Memory Cells Research Articles

Teplizumab induces persistent changes in the antigen-specific repertoire in individuals at risk for type 1 diabetes.

BACKGROUNDTeplizumab, a non-FcR-binding anti-CD3 mAb, is approved to delay progression of type 1 diabetes (T1D) in at-risk patients. Previous investigations described the immediate effects of the 14-day treatment, but longer-term effects of the drug remain unknown.METHODSWith an extended analysis of study participants, we found that 36% were undiagnosed or remained free of clinical diabetes after 5 years, suggesting operational tolerance. Using single-cell RNA sequencing, we compared the phenotypes, transcriptome, and repertoire of peripheral blood CD8+ T cells including autoreactive T cells from study participants before and after teplizumab and features of responders and non-responders.RESULTSAt 3 months, there were transcriptional signatures of cell activation in CD4+ and CD8+ T cells including signaling that was reversed at 18 months. At that time, there was reduced expression of genes in T cell receptor and activation pathways in clinical responders. In CD8+ T cells, we found increased expression of genes associated with exhaustion and immune regulation with teplizumab treatment. These transcriptional features were further confirmed in an independent cohort. Pseudotime analysis showed differentiation of CD8+ exhausted and memory cells with teplizumab treatment. IL7R expression was reduced, and patients with lower expression of CD127 had longer diabetes-free intervals. In addition, the frequency of autoantigen-reactive CD8+ T cells, which expanded in the placebo group over 18 months, did not increase in the teplizumab group.CONCLUSIONThese findings indicate that teplizumab promotes operational tolerance in T1D, involving activation followed by exhaustion and regulation, and prevents expansion of autoreactive T cells.TRIAL REGISTRATIONClinicalTrials.gov NCT01030861.FUNDINGNational Institute of Diabetes and Digestive and Kidney Diseases/NIH, Juvenile Diabetes Research Foundation.

Genetic modification of primary human B cells to model the process of B cell development in germinal centers

The main stages of maturation of antigen-specific B cells occur in the germinal centers of the lymph nodes. During the process of differentiation, a decision is made on which path the B cells will take to develop further. They will either turn into short-lived plasmablasts or memory B cells or plasma cells. The relationship between these processes is very important for the development of a productive humoral immune response. The goal of the work was to create a system that is capable of simulating ex vivo processes occurring in germinal centers. We used primary B cells from human peripheral blood as starting material. B lymphocytes were stimulated in vitro using feeder cells carrying CD40L molecules and recombinant IL-21. Upon IL-21/CD40L stimulation, B lymphocytes changed their morphology, surface phenotype, and functional activity. After active expansion for 10 days, further cell growth stopped, and after some time they died. To generate stably proliferating B cells, we used lentiviral transduction of IL-21/CD40L stimulated IgM+ B cells. For this purpose, lentivirus preparations were obtained that carried a cassette consisting of the BCL6 and BCL2L1 genes, separated by a sequence encoding the self-cutting peptide P2A, as well as a GFP reporter gene separated from the target genes by an IRES element. The cassette used ensured the synthesis of the Bcl-6 transcription factor and the Bcl-XL protein in target cells. The Bcl-6 repressor prevented B cells from undergoing terminal differentiation and becoming plasma cells, and the Bcl-XL protein had an anti-apoptotic effect. Transduced B cells proliferated for more than a month and maintained a plasmablast phenotype. Forty-two days after the start of stimulation, transduced B cells remained GFP-positive, coexpressed CD27 and CD38 antigens, carried surface CD20 and IgM, intracellular Bcl-6, Bcl-XL and IgM, retained IgM secretion, but remained negative for surface and intracellular IgG. The proven stimulation system will allow us to simulate key aspects of B cell development in germinal centers to study the formation of B cell memory, which will ultimately facilitate the development of effective vaccines.

The Immune Memory Response of In Vitro-Polarised Th1, Th2, and Th17 Cells in the Face of Ovalbumin-Transgenic Leishmania major in a Mouse Model.

Th1 and Th2 cytokines determine the outcome of Leishmania major infection and immune protection depends mainly on memory T cells induced during vaccination. This largely hinges on the nature and type of memory T cells produced. In this study, transgenic Leishmania major strains expressing membrane-associated ovalbumin (mOVA) and soluble ovalbumin (sOVA) were used as a model to study whether fully differentiated Th1/Th2 and Th17 cells can recall immune memory and tolerate pathogen manipulation. Naïve OT-II T cells were polarised in vitro into Th1/Th2 cells, and these cells were transferred adoptively into recipient mice. Following the transferral of the memory cells, the recipient mice were challenged with OVA transgenic Leishmania major and a wild-type parasite was used a control. The in vitro-polarised T helper cells continued to produce the same cytokine signatures after being challenged by both forms of OVA-expressing Leishmania major parasites in vivo. This suggests that antigen-experienced cells remain the same or unaltered in the face of OVA-transgenic Leishmania major. Such ability of these antigen-experienced cells to remain resilient to manipulation by the parasite signifies that vaccines might be able to produce immune memory responses and defend against parasitic immune manipulation in order to protect the host from infection.

Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models

BackgroundVaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend against targeted diseases. Clinical trials evaluate vaccine performance, including dosage, administration routes, and potential side effects. ClinicalTrials.gov is a valuable repository of clinical trial information, but the vaccine data in them lacks standardization, leading to challenges in automatic concept mapping, vaccine-related knowledge development, evidence-based decision-making, and vaccine surveillance.ResultsIn this study, we developed a cascaded framework that capitalized on multiple domain knowledge sources, including clinical trials, the Unified Medical Language System (UMLS), and the Vaccine Ontology (VO), to enhance the performance of domain-specific language models for automated mapping of VO from clinical trials. The Vaccine Ontology (VO) is a community-based ontology that was developed to promote vaccine data standardization, integration, and computer-assisted reasoning. Our methodology involved extracting and annotating data from various sources. We then performed pre-training on the PubMedBERT model, leading to the development of CTPubMedBERT. Subsequently, we enhanced CTPubMedBERT by incorporating SAPBERT, which was pretrained using the UMLS, resulting in CTPubMedBERT + SAPBERT. Further refinement was accomplished through fine-tuning using the Vaccine Ontology corpus and vaccine data from clinical trials, yielding the CTPubMedBERT + SAPBERT + VO model. Finally, we utilized a collection of pre-trained models, along with the weighted rule-based ensemble approach, to normalize the vaccine corpus and improve the accuracy of the process. The ranking process in concept normalization involves prioritizing and ordering potential concepts to identify the most suitable match for a given context. We conducted a ranking of the Top 10 concepts, and our experimental results demonstrate that our proposed cascaded framework consistently outperformed existing effective baselines on vaccine mapping, achieving 71.8% on top 1 candidate’s accuracy and 90.0% on top 10 candidate’s accuracy.ConclusionThis study provides a detailed insight into a cascaded framework of fine-tuned domain-specific language models improving mapping of VO from clinical trials. By effectively leveraging domain-specific information and applying weighted rule-based ensembles of different pre-trained BERT models, our framework can significantly enhance the mapping of VO from clinical trials.

Возрастная динамика субпопуляций Т-лимфоцитов у пациентов с синдромом делеции 22q11.2 (синдромом Ди Джорджи)

Patients with the 22q11.2 deletion syndrome (DiGeorge syndrome, DDS) suffer from T-cell lymphopenia, changes in function and subpopulation of T-lymphocytes. The bibliographical data conflicts on the characteristics of T-lymphocytes in patients with DDS and their changes during physiological maturation. The purpose of this research was to follow-up patients with emphasis on the dynamics of changes in T-lymphocyte subpopulations with age. Methods used: 117 patients observed during 2013-2023 who were administered at the Allergology and Immunology Department with the G.N. Speransky City Children’s Hospital No. 9 (Moscow, Russia) with a diagnosis of DDS and who had undergone blood sampling to assess T-lymphocyte subpopulations using flow cytometry. All patients (0 to 18 y/o) were divided into 4 age groups: 0 to 2 y/o, 2 to 5 y/o, 5 to 10 y/o and 10 to 18 y/o. In parallel, the blood samples of 185 apparently healthy children of the corresponding age were examined. Results: a decrease in CD3 T-lymphocytes, CD4 T-helper cells, CD8 T-cytotoxic lymphocytes, CD4 early thymic emigrants and CD4 naive T-lymphocytes was found in all age groups (p<0.05). CD8+ naive T-lymphocytes and CD8+ early thymic emigrants were reduced in all age groups, but in the 2 to 5 y/o age group their values were close to normal (p=0.072 and p=0.220, respectively). CD4+ central memory cells were elevated in all age groups (p<0.001), while CD8+ central memory cells, CD4+ and CD8+ effector memory cells differed in that they had normal values in the 2 to 5 y/o age group (p=0.229, p=0.457 and p=0.140, respectively). CD4+ TEMRA were significantly increased in the 0 to 2 y/o age group (p=0.002), and in older age groups they tended to normal values. CD8+ TEMRA did not differ from the control group and did not have age-related dynamics. The T-helper subpopulations were characterized by a significant increase in the percentage of T-helper type 1, T-helper 17, T-helper 17.1 and a decrease in T-helper type 2 compared to the population of healthy blood sample donors (p=0.001), except for patients from the 2 to 5 y/o age group. T-regulatory cells in absolute amount were reduced in all age groups (p<0.001), while their relative number corresponded to the norm in the 0 to 2 y/o age group (p=0.811) and decreased slightly in patients in older age groups, especially in the 2 to 5 y/o age group (p=0.030). Conclusion: the pathology of thymus development in patients with DDS leads to impaired maturation of T-lymphocytes, leading to an increase in the number of mature forms of T-lymphocytes, shifts towards the development of T-helper 1 and T-helper 17, and a decrease in T-regulatory cells. Disturbances in T-lymphocytes can cause changes (dysregulation) in subpopulations of B-cells. All these processes may underlie the progression of autoimmune and infectious complications in such patients that are increasing with aging.

Ultra-Low-Power Hybrid Synaptic Memristor via Simultaneous-Controlled Mechanism of Cations and Anions for Hyper-Scale Synaptic Cores

Recently, memristive devices such as phase change random access memory (PCRAM), resistive random access memory (ReRAM), and ferroelectric random access memory (FeRAM) have been actively researched to implement hyper-scale synaptic cores of various ANNs, i.e., deep neural networks (DNNs), spiking neural networks (SNNs), convolutional neural networks (CNNs), and binarized neural networks (BNNs). In particular, ReRAM is currently being highlighted as an artificial synaptic device because of its multilevel capability (> 11 bits)1, high switching speed (< 100 ps)2, high endurance (> 1012 cycles)3, high scalability, and complementary metal-oxide-semiconductor (CMOS) compatibility4. ReRAM is generally divided into two types: valence change memory (VCM) cells having oxygen vacancy filaments and electrochemical metallization (ECM) cells having conductive metal filaments. VCM cells have great retention but exhibit high switching current (~ 100 μA). In contrast, ECM cells exhibit relatively lower switching current (~10 uA) than VCM cells but have poor retention due to diffusion phenomena at high external temperatures5. Due to their high switching current and poor reliability, VCM and ECM cells have limitations in their application as synaptic devices in next-generation neuromorphic systems for energy consumption similar to that of the human brain (~20 W). In this study, for the first time, we developed a Ru-based ultra-low-power (< 1μA) hybrid synaptic memristor having a simultaneous-controlled mechanism of Ru cations and oxygen anions in a resistive switching layer. To elucidate the simultaneous-controlled mechanism of Ru cations and oxygen anions, we fabricated the VCM, ECM, and Ru-based hybrid memristor and performed x-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis depending on the resistance states (i.e., pristine, set, and reset). In addition, the mobility of mobile species in VCM, ECM, and Ru-based hybrid memristors was calculated indirectly via electrical properties (switching speed, operating voltage) and ToF-SIMS depth profiles, revealing the mechanism by which Ru-based hybrid memristor has low switching currents (< 1μA). Finally, the power consumption of active synaptic cores in the training and inference process of the designed DNN was evaluated for VCM, ECM, and Ru-based hybrid memristor. The simultaneous-controlled mechanism of Ru cations and oxygen anions of the Ru-based hybrid memristor and its application to DNN will be presented in detail. Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00260527) and Institute of Information & communications Technology Planning & Evaluation (IITP) under the artificial intelligence semiconductor support program to nurture the best talents (IITP-(2023)-RS-2023-00253914) grant funded by the Korea government(MSIT)". References Rao, M. et al. Thousands of conductance levels in memristors integrated on CMOS. Nature 615, 823–829 (2023).Yu, S., Wu, Y., Jeyasingh, R., Kuzum, D. & Wong, H. S. P. An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation. IEEE Trans. Electron Devices 58, 2729–2737 (2011).Lee, H. Y. et al. Evidence and solution of over-RESET problem for HfOX based resistive memory with sub-ns switching speed and high endurance. Tech. Dig. - Int. Electron Devices Meet. IEDM 7–10 (2010) doi:10.1109/IEDM.2010.5703395.Wong, H. S. P. et al. Metal-oxide RRAM. Proc. IEEE 100, 1951–1970 (2012).Yoon, J. H. et al. A Low-Current and Analog Memristor with Ru as Mobile Species. Adv. Mater. 32, 1–9 (2020). Figure 1

Senolytic intervention improves cognition, metabolism, and adiposity in female APPNL-F/NL-F mice.

Senescent cells accumulate throughout the body and brain contributing to unhealthy aging and Alzheimer's disease (AD). The APPNL-F/NL-F amyloidogenic AD mouse model exhibits increased markers of senescent cells and the senescence-associated secretory phenotype (SASP) in visceral white adipose tissue and the hippocampus before plaque accumulation and cognitive decline. We hypothesized that senolytic intervention would alleviate cellular senescence thereby improving spatial memory in APPNL-F/NL-F mice. Thus, 4-month-old male and female APPNL-F/NL-F mice were treated monthly with vehicle, 5mg/kg dasatinib + 50mg/kg quercetin, or 100mg/kg fisetin. Blood glucose levels, energy metabolism, spatial memory, amyloid burden, and senescent cell markers were assayed. Dasatinib + quercetin treatment in female APPNL-F/NL-F mice increased oxygen consumption and energy expenditure resulting in decreased body mass. White adipose tissue mass was decreased along with senescence markers, SASP, blood glucose, and plasma insulin and triglycerides. Hippocampal senescence markers and SASP were reduced along with soluble and insoluble amyloid-β (Aβ)42 and senescence-associated-β-gal activity leading to improved spatial memory. Fisetin had negligible effects on these measures in female APPNL-F/NL-F mice while neither senolytic intervention altered these parameters in the male mice. Considering women have a greater risk of dementia, identifying senotherapeutics appropriate for sex and disease stage is necessary for personalized medicine.

Atypical and non-classical CD45RBlo memory B cells are the majority of circulating SARS-CoV-2 specific B cells following mRNA vaccination or COVID-19

Resting memory B cells can be divided into classical or atypical groups, but the heterogenous marker expression on activated memory B cells makes similar classification difficult. Here, by longitudinal analysis of mass cytometry and CITE-seq data from cohorts with COVID-19, bacterial sepsis, or BNT162b2 mRNA vaccine, we observe that resting B cell memory consist of classical CD45RB+ memory and CD45RBlo memory, of which the latter contains of two distinct groups of CD11c+ atypical and CD23+ non-classical memory cells. CD45RB levels remain stable in these cells after activation, thereby enabling the tracking of activated B cells and plasmablasts derived from either CD45RB+ or CD45RBlo memory B cells. Moreover, in both COVID-19 patients and mRNA vaccination, CD45RBlo B cells formed the majority of SARS-CoV2 specific memory B cells and correlated with serum antibodies, while CD45RB+ memory are activated by bacterial sepsis. Our results thus identify that stably expressed CD45RB levels can be exploited to trace resting memory B cells and their activated progeny, and suggest that atypical and non-classical CD45RBlo memory B cells contribute to SARS-CoV-2 infection and vaccination.

A Mechanism of Resistance Switching in CNT Based Memory Devices

Carbon nanotubes (CNTs) show promise for high energy efficiency electronic devices due to their high electrical conductivity. One possible application is in the fabrication of resistance-change computer memory, where the application of an external electrical bias can use a CNT layer as the switching element in a RAM cell. Memory cells of this type have been extensively demonstrated, where the electrical resistance of a switching layer of CNTs can be reversibly controlled by the application of external bias [1].To better understand these devices, we have developed a nanoscale model of their electrical switching. Towards this end, first-principles calculations of the electrical conductivity of CNT-CNT junctions were performed using the Density Functional Tight Binding (DFTB) in combination with the Non-Equilibrium Greens functions (NEGF) approach, enabling an improved understanding of the tunnelling of electrons across a range of CNT junctions [2]. These results demonstrate that the conductivity of CNT contacts depends on the overlap area between nanotubes and exponentially on the distances between the carbon atoms of the interacting CNTs. Secondly, we employed coarse-grained molecular dynamics [3,4] to produce nanoscale dense CNT film models like those used in the devices. We devise a set of metrics for characterising the structural properties of CNT films, and apply them to a set of model films designed to mimic those used in microelectronics devices. In order to understand how the geometrical properties of CNTs affect the film structure, we analyse films with different CNT chirality and length distributions. Unlike previous studies that focused on relatively low-density systems below ∼0.4 g/cm3, we also consider films with density of ∼0.6 g/cm3, as employed in experimentally fabricated CNT-based NRAM devices. By adding amorphous carbon to the film models, in varying amounts, we are then able to assess its effects. Finally, these two elements were combined to produce electrical simulations of the conductivity of the CNT films connected to TiN electrodes. These electrodes are shown to be partially oxidized during the device fabrication. The electrical conductivity in a device is characterized by formation of conduction paths formed by CNTs between the electrodes and connected via the CNT junctions. The conductivity is modulated by charging of CNTs and amorphous carbon present in the film.Using these simulations, we propose a resistance switching mechanism in TiN/CNT/TiN devices based on the physical movement of CNTs. During the initial operation of the device, oxygen is released from the oxidized bottom electrode and this readily reacts with individual CNTs to form charge trapping sites. Once these sites have become charged, they enable controllable movement of CNTs at the bottom electrode under the application of electric field. By reversibly connecting and disconnecting such CNTs from the bottom electrode, the electrical conductivity through the CNT film as a whole can be controlled.

(Invited) Oxide Semiconductor Gain Cell Memory

The energy and delay consumed by the off-chip memory (DRAM) and memory-to-logic chip data movement becomes the bottleneck (known as the memory wall) for the computing systems nowadays, especially for abundant-data computing and neural network accelerators. Larger on-chip memory capacity with high bandwidth can be a solution, yet it is difficult to achieve using SRAM and DRAM. Oxide semiconductor FET (OSFET)-based gain cell memory on the logic platform provides higher density than SRAM due to 3D stacking and is an attractive complement to off-chip DRAM. OSFET with extremely low leakage is used as the write transistor for long retention time, while the read transistor can either adopt OSFET for multiple-layer stacking (OS-OS gain cell) or Si FET for higher read speed (Hybrid gain cell). Designing OSFET gain cell is more than simply choosing materials/device designs that have the lowest off-state leakage current for the longest retention time. Atomic Layer Deposition (ALD) Indium Tin Oxide (ITO) FET is chosen to balance retention time with memory bandwidth. With material, process, and device co-design, the ITO films deposited by ALD with TMIn precursor, 9:1 In:Sn cycle ratio, and 2nm thickness exhibited optimized characteristics for OSFET-based gain cell. The experimentally optimized device exhibits low off-current 2×10-18 A/µm, high on-current 26.8 µA/µm, low SS 70 mV/dec, and high mobility 27 cm2/Vs. It also shows good stability with small VTH shift < 0.2 V under 125 °C, low PBS shift < 0.35 V and low NBS shift < 0.1 V under 1000s bias stress. Oxide semiconductor transistors is an accumulation mode transistor that requires a gate electric field to turn off the transistor. The transistor design calls for nanometer-thin oxide semiconductor channels. Significant device design tradeoffs exists between high on-current, low off-current, short gate length scalability, and the setting of proper threshold voltages. This talk will give an overview of the above experimental achievements today and the device design considerations for future gain cell memories.

NeuroTAP: Thermal and Memory Access Pattern-aware Data Mapping on 3D DRAM for Maximizing DNN Performance

Deep neural networks (DNNs) have been widely adopted, owing to break-through performance and high accuracy. DNNs exhibit varying memory behavior involving specific and recognizable memory access patterns and access intensity, depending on the selected data reuse in different layers. Such applications have high memory bandwidth demands due to aggressive computations, performing several billion-floating-point-operations-per-second (BFLOPs). 3D DRAMs, providing very high memory access bandwidth, are extensively employed to break the memory wall , bridging the gap between compute and memory while running DNNs. However, the vertical integration in 3D DRAM introduces serious thermal issues, resulting from high power density and close proximity of memory cells, and requires dynamic thermal management (DTM). To unleash the true potential of 3D DRAM and exploit the enormous bandwidth under thermal constraints, there is a need to intelligently map the DNN application’s data across memory channels, pseudo-channels, and banks, minimizing the effective memory latency and reducing the thermal-induced application slowdown. The specific memory access patterns exhibited by a DNN layer execution are crucial to determine a favourable data mapping method for 3D DRAM dies that potentially causes minimal thermal impact, and also maximize DRAM bandwidth utilization. In this work, we propose an application-aware and thermal-sensitive data mapping that intelligently assigns portions of the 3D DRAM to DNN layers, leveraging the knowledge about layer’s memory access patterns and minimizing DTM-induced performance overheads. Additionally, we also deploy a DRAM low-power states based DTM mechanism to keep the 3D DRAM within safe thermal limits. Using our proposal, we observe a performance improvement of 1% to 61%, and memory energy savings of 1% to 55% for popular deep neural networks over state-of-the-art DTM strategies while running DNN inference.

Quantum thermodynamics with a single superconducting vortex.

We demonstrate complete control over dynamics of a single superconducting vortex in a nanostructure, which we coin the Single Vortex Box. Our device allows us to trap the vortex in a field-cooled aluminum nanosquare and expel it on demand with a nanosecond pulse of electrical current. Using the time-resolving nanothermometry we measure [Formula: see text] joules as the amount of the dissipated heat in the elementary process of the single-vortex expulsion. Our experiment enlightens the thermodynamics of the absorption process in the superconducting nanowire single-photon detectors, in which vortices are perceived to be essential for a formation of a detectable hotspot. The demonstrated opportunity to manipulate a single superconducting vortex reliably in a confined geometry comprises a proof of concept of a nanoscale nonvolatile memory cell with subnanosecond write and read operations, which offers compatibility with quantum processors based either on superconducting qubits or on rapid single-flux quantum circuits.

Dysregulated T-cell homeostasis and decreased CD30+ Treg proliferating in aplastic anemia

Aplastic anemia (AA) is an autoimmune hematopoietic disease mediated by autoreactive T cells leading to bone marrow failure. However, the precise role of autoreactive T cells in the development of AA is not fully understood, hindering the advancement of therapeutic and diagnostic strategies. In this study, we conducted a single-cell transcriptome analysis of CD8+ T cells, conventional CD4+ T (CD4+ Tconv) cells, and Treg cells, to elucidate the potential disruption of T cell homeostasis in patients with AA. We identified changes in CD4+ Tconv cells, including loss of homeostasis in naïve and memory cells and increased differentiation potential in T helper type 1 (TH1), T helper type 2 (TH2), and T helper type 17 (TH17) cells. Additionally, we identified naïve and memory CD8+ T cells that were enforced into an effector state. CD127 is an ideal surface marker for assessing the immune state of CD8+ T cells，as identified by flow cytometry. Abnormal expression of TNFSF8 has been observed in AA and other autoimmune diseases. Flow cytometry analysis revealed that TNFRSF8 (CD30), a receptor for TNFSF8, was predominantly present in human Treg cells. Importantly, patients with AA have a decreased CD30+ Treg subset. RNA-sequencing analysis revealed, that the CD30+ Treg cells are characterized by high proliferation and a remarkable immunosuppressive phenotype. Taken, together, we propose that abnormal TNFSF8/TNFRSF8 signaling is involved in dysfunctional T cell immunity by increasing the destruction of CD30+ Treg cells.

Energy efficient improved content addressable memory using quantum-dot cellular automata

Quantum-dot cellular automata (QCA) is an emerging technology with high integration density, low power consumption, and high operating speed. This study introduces a QCA-based modified content addressable memory (CAM) cell employing a five-input minority gate. The functionality, temperature sensitivity, and heat distribution of this modified CAM cell are comprehensively analyzed using QCADesigner E and QCA Pro simulation tools. The results reveal significant advancements over existing designs, with a remarkable 8.33% reduction in area and a substantial 63.7% decrease in energy consumption. Additionally, this modified CAM cell exhibits a notable 5% enhancement in temperature tolerance. These findings emphasize the QCA-based modified CAM cell is more efficient and thermally robust.

Design of a Radiation-Hardened SRAM Cell using 16nm Technology Node

Electronic circuits are exposed to very high energy radiation in the harsh conditions of outer space. This leads to soft errors such as single-event upsets (SEU), double-event upsets (DEU) and single-event transients (SET). The memory circuits are the most susceptible to these soft errors resulting in severe data loss. This paper proposes the design for an SRAM cell that is radiation hardened by design (RHBD). A comparative study of the standard SRAM cell and the RHBD SRAM cell indicates that the proposed design is resilient to SEUs and DEUs. The proposed design is an improvement on the 8T SRAM cell design and includes a 20T triple interlocked cell (TICE) design. The error correction capabilities of both designs are compared by manually injecting bit upsets at crucial nodes in the circuit. It is observed that the TICE design provides a 96.75% and 98.5% improvement over the standard 8T cell for 1-0 and 0-1 bit upsets respectively. The proposed design has been implemented using the 16nm model from the Arizona State University’s Predictive Technology Model (ASU-PTM), and the LTSpice software was used to carry out the simulations. Tools used: LTSpice v17 is the tool used to design the schematic circuits and to obtain the simulation results. The library file used to design the schematic is the 16nm technology node from the library of the Arizona State University’s Predictive Technology Model (ASU-PTM). Methods: To perform a comparative study of the 8T SRAM and 20T TICE, the schematic circuits were designed using the 16nm technology node in LTSpice. A baseline for the expected voltages of logic 0 and logic 1 is established before injecting errors at the sensitive voltage nodes of the circuit. The next step is to manually inject bit upsets at the crucial nodes of the memory cell to induce either a 0-1 upset or a 1-0 upset. The read/write operation is carried out along with the error injection to compare the error mitigation capacity of the circuits. Finally, the results are tabulated to prove that the 20T TICE is resilient to soft errors arising from exposure to high radiation. Results: During the normal operation of the 8T SRAM cell, the observed output voltage corresponding to logic 0 and logic 1 are 25mV and 780mV respectively. The voltage levels increased to 400mV during a 0-1 upset and dropped to 25mV during a 0-1 bit upset. This indicates that the cell is not reliable. In case of the 20T RHBD cell, the voltage levels for the normal operation were 5mV (logic 0) and 780mV (logic 1). The major improvement is shown in the case where the 20T TICE is injected with bit upsets, since it delivers a voltage of just 6mV during a 0-1 bit upset and maintains a voltage of 770mV during a 1-0 bit upset. Conclusion: The work performs the schematic designs for the comparison of the error mitigation capabilities of a 8T SRAM cell and a 20T TICE which is radiation hardened by design. The study proves that the 20T cell is capable of successfully mitigating both a 1-0 bit upset and a 0-1 bit upset

The dynamics and longevity of circulating CD4+ memory T cells depend on cell age and not the chronological age of the host.

Quantifying the kinetics with which memory T cell populations are generated and maintained is essential for identifying the determinants of the duration of immunity. The quality and persistence of circulating CD4 effector memory (TEM) and central memory (TCM) T cells in mice appear to shift with age, but it is unclear whether these changes are driven by the aging host environment, by cell age effects, or both. Here, we address these issues by combining DNA labelling methods, established fate-mapping systems, a novel reporter mouse strain, and mathematical models. Together, these allow us to quantify the dynamics of both young and established circulating memory CD4 T cell subsets, within both young and old mice. We show that that these cells and their descendents become more persistent the longer they reside within the TCM and TEM pools. This behaviour may limit memory CD4 T cell diversity by skewing TCR repertoires towards clones generated early in life, but may also compensate for functional defects in new memory cells generated in old age.

Evaluation of a novel intramuscular prime/intranasal boost vaccination strategy against influenza in the pig model.

Live-attenuated influenza vaccines (LAIV) offer advantages over the commonly used inactivated split influenza vaccines. However, finding the optimal balance between sufficient attenuation and immunogenicity has remained a challenge. We recently developed an alternative LAIV based on the 2009 pandemic H1N1 virus with a truncated NS1 protein and lacking PA-X protein expression (NS1(1-126)-ΔPAX). This virus showed a blunted replication and elicited a strong innate immune response. In the present study, we evaluated the efficacy of this vaccine candidate in the porcine animal model as a pertinent in vivo system. Immunization of pigs via the nasal route with the novel NS1(1-126)-ΔPAX LAIV did not cause disease and elicited a strong mucosal immune response that completely blocked replication of the homologous challenge virus in the respiratory tract. However, we observed prolonged shedding of our vaccine candidate from the upper respiratory tract. To improve LAIV safety, we developed a novel prime/boost vaccination strategy combining primary intramuscular immunization with a haemagglutinin-encoding propagation-defective vesicular stomatitis virus (VSV) replicon, followed by a secondary immunization with the NS1(1-126)-ΔPAX LAIV via the nasal route. This two-step immunization procedure significantly reduced LAIV shedding, increased the production of specific serum IgG, neutralizing antibodies, and Th1 memory cells, and resulted in sterilizing immunity against homologous virus challenge. In conclusion, our novel intramuscular prime/intranasal boost regimen interferes with virus shedding and transmission, a feature that will help combat influenza epidemics and pandemics.

Enhancing stock market prediction accuracy with recurrent deep learning models: A case study on the CAC40 index

This paper explores the application of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks for stock price prediction over a 10-day horizon. The study aims to compare the predictive performance of these two deep learning architectures within the context of financial forecasting. Utilizing historical stock data from the CAC40 dataset, which represents a capitalization-weighted measure of the 40 most significant stocks on the Euronext Paris, we train and evaluate RNN and LSTM models to forecast future stock prices. Our results demonstrate the superior performance of LSTM networks in capturing the intricate temporal dependencies inherent in stock price data. Compared to standard RNNs, LSTM models exhibit higher accuracy and provide more reliable forecasts over the 10-day prediction period. The specialized memory cells and gating mechanisms in LSTM networks enable them to effectively identify both short-term changes and long-term patterns in stock prices, thus outperforming traditional RNN architectures. This enhanced ability to model the complex dynamics of stock market data underscores the potential of LSTM networks to improve investment decision-making, risk management, and the overall efficiency of financial markets. The insights gained from this study contribute to the growing body of knowledge on the application of deep learning in finance and investment, offering valuable guidance for practitioners and researchers seeking to harness the power of advanced algorithms for stock market prediction and optimization.

A CAR enhancer increases the activity and persistence of CAR T cells.

Although chimeric antigen receptor (CAR) T cell therapies have demonstrated promising clinical outcomes, durable remissions remain limited. To extend the efficacy of CAR T cells, we develop a CAR enhancer (CAR-E), comprising a CAR T cell antigen fused to an immunomodulatory molecule. Here we demonstrate this strategy using B cell maturation antigen (BCMA) CAR T cells for the treatment of multiple myeloma, with a CAR-E consisting of the BCMA fused to a low-affinity interleukin 2 (IL-2). This selectively induces IL-2 signaling in CAR T cells upon antigen-CAR binding, enhancing T cell activation and antitumor activity while reducing IL-2-associated toxicities. We show that the BCMA CAR-E selectively binds CAR T cells and increases CAR T cell proliferation, clearance of tumor cells and development of memory CAR T cells. The memory cells retain the ability to re-expand upon restimulation, effectively controlling tumor growth upon rechallenge. Mechanistic studies reveal the involvement of both CAR and IL-2 receptor endodomains in the CAR-E mechanism of action. The CAR-E approach avoids the need for specific engineering and enables CAR T cell therapy with lower cell doses.

Differences in T cell-associated serum markers between ischemic cardiomyopathy and dilated cardiomyopathy.

Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) have similar clinical manifestations but differ in pathogenesis. We aimed to identify T cell-associated serum markers that can be used to distinguish between ICM and DCM. We identified differentially expressed genes (DEGs) with transcriptome sequencing data in GSE116250, and then conducted enrichment analysis of DEGs in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Protein-protein interaction (PPI) networks were used to analyze the relationship between T cells-related genes and identify hub genes. Enzyme-linked immunosorbent assay (ELISA) kits were used to detect T cell-associated proteins in serum, and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of these serum markers. Using the limma package and Venn plots, we found that the non-failing donors (NFD) and DCM groups shared many of the same DEGs and DEGs-enriched functions compared to the ICM group, which were involved in T cell activation and differentiation, among other functions. Subsequently, the immune cell score showed no difference between NFD and DCM, but they were significantly different from ICM patients in CD8 T cells CD4 T cells memory resting and activated, T cells follicular helper, and M1 macrophage. After analyzing T cell-associated DEGs, it was found that 4 DEGs encoding secreted proteins were highly expressed in the ICM group compared with the NFD and DCM groups, namely chemokine (C-C motif) ligand 21 (CCL21), interleukin (IL)-1β, lymphocyte-activation gene 3 (LAG3), and vascular cell adhesion molecule-1 (VCAM-1). Importantly, the serum levels of CCL21, IL-1β, LAG3, and VCAM-1 in ICM patients were all significantly higher than those in DCM patients. The ROC curves showed that the area under the curve (AUC) values of serum CCL21, IL-1β, LAG3, and VCAM-1 were 0.775, 0.868, 0.934, and 0.903, respectively. We have identified four T cell-associated serum markers, CCL21, IL-1β, LAG3, and VCAM-1, as potential diagnostic serum markers that differentiate ICM from DCM.