTC2.1−/− mice. Hence, induction of ARTC2.1 expression under inflammatory conditions, and subsequent ADP-ribosylation of cell surface target proteins could represent a hitherto unnoticed mechanism to regulate the immune response of murine microglia.

Fetal hemoglobin (HbF) and peripheral hemoglobin oxygen saturation (SpO2) both predict clinical severity in sickle cell disease (SCD), while reticulocytosis is associated with vasculopathy, but there are few data on mechanisms. HbF, SpO2 and routine clinical and laboratory measures were available in a Tanzanian cohort of 1175 SCD individuals aged ≥ 5 years and the association with SpO2 (as response variable transformed to a Poisson distribution) was assessed by negative binomial model with age and sex as covariates. Increase in HbF was associated with increased SpO2 (rate ratio, RR = 1.19; 95% confidence intervals [CI] 1.04, 1.37 per natural log unit of HbF; p = 0.0004). In univariable analysis, SpO2 was inversely associated with age, reticulocyte count, and log (total bilirubin) and directly with pulse, SBP, hemoglobin, and log(HbF). In multivariable regression log(HbF) (RR 1.191; 95%CI 1.04, 1.37; p = 0.013), pulse (RR 1.01; 95%CI 1.00, 1.01; p = 0.026), SBP (RR 1.008; 95%CI 1.00, 1.02; p = 0.014), and hemoglobin (1.120; 95%CI 1.05, 1.19; p = 0.001) were positively and independently associated with SpO2 while reticulocyte count (RR 0.985; 95%CI 0.97, 0.99; p = 0.019) was independently inversely associated with SpO2. In SCD, improving SpO2, in part through cardiovascular compensation and associated with reduced reticulocytosis, may be a mechanism by which HbF reduces disease severity.

The P2X4 channel is involved in different physiological and pathological conditions and functions in the nervous system. Despite the existence of several mouse models for which the expression of the gene was manipulated, there is still little information on the expression of the protein at the cellular level. In particular, supposedly specific available antibodies have often proved to recognize unrelated proteins in P2X4-deficient mice. Here, we used an in vivo DNA vaccine approach to generate a series of monoclonal antibodies and nanobodies specific for human, mouse, and rat P2X4 channels. We further characterized these antibodies and show that they solely recognize the native form of the proteins both in biochemical and cytometric applications. Some of these antibodies prove to specifically recognize P2X4 channels by immunostaining in brain or sensory ganglia slices, as well as at the cellular and subcellular levels. Due to their clonality, these different antibodies should represent versatile tools for further characterizing the cellular functions of P2X4 in the nervous system as well as at the periphery.

Resistive switching in metal oxides is related to the migration of donor defects. Here Baeumer et al. use in operandoX-ray spectromicroscopy to quantify the doping locally and show that small local variations in the donor concentration result in large variations in the device resistance.

CD38 is overexpressed by multiple myeloma cells and has emerged as a target for therapeutic antibodies. Nanobodies are soluble single domain antibody fragments derived from the VHH variable domain of heavy chain antibodies naturally occurring in camelids. We previously identified distinct llama nanobodies that recognize three non-overlapping epitopes of the extracellular domain of CD38. Here, we fused these VHH domains to the hinge, CH2, and CH3 domains of human IgG1, yielding highly soluble chimeric llama/human heavy chain antibodies (hcAbs). We analyzed the capacity of these hcAbs to mediate complement-dependent cytotoxicity (CDC) to CD38-expressing human multiple myeloma and Burkitt lymphoma cell lines. Combinations of two hcAbs that recognize distinct, non-overlapping epitopes of CD38 mediated potent CDC, in contrast to the hcAb monotherapy with only weak CDC capacity. Similarly, combining daratumumab with a hcAb that recognizes a non-overlapping epitope resulted in dramatically enhanced CDC. Further, introducing the E345R HexaBody mutation into the CH3 domain strongly enhanced the CDC potency of hcAbs to CD38-expressing cells. Exploiting their high solubility, we genetically fused two distinct nanobodies into heteromeric dimers via a flexible peptide linker and then fused these nanobody dimers to the hinge, CH2 and CH3 domains of human IgG1, yielding highly soluble, biparatopic hcAbs. These biparatopic hcAbs elicited CDC toward CD38-expressing myeloma cells more effectively than daratumumab. Our results underscore the advantage of nanobodies vs. pairs of VH and VL domains for constructing bispecific antibodies. Moreover, the CD38-specific biparatopic heavy chain antibodies described here represent potential new powerful therapeutics for treatment of multiple myeloma.

Summary: The clostridium-like ecto-ADP-ribosyltransferase ARTC1 is expressed in a highly restricted manner in skeletal muscle and heart tissue. Although ARTC1 is well studied, the identification of ARTC1 targets in vivo and subsequent characterization of ARTC1-regulated cellular processes on the proteome level have been challenging and only a few ARTC1-ADP-ribosylated targets are known. Applying our recently developed mass spectrometry-based workflow to C2C12 myotubes and to skeletal muscle and heart tissues from wild-type mice, we identify hundreds of ARTC1-ADP-ribosylated proteins whose modifications are absent in the ADP-ribosylome of ARTC1-deficient mice. These proteins are ADP-ribosylated on arginine residues and mainly located on the cell surface or in the extracellular space. They are associated with signal transduction, transmembrane transport, and muscle function. Validation of hemopexin (HPX) as a ARTC1-target protein confirmed the functional importance of ARTC1-mediated extracellular arginine ADP-ribosylation at the systems level. : Leutert et al. identify the ADP-ribosylomes of skeletal muscle and heart tissue and show that they comprise mainly arginine modification sites that are modified by the ADP-ribosyltransferase ARTC1. The functional importance of ARTC1 is documented by impaired muscle performance in ARTC1-deficient mice and tuning of heme binding by hemopexin ADP-ribosylation in vitro. Keywords: ADP-ribosylation, proteomics, mass spectrometry, post-translational modification, ARTC1, arginine modification, muscle, heart, C2C12, hemopexin

Silent cerebral infarction is the most common neurological abnormality in children with sickle cell anemia, affecting 30-40% of 14 year olds. There are no known biomarkers to identify children with silent cerebral infarcts, and the pathological basis is also unknown. We used an unbiased proteomic discovery approach to identify plasma proteins differing in concentration between children with and without silent cerebral infarcts. Clinical parameters and plasma samples were analysed from 51 children (mean age 11.8 years, range 6-18) with sickle cell anemia (HbSS). A total of 19 children had silent cerebral infarcts and 32 normal MRI; the children with silent infarcts had lower HbF levels (8.6 vs. 16.1%, P=0.049) and higher systolic blood pressures (115 vs. 108.6, P=0.027). Plasma proteomic analysis showed 13 proteins increased more than 1.3 fold in the SCI patients, including proteins involved in hypercoagulability (α2-antiplasmin, fibrinogen−γ chain, thrombospondin-4), inflammation (α2-macroglobulin, complement C1s and C3), and atherosclerosis (apolipoprotein B-100). Higher levels of gelsolin and retinol-binding protein 4 were also found in the population with silent infarcts, both of which have been linked to stroke. We investigated the genetic basis of these differences by studying 359 adults with sickle cell disease (199 with silent cerebral infarcts, 160 normal MRIs), who had previously undergone a genome-wide genotyping array. None of the genes coding for the differentially expressed proteins were significantly associated with silent infarction. Our study suggests that silent cerebral infarcts in sickle cell anemia may be associated with higher systolic blood pressure, lower HbF levels, hypercoagulability, inflammation and atherosclerotic lipoproteins.

Adenosine triphosphate (ATP) and nicotinamide adenine dinucleotide (NAD+) are released as danger signals from cells during infection and sterile inflammation. In the extracellular compartment ATP is converted by CD39, CD73, and other ecto-enzymes into metabolites that modulate the activity of T cells and macrophages. While ATP mediates pro-inflammatory signals via P2X7 and other P2 receptors, adenosine triggers anti-inflammatory signaling via the adenosine 2a receptor (Adora2a) and other P1 receptors. The latter also plays a role in maintaining an immunosuppressive tumor microenvironment. NAD+ is converted by CD38, CD203 and other ecto-enzymes to the Ca2+ mobilizing messengers cyclic ADP-ribose and ADP-ribose, and to adenosine. Recent findings on the roles of CD38, CD39, CD73, CD203, P2X7, and Adora2a in inflammation and immunity underscore the potential of these proteins as drug targets. However, available small molecule inhibitors often lack specificity and mediate unwanted off-target toxicity. Nanobodies – single domain antibodies derived from heavy chain antibodies that naturally occur in camelids – display a propensity to bind functional epitopes not accessible to conventional antibodies. Like conventional antibodies, nanobodies and nanobody-based biologics are highly specific and have well-understood, tunable in vivo pharmacodynamics with little if any toxicity. Nanobodies thus represent attractive alternatives to small molecule inhibitors for modulating purinergic signaling in inflammation and immunity. Here we review recent progress made in developing nanobodies against key targets of purinergic signaling.

Nanobodies (Nbs) are soluble, versatile, single-domain binding modules derived from the VHH variable domain of heavy-chain antibodies naturally occurring in camelids. Nbs hold huge promise as novel therapeutic biologics. Membrane proteins are among the most interesting targets for therapeutic Nbs because they are accessible to systemically injected biologics. In order to be effective, therapeutic Nbs must recognize their target membrane protein in native conformation. However, raising Nbs against membrane proteins in native conformation can pose a formidable challenge since membrane proteins typically contain one or more hydrophobic transmembrane regions and, therefore, are difficult to purify in native conformation. Here, we describe a highly efficient genetic immunization strategy that circumvents these difficulties by driving expression of the target membrane protein in native conformation by cells of the immunized camelid. The strategy encompasses ballistic transfection of skin cells with cDNA expression plasmids encoding one or more orthologs of the membrane protein of interest and, optionally, other costimulatory proteins. The plasmid is coated onto 1 µm gold particles that are then injected into the shaved and depilated skin of the camelid. A gene gun delivers a helium pulse that accelerates the DNA-coated particles to a velocity sufficient to penetrate through multiple layers of cells in the skin. This results in the exposure of the extracellular domains of the membrane protein on the cell surface of transfected cells. Repeated immunization drives somatic hypermutation and affinity maturation of target-specific heavy-chain antibodies. The VHH/Nb coding region is PCR-amplified from B cells obtained from peripheral blood or a lymph node biopsy. Specific Nbs are selected by phage display or by screening of Nb-based heavy-chain antibodies expressed as secretory proteins in transfected HEK cells. Using this strategy, we have successfully generated agonistic and antagonistic Nbs against several cell surface ecto-enzymes and ligand-gated ion channels.

Genetic variants at three quantitative trait loci (QTL) for fetal haemoglobin (HbF), BCL11A, HBS1L-MYB and the β-globin gene cluster, have attracted interest as potential targets of therapeutic strategies for HbF reactivation in sickle cell anaemia (SCA). We carried out the first systematic evaluation of critical single nucleotide polymorphisms at these disease modifier loci in Nigerian patients with SCA. Common variants for BCL11A and HBS1L-MYB were strongly associated with HbF levels. At both loci, secondary association signals were detected, illustrating the mapping resolution attainable in this population. For BCL11A, the two independent sites of association were represented by rs1427407 (primary site, p = 7.0 x 10(-10)) and rs6545816 (secondary site, conditioned on rs1427407: p = 0.02) and for HBS1L-MYB by rs9402686 (HMIP-2B, p = 1.23 x 10(-4)) and rs66650371 (HMIP-2A, p = 0.002). Haplotype analysis revealed similarities in the genetic architecture of BCL11A and HBS1L-MYB in Nigerian patients. Variants at both loci also alleviated anaemia. The variant allele for the γ globin gene promoter polymorphism XmnI-HBG2 was too infrequent in our patients to be evaluated in this relatively small study. Studying the large and diverse SCA patient populations in African countries such as Nigeria will be key for a clearer understanding of how these loci work and for the discovery of new disease modifier genes.

Introducción. La hemoglobina fetal es un importante factor modulador de la gravedad de la anemia falciforme, cuya expresión está muy condicionada por el factor genético. Los loci asociados con el incremento de la hemoglobina fetal pueden presentar frecuencias alélicas específicas para cada población. Objetivo. Investigar la presencia y el efecto de las variantes genéticas rs11886868, rs9399137, rs4895441 y rs7482144 asociadas con la persistencia de hemoglobina fetal, en 60 pacientes colombianos con anemia falciforme. Materiales y métodos. Se hizo la genotipificación de los polimorfismos de nucleótido simple (Single Nucleotide Polymorphisms, SNP) mediante la técnica de polimorfismos de longitud de fragmentos de restricción (Restriction Fragment Length Polymorphisms, RFLP) y el procedimiento TaqMan. La hemoglobina fetal (HbF) se cuantificó utilizando la técnica de desnaturalización alcalina de la oxihemoglobina. Las frecuencias genotípicas se compararon con las reportadas en poblaciones de referencia global. Resultados. Se observaron variantes genéticas ya reportadas para aumento de HbF en los cuatro SNP. La asociación genética entre los SNP y el incremento de la HbF no alcanzó significancia estadística. La frecuencia de estos alelos reflejó la siguiente composición específica en esta muestra de pacientes colombianos: una gran prevalencia de rs7482144-‘A’, lo que indica que el origen de la mutación para la anemia falciforme es África occidental, y una gran frecuencia de rs4895441-‘G’ y rs11886868-‘C’, lo que denota la influencia significativa del origen genético amerindio. Conclusión. Los resultados evidenciaron que la población con anemia falciforme de Colombia no tiene un único origen genético, sino que existen dos (africano y amerindio). Esta situación genética única ofrece la oportunidad de llevar a cabo un estudio más amplio de estos loci a nivel molecular. Se espera que el estudio de pacientes colombianos permita una visión diferente del efecto de los loci modificadores en esta enfermedad.

Sickle cell disease is an increasing global health burden. This inherited disease is characterized by a remarkable phenotypic heterogeneity, which can only partly be explained by genetic factors. Environmental factors are likely to play an important role but studies of their impact on disease severity are limited and their results are often inconsistent. This study investigated associations between a range of environmental factors and hospital admissions of young patients with sickle cell disease in London and in Paris between 2008 and 2012. Specific analyses were conducted for subgroups of patients with different genotypes and for the main reasons for admissions. Generalized additive models and distributed lag non-linear models were used to assess the magnitude of the associations and to calculate relative risks. Some environmental factors significantly influence the numbers of hospital admissions of children with sickle cell disease, although the associations identified are complicated. Our study suggests that meteorological factors are more likely to be associated with hospital admissions for sickle cell disease than air pollutants. It confirms previous reports of risks associated with wind speed (risk ratio: 1.06/standard deviation; 95% confidence interval: 1.00–1.12) and also with rainfall (1.06/standard deviation; 95% confidence interval: 1.01–1.12). Maximum atmospheric pressure was found to be a protective factor (0.93/standard deviation; 95% confidence interval: 0.88–0.99). Weak or no associations were found with temperature. Divergent associations were identified for different genotypes or reasons for admissions, which could partly explain the lack of consistency in earlier studies. Advice to patients with sickle cell disease usually includes avoiding a range of environmental conditions that are believed to trigger acute complications, including extreme temperatures and high altitudes. Scientific evidence to support such advice is limited and sometimes confusing. This study shows that environmental factors do explain some of the variations in rates of admission to hospital with acute symptoms in sickle cell disease, but the associations are complex, and likely to be specific to different environments and the individual’s exposure to them. Furthermore, this study highlights the need for prospective studies with large numbers of patients and standardized protocols across Europe.