Multi-layered computational gene networks by engineered tristate logics.

So far, biocomputation strictly follows traditional design principles of digital electronics, which could reach their limits when assembling gene circuits of higher complexity. Here, by creating genetic variants of tristate buffers instead of using conventional logic gates as basic signal processing units, we introduce a tristate-based logic synthesis (TriLoS) framework for resource-efficient design of multi-layered gene networks capable of performing complex Boolean calculus within single-cell populations. This sets the stage for simple, modular, and low-interference mapping of various arithmetic logics of interest and an effectively enlarged engineering space within single cells. We not only construct computational gene networks running full adder and full subtractor operations at a cellular level but also describe a treatment paradigm building on programmable cell-based therapeutics, allowing for adjustable and disease-specific drug secretion logics in vivo. This work could foster the evolution of modern biocomputers to progress toward unexplored applications in precision medicine.

Multiple Input Sensing and Signal Integration Using a Split Cas12a System.

The ability to integrate biological signals and execute a functional response when appropriate is critical for sophisticated cell engineering using synthetic biology. Although the CRISPR-Cas system has been harnessed for synthetic manipulation of the genome, it has not been fully utilized for complex environmental signal sensing, integration, and actuation. Here, we develop a split dCas12a platform and show that it allows for the construction of multi-input, multi-output logic circuits in mammalian cells. The system is highly programmable and can generate expandable AND gates with two, three, and four inputs. It can also incorporate NOT logic by using anti-CRISPR proteins as an OFF switch. By coupling the split dCas12a design to multiple tumor-relevant promoters, we provide a proof of concept that the system can implement logic gating to specifically detect breast cancer cells and execute therapeutic immunomodulatory responses.

Single-Nucleotide-Resolution Computing and Memory in Living Cells.

The ability to process and store information in living cells is essential for developing next-generation therapeutics and studying biology in situ. However, existing strategies have limited recording capacity and are challenging to scale. To overcome these limitations, we developed DOMINO, a robust and scalable platform for encoding logic and memory in bacterial and eukaryotic cells. Using an efficient single-nucleotide-resolution Read-Write head for DNA manipulation, DOMINO converts the living cells' DNA into an addressable, readable, and writable medium for computation and storage. DOMINO operators enable analog and digital molecular recording for long-term monitoring of signaling dynamics and cellular events. Furthermore, multiple operators can be layered and interconnected to encode order-independent, sequential, and temporal logic, allowing recording and control over the combination, order, and timing of molecular events in cells. We envision that DOMINO will lay the foundation for building robust and sophisticated computation-and-memory gene circuits for numerous biotechnological and biomedical applications.

Foundations of reasoning with uncertainty via real-valued logics.

Interest in logics with some notion of real-valued truths has existed since at least Boole and has been increasing in AI due to the emergence of neuro-symbolic approaches, though often their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of such systems. We introduce a rich class of multidimensional sentences, with a sound and complete axiomatization that can be parameterized to cover many real-valued logics, including all the common fuzzy logics, and extend these to weighted versions, and to the case where the truth values are probabilities. Our multidimensional sentences form a very rich class. Each of our multidimensional sentences describes a set of possible truth values for a collection of formulas of the real-valued logic, including which combinations of truth values are possible. Our completeness result is strong, in the sense that it allows us to derive exactly what information can be inferred about the combinations of truth values of a collection of formulas given information about the combinations of truth values of a finite number of other collections of formulas. We give a decision procedure based on linear programming for deciding, for certain real-valued logics and under certain natural assumptions, whether a set of our sentences logically implies another of our sentences. The generality of this work, compared to many previous works on special cases, may provide insights for both existing and new real-valued logics whose inference properties have never been characterized. This work may also provide insights into the reasoning capabilities of deep learning models.

CARTAR: a comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data.

Chimeric antigen receptor (CAR) therapy has emerged as a ground-breaking advancement in cancer treatment, harnessing the power of engineered human immune cells to target and eliminate cancer cells. The escalating interest and investment in CAR therapy in recent years emphasize its profound significance in clinical research, positioning it as a rapidly expanding frontier in the field of personalized cancer therapies. A crucial step in CAR therapy design is choosing the right target as it determines the therapy's effectiveness, safety and specificity against cancer cells, while sparing healthy tissues. Herein, we propose a suite of tools for the identification and analysis of potential CAR targets leveraging expression data from The Cancer Genome Atlas and Genotype-Tissue Expression Project, which are implemented in CARTAR website. These tools focus on pinpointing tumor-associated antigens, ensuring target selectivity and assessing specificity to avoid off-tumor toxicities and can be used to rationally designing dual CARs. In addition, candidate target expression can be explored in cancer cell lines using the expression data for the Cancer Cell Line Encyclopedia. To our best knowledge, CARTAR is the first website dedicated to the systematic search of suitable candidate targets for CAR therapy. CARTAR is publicly accessible at https://gmxenomica.github.io/CARTAR/.

Single-cell multi-omics analysis identifies context-specific gene regulatory gates and mechanisms.

There is a growing interest in inferring context specific gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. This involves identifying the regulatory relationships between transcription factors (TFs) and genes in individual cells, and then characterizing these relationships at the level of specific cell types or cell states. In this study, we introduce scGATE (single-cell gene regulatory gate) as a novel computational tool for inferring TF-gene interaction networks and reconstructing Boolean logic gates involving regulatory TFs using scRNA-seq data. In contrast to current Boolean models, scGATE eliminates the need for individual formulations and likelihood calculations for each Boolean rule (e.g. AND, OR, XOR). By employing a Bayesian framework, scGATE infers the Boolean rule after fitting the model to the data, resulting in significant reductions in time-complexities for logic-based studies. We have applied assay for transposase-accessible chromatin with sequencing (scATAC-seq) data and TF DNA binding motifs to filter out non-relevant TFs in gene regulations. By integrating single-cell clustering with these external cues, scGATE is able to infer context specific networks. The performance of scGATE is evaluated using synthetic and real single-cell multi-omics data from mouse tissues and human blood, demonstrating its superiority over existing tools for reconstructing TF-gene networks. Additionally, scGATE provides a flexible framework for understanding the complex combinatorial and cooperative relationships among TFs regulating target genes by inferring Boolean logic gates among them.

Human verifications: Computable with truth values outside logic.

Cognitive scientists treat verification as a computation in which descriptions that match the relevant situation are true, but otherwise false. The claim is controversial: The logician Gödel and the physicist Penrose have argued that human verifications are not computable. In contrast, the theory of mental models treats verification as computable, but the two truth values of standard logics, true and false, as insufficient. Three online experiments (n = 208) examined participants' verifications of disjunctive assertions about a location of an individual or a journey, such as: 'You arrived at Exeter or Perth'. The results showed that their verifications depended on observation of a match with one of the locations but also on the status of other locations (Experiment 1). Likewise, when they reached one destination and the alternative one was impossible, their use of the truth value: could be true and could be false increased (Experiment 2). And, when they reached one destination and the only alternative one was possible, they used the truth value, true and it couldn't have been false, and when the alternative one was impossible, they used the truth value: true but it could have been false (Experiment 3). These truth values and those for falsity embody counterfactuals. We implemented a computer program that constructs models of disjunctions, represents possible destinations, and verifies the disjunctions using the truth values in our experiments. Whether an awareness of a verification's outcome is computable remains an open question.

A quantum information processing machine for computing by observables.

A quantum machine that accepts an input and processes it in parallel is described. The logic variables of the machine are not wavefunctions (qubits) but observables (i.e., operators) and its operation is described in the Heisenberg picture. The active core is a solid-state assembly of small nanosized colloidal quantum dots (QDs) or dimers of dots. The size dispersion of the QDs that causes fluctuations in their discrete electronic energies is a limiting factor. The input to the machine is provided by a train of very brief laser pulses, at least four in number. The coherent band width of each ultrashort pulse needs to span at least several and preferably all the single electron excited states of the dots. The spectrum of the QD assembly is measured as a function of the time delays between the input laser pulses. The dependence of the spectrum on the time delays can be Fourier transformed to a frequency spectrum. This spectrum of a finite range in time is made up of discrete pixels. These are the visible, raw, basic logic variables. The spectrum is analyzed to determine a possibly smaller number of principal components. A Lie-algebraic point of view is used to explore the use of the machine to emulate the dynamics of other quantum systems. An explicit example demonstrates the considerable quantum advantage of our scheme.

Dual-inhibitory domain iCARs improve the efficiency of the AND-NOT gate CAR T strategy.

CAR (chimeric antigen receptor) T cell therapy has shown clinical success in treating hematological malignancies, but its treatment of solid tumors has been limited. One major challenge is on-target, off-tumor toxicity, where CAR T cells also damage normal tissues that express the targeted antigen. To reduce this detrimental side-effect, Boolean-logic gates like AND-NOT gates have utilized an inhibitory CAR (iCAR) to specifically curb CAR T cell activity at selected nonmalignant tissue sites. However, the strategy seems inefficient, requiring high levels of iCAR and its target antigen for inhibition. Using a TROP2-targeting iCAR with a single PD1 inhibitory domain to inhibit a CEACAM5-targeting CAR (CEACAR), we observed that the inefficiency was due to a kinetic delay in iCAR inhibition of cytotoxicity. To improve iCAR efficiency, we modified three features of the iCAR-the avidity, the affinity, and the intracellular signaling domains. Increasing the avidity but not the affinity of the iCAR led to significant reductions in the delay. iCARs containing twelve different inhibitory signaling domains were screened for improved inhibition, and three domains (BTLA, LAIR-1, and SIGLEC-9) each suppressed CAR T function but did not enhance inhibitory kinetics. When inhibitory domains of LAIR-1 or SIGLEC-9 were combined with PD-1 into a single dual-inhibitory domain iCAR (DiCARs) and tested with the CEACAR, inhibition efficiency improved as evidenced by a significant reduction in the inhibitory delay. These data indicate that a delicate balance between CAR and iCAR signaling strength and kinetics must be achieved to regulate AND-NOT gate CAR T cell selectivity.

Inhibitory CARs fail to protect from immediate T cell cytotoxicity.

Chimeric antigen receptors (CARs) equipped with an inhibitory signaling domain (iCARs) have been proposed as strategy to increase on-tumor specificity of CAR-T cell therapies. iCARs inhibit T cell activation upon antigen recognition and thereby program a Boolean NOT gate within the CAR-T cell. If cancer cells do not express the iCAR target antigen while it is highly expressed on healthy tissue, CAR/iCAR coexpressing T cells are supposed to kill cancer cells but not healthy cells expressing the CAR antigen. In this study, we employed a well-established reporter cell system to demonstrate high potency of iCAR constructs harboring BTLA-derived signaling domains. We then created CAR/iCAR combinations for the clinically relevant antigen pairs B7-H3/CD45 and CD123/CD19 and show potent reporter cell suppression by iCARs targeting CD45 or CD19. In primary human T cells αCD19-iCARs were capable of suppressing T cell proliferation and cytokine production. Surprisingly, the iCAR failed to veto immediate CAR-mediated cytotoxicity. Likewise, T cells overexpressing PD-1 or BTLA did not show impaired cytotoxicity toward ligand-expressing target cells, indicating that inhibitory signaling by these receptors does not mediate protection against cytotoxicity by CAR-T cells. Future approaches employing iCAR-equipped CAR-T cells for cancer therapy should therefore monitor off-tumor reactivity and potential CAR/iCAR-T cell dysfunction.

Logic-enabled textiles.

Textiles hold great promise as a soft yet durable material for building comfortable robotic wearables and assistive devices at low cost. Nevertheless, the development of smart wearables composed entirely of textiles has been hindered by the lack of a viable sheet-based logic architecture that can be implemented using conventional fabric materials and textile manufacturing processes. Here, we develop a fully textile platform for embedding pneumatic digital logic in wearable devices. Our logic-enabled textiles support combinational and sequential logic functions, onboard memory storage, user interaction, and direct interfacing with pneumatic actuators. In addition, they are designed to be lightweight, easily integrable into regular clothing, made using scalable fabrication techniques, and durable enough to withstand everyday use. We demonstrate a textile computer capable of input-driven digital logic for controlling untethered wearable robots that assist users with functional limitations. Our logic platform will facilitate the emergence of future wearables powered by embedded fluidic logic that fully leverage the innate advantages of their textile construction.

Programmable soft valves for digital and analog control.

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials-in this case, by leveraging membrane inversion and tube kinking-two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user's fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

Programmable Threshold Logic Implementations in a Memristor Crossbar Array.

In this study, we demonstrate the implementation of programmable threshold logics using a 32 × 32 memristor crossbar array. Thanks to forming-free characteristics obtained by the annealing process, its accurate programming characteristics are presented by a 256-level grayscale image. By simultaneous subtraction between weighted sum and threshold values with a differential pair in an opposite way, 3-input and 4-input Boolean logics are implemented in the crossbar without additional reference bias. Also, we verify a full-adder circuit and analyze its fidelity, depending on the device programming accuracy. Lastly, we successfully implement a 4-bit ripple carry adder in the crossbar and achieve reliable operations by read-based logic operations. Compared to stateful logic driven by device switching, a 4-bit ripple carry adder on a memristor crossbar array can perform more reliably in fewer steps thanks to its read-based parallel logic operation.

Logic Gates Based on 3D Vertical Junctionless Gate-All-Around Transistors with Reliable Multilevel Contact Engineering.

Vertical gate-all-around (V-GAA) represents the ultimate configuration in the forthcoming transistor industry, but it still encounters challenges in the semiconductor community. This paper introduces, for the first time, a dual-input logic gate circuit achieved using 3D vertical transistors with nanoscale sub-20-nm GAA, employing a novel technique for creating contacts and patterning metallic lines at the bottom level without the conventional lift-off process. This involves a two-step oxidation process: patterning the first field oxide to form bottom metal lines and then creating the gate oxide layer on nanowires (NWs), followed by selective removal from the top and bottom of the nanostructures. VGAA-NW transistors, fabricated using the lift-off-free approach, exhibit improved yield and reduced access resistance, leading to an enhanced drive current while maintaining good immunity against short-channel effects. Finally, elementary two-input logic gates within a single cell, using VNW transistors, demonstrate novel possibilities in advanced logic circuitry design and routing options in 3D.

Nitrogen-Doped 3D-Graphene Advances Near-Infrared Photodetector for Logic Circuits and Image Sensors Overcoming 2D Limitations.

The limitations of two-dimensional (2D) graphene in broadband photodetector are overcome by integrating nitrogen (N) doping into three-dimensional (3D) structures within silicon (Si) via plasma-assisted chemical vapor deposition (PACVD) technology. This contributes to the construction of vertical Schottky heterojunction broad-spectrum photodetectors and applications in logic devices and image sensors. The natural nanoscale resonant cavity structure of 3D-graphene enhances photon capture efficiency, thereby increasing photocarrier generation. N-doping can fine-tune the electronic structure, advancing the Schottky barrier height and reducing dark current. The as-fabricated photodetector exhibits exceptional self-driven photoresponse, especially at 1550 nm, with an excellent photoresponsivity (79.6 A/W), specific detectivity (1013 Jones), and rapid response of 130 µs. Moreover, it enables logic circuits, high-resolution pattern image recognition, and broadband spectra recording across the visible to near-infrared range (400-1550 nm). This research will provide new views and technical support for the development and widespread application of high-performance semiconductor-based graphene broadband detectors.

Reconfigurable Neuromorphic Computing with 2D Material Heterostructures for Versatile Neural Information Processing.

Reconfigurable neuromorphic computing holds promise for advancing energy-efficient neural network implementation and functional versatility. Previous work has focused on emulating specific neural functions rather than an integrated approach. We propose an all two-dimensional (2D) material-based heterostructure capable of performing multiple neuromorphic operations by reconfiguring output terminals in response to stimuli. Specifically, our device can synergistically emulate the key neural elements of the synapse, neuron, and dendrite, which play important and interrelated roles in information processing. Dendrites, the branches that receive and transmit presynaptic action potentials, possess the ability to nonlinearly integrate and filter incoming signals. The proposed heterostructure allows reconfiguration between different operation modes, demonstrating its potential for diverse computing tasks. As a proof of concept, we show that the device can perform basic Boolean logic functions. This highlights its applicability to complex neural-network-based information processing problems. Our integrated neuromorphic approach may advance the development of versatile, low-power neuromorphic hardware.

Optically Mediated Hydrogel-Based Ionic Diode.

Ionic diodes with environmentally modulated ion-rectifying characteristics have attracted much attention and show great promise in the construction of smart devices with environmental adaptability. One immediate challenge is to integrate stimuli responsiveness and ion rectification into one single ionic diode, which requires a close cooperation of chemical principles and device technologies. Herein, an ionic diode based on a photoresponsive hydrogel with optically mediated ion-rectifying performances is introduced. Relying on the photoresponsive concentration of proton in the hydrogel, the ionic current rectification can be prominently enhanced upon ultraviolet (UV) irradiation. A maximum ionic current rectification ratio of the optically mediated ionic diode about 4 × 105 is achieved. Furthermore, the hydrogel-based diode can serve as an AND logic gate operated by UV light and voltage bias as two independent inputs. As a proof of concept, to use the optically mediated diode is achieved to modulate the feedback of a robot with logic behaviors. This work provides a novel and valuable strategy for designing functional hydrogel-based devices with the integration of stimuli-responsiveness and logic signal processing through chemical approaches.

2D Dual Gate Field-Effect Transistor Enabled Versatile Functions.

Advanced computing technologies such as distributed computing and the Internet of Things require highly integrated and multifunctional electronic devices. Beyond the Si technology, 2D-materials-based dual-gate transistors are expected to meet these demands due to the ultra-thin body and the dangling-bond-free surface. In this work, a molybdenum disulfide (MoS2 ) asymmetric-dual-gate field-effect transistor (ADGFET) with an In2 Se3 top gate and a global bottom gate is designed. The independently controlled double gates enable the device to achieve an on/off ratio of 106 with a low subthreshold swing of 94.3 mV dec-1 while presenting a logic function. The coupling effect between the double gates allows the top gate to work as a charge-trapping layer, realizing nonvolatile memory (105 on/off ratio with retention time over 104 s) and six-level memory states. Additionally, ADGFET displays a tunable photodetection with the responsivity reaching the highest value of 857 A W-1 , benefiting from the interface coupling between the double gates. Meanwhile, the photo-memory property of ADGFET is also verified by using the varying exposure dosages-dependent illumination. The multifunctional applications demonstrate that the ADGFET provides an alternative way to integrate logic, memory, and sensing into one device architecture.

Self-Assembled DNA Nanospheres Driven by Carbon Dots for MicroRNAs Imaging in Tumor via Logic Circuit.

DNA nanostructures with diverse biological functions have made significant advancements in biomedical applications. However, a universal strategy for the efficient production of DNA nanostructures is still lacking. In this work, a facile and mild method is presented for self-assembling polyethylenimine-modified carbon dots (PEI-CDs) and DNA into nanospheres called CANs at room temperature. This makes CANs universally applicable to multiple biological applications involving various types of DNA. Due to the ultra-small size and strong cationic charge of PEI-CDs, CANs exhibit a dense structure with high loading capacity for encapsulated DNA while providing excellent stability by protecting DNA from enzymatic hydrolysis. Additionally, Mg2+ is incorporated into CANs to form Mg@CANs which enriches the performance of CANs and enables subsequent biological imaging applications by providing exogenous Mg2+. Especially, a DNAzyme logic gate system that contains AND and OR Mg@CANs is constructed and successfully delivered to tumor cells in vitro and in vivo. They can be specifically activated by endogenic human apurinic/apyrimidinic endonuclease 1 and recognize the expression levels of miRNA-21 and miRNA-155 at tumor sites by logic biocomputing. A versatile pattern for delivery of diverse DNA and flexible logic circuits for multiple miRNAs imaging are developed.

Multifunctional Antimonene-Silver Nanocomposites for Ultra-Multi-Mode and Multi-Analyte Sensing, Parallel and Batch Logic Computing, Long-Text Information Protection.

To simulate life's emergent functions, mining the multiple sensing capabilities of nanosystems, and digitizing networks of transduction signals and molecular interactions, is an ongoing endeavor. Here, multifunctional antimonene-silver nanocomposites (AM-Ag NCs) are synthesized facilely and fused for molecular sensing and digitization applications (including ultra-multi-mode and multi-analyte sensing, parallel and batch logic computing, long-text information protection). By mixing surfactant, AM, Ag+ and Sodium borohydride (NaBH4) at room temperature for 5 min, the resulting NCs are comprised of Ag nanoparticles scattered within AM nanosheets and protected by the surfactant. Interestingly, AM-Ag NCs exhibit ultra-multi-mode sensing ability for multiplex metal ions (Hg2+, Fe3+, or Al3+), which significantly improved selectivity (≈2 times) and sensitivity (≈400 times) when analyzing the combined channels. Moreover, multiple sensing capabilities of AM-Ag NCs enable diverse batch and parallel molecular logic computations (including advanced cascaded logic circuits). Ultra-multi-mode selective patterns of AM-Ag NCs to 18 kinds of metal ions can be converted into a series of binary strings by setting the thresholds, and realized high-density, long-text information protection for the first time. This study provides new ideas and paradigms for the preparation and multi-purpose application of 2D nanocomposites, but also offers new directions for the fusion of molecular sensing and informatization.