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Operating system (OS) kernels form the backbone of system software. They can have a significant impact on the resilience and security of today's computers. Recent efforts have demonstrated the feasibility of formally verifying simple general-purpose kernels, but they have ignored the important issues of concurrency, which include not just user and I/O concurrency on a single core, but also multi-core parallelism with fine-grained locking. In this work, we present CertiKOS, a novel compositional framework for building verified concurrent OS kernels. Concurrency allows interleaved execution of programs belonging to different abstraction layers and running on different CPUs/threads. Each such layer can have a different set of observable events. In CertiKOS, these layers and their observable events can be formally specified, and each module can then be verified at the abstraction level it belongs to. To link all the verified pieces together, CertiKOS enforces a so-called contextual refinement property for every such piece, which states that the implementation will behave like its specification under any concurrent context with any valid interleaving. Using CertiKOS, we have successfully developed a practical concurrent OS kernel, called mC2, and built the formal proofs of its correctness in Coq. The mC2 kernel is written in 6500 lines of C and x86 assembly and runs on stock x86 multicore machines. To our knowledge, this is the first correctness proof of a general-purpose concurrent OS kernel with fine-grained locking.

A key ingredient contributing to the success of CompCert, the state-of-the-art verified compiler for C, is its block-based memory model, which is used uniformly for all of its languages and their verified compilation. However, CompCert's memory model lacks an explicit notion of stack. Its target assembly language represents the runtime stack as an unbounded list of memory blocks, making further compilation of CompCert assembly into more realistic machine code difficult since it is not possible to merge these blocks into a finite and continuous stack. Furthermore, various notions of verified compositional compilation rely on some kind of mechanism for protecting private stack data and enabling modification to the public stack-allocated data, which is lacking in the original CompCert. These problems have been investigated but not fully addressed before, in the sense that some advanced optimization passes that significantly change the ways stack blocks are (de-)allocated, such as tailcall recognition and inlining, are often omitted. We propose a lightweight and complete solution to the above problems. It is based on the enrichment of CompCert's memory model with an abstract stack that keeps track of the history of stack frames to bound the stack consumption and that enforces a uniform stack access policy by assigning fine-grained permissions to stack memory. Using this enriched memory model for all the languages of CompCert, we are able to reprove the correctness of the full compilation chain of CompCert, including all the optimization passes. In the end, we get Stack-Aware CompCert, a complete extension of CompCert that enforces the finiteness of the stack and fine-grained stack permissions. Based on Stack-Aware CompCert, we develop CompCertMC, the first extension of CompCert that compiles into a low-level language with flat memory spaces. Based on CompCertMC, we develop Stack-Aware CompCertX, a complete extension of CompCert that supports a notion of compositional compilation that we call contextual compilation by exploiting the uniform stack access policy provided by the abstract stack.

A TEMPO-catalysed direct amination of arene through C-H bond cleavage employing N-fluorobenzenesulfonimide (NFSI) as the amination reagent in good to excellent yields with broad arene scope in the absence of any metal, ligand or additive is reported. Unlike previous transition metal-catalysed aminations in which high reaction temperatures are usually necessary, this novel reaction at room temperature is the first example of C-H amination with NFSI that is realised via organocatalysis. The probable mechanism of this concise amination is also proposed.

Shark is a cartilaginous fish that produces new antigen receptor (IgNAR) antibodies. This antibody is identified with a similar human heavy chain but dissimilar sequences. The variable domain (VNAR) of IgNAR is stable and small in size, these features are desirable for drug discovery. Previous study results revealed the effectiveness of VNAR as a single molecule or a combination molecule to treat diseases both in vivo and in vitro with promising clinical applications. We showed the first evidence of IgNAR alternative splicing from spotted bamboo shark (Chiloscyllium plagiosum), broadening our understanding of the IgNARs characteristics. In this review, we summarize the discoveries on IgNAR with a focus on its advantages for therapeutic development based on its peculiar biochemistry and molecular structure. Proper applications of IgNAR will provide a novel avenue to understand its special presence in cartilaginous fishes as well as designing a number of drugs for undefeated diseases.

Macrophages are dominant innate immune cells. They demonstrate remarkable heterogeneity and plasticity that are essential for homeostasis and host defense. The heterogeneity of tissue macrophages is shaped by the ontogeny, tissue factors, and environmental signals, a pattern in a tissue-associated latitudinal manner. At the same time, macrophages have long been considered as mainly plastic cells. These cells respond to stimulation quickly and in a stimulus-specific way by utilizing a longitudinal cascaded activation, including coordination of signal transducer, epigenetic elements, and transcription factors, conclusively determine the macrophage phenotypes and functions. With the development of cutting-edge technologies, such as fate-mapping, single-cell transcriptomics, ipsc platform, nanotherapeutic materials, etc., our understanding of macrophage biology and the roles in the pathogenesis of diseases is much advanced. This review summarizes recent progress on the latitudinal and longitudinal regulation of tissue macrophages in inflammatory diseases. The latitudinal regulation covers the tissue macrophage origins, tissue factors, and environmental signals, reflecting the macrophage heterogeneity. The longitudinal regulation focuses on how multiple factors shape the phenotypes and functions of macrophage subsets to gain plasticity in inflammatory diseases (i.e., inflammatory bowel disease). In addition, how to target macrophages as a potential therapeutic approach and cutting edge-technologies for tissue macrophage study are also discussed in this review.

This paper presents a design framework for machine learning applications that operate in systems such as cyber-physical systems where time is a scarce resource. We manage the tradeoff between processing time and solution quality by performing as much preprocessing of data as time will allow. This approach leads us to a design framework in which there are two separate learning networks: one for preprocessing and one for the core application functionality. We show how these networks can be trained together and how they can operate in an anytime fashion to optimize performance.

The BTLA and HVEM are two well-characterized immune checkpoint inhibitors in humans and other mammalian species. However, the occurrence and functionality of these two molecules in non-mammalian species remain poorly understood. In the present study, we identified the BTLA and HVEM homologs from large yellow croaker (Larimichthys crocea), an economically important marine species of the perciform fish family. The Larimichthys crocea BTLA and HVEM (LcBTLA and LcHVEM) share conserved structural features to their mammalian counterparts, and they were expressed in various tissues and cells examined at different transcriptional levels, with particular abundance in immune-relevant tissues and splenic leukocytes. Immunofluorescence staining and flow cytometry analysis showed that LcHVEM and LcBTLA proteins were distributed on MHC-II+ APCs and CD4-2+ T cells, and a strong interaction between LcBTLA and LcHVEM was detected in splenic leukocytes in the mixed lymphocyte reaction (MLR). By blockade assays using anti-LcBTLA and anti-LcHVEM Abs as well as recombinant soluble LcBTLA and LcHVEM proteins in different combinations, it was found that LcBTLA-LcHVEM interactions play an important inhibitory role in the activation of alloreactive T cells using MLR as a model, and APC-initiated antigen-specific CD4-2+ T cells in response to A. hydrophila (A. h) stimulation. These observations highlight the extensive functional roles of LcBTLA and LcHVEM immune-checkpoint inhibitors in allogeneic T cell reactions, and CD4-2+ T cell-mediated adaptive immune responses in Larimichthys crocea. Thus, the BTLA-HVEM checkpoint may represent an ancient coinhibitory pathway, which was originated in fish and was conserved from fish to mammals throughout the vertebrate evolution.

We present CompCertELF, the first extension to CompCert that supports verified compilation from C programs all the way to a standard binary file format, i.e., the ELF object format. Previous work on Stack-Aware CompCert provides a verified compilation chain from C programs to assembly programs with a realistic machine memory model. We build CompCertELF by modifying and extending this compilation chain with a verified assembler which further transforms assembly programs into ELF object files. CompCert supports large-scale verification via verified separate compilation: C modules can be written and compiled separately, and then linked together to get a target program that refines the semantics of the program linked from the source modules. However, verified separate compilation in CompCert only works for compilation to assembly programs, not to object files. For the latter, the main difficulty is to bridge the two different views of linking: one for CompCert's programs that allows arbitrary shuffling of global definitions by linking and the other for object files that treats blocks of encoded definitions as indivisible units. We propose a lightweight approach that solves the above problem without any modification to CompCert's framework for verified separate compilation: by introducing a notion of syntactical equivalence between programs and proving the commutativity between syntactical equivalence and the two different kinds of linking, we are able to transit from the more abstract linking operation in CompCert to the more concrete one for ELF object files. By applying this approach to CompCertELF, we obtain the first compiler that supports verified separate compilation of C programs into ELF object files.

IgZ or its equivalent IgT is a newly discovered teleost specific Ig class that is highly specialized in mucosal immunity. However, whether this IgZ/IgT class participates in other biological processes remains unclear. In this study, we unexpectedly discovered that IgZ is highly expressed in zebrafish ovary, accumulates in unfertilized eggs, and is transmitted to offspring from eggs to zygotes. Maternally transferred IgZ in zygotes is found at the outer and inner layers of chorion, perivitelline space, periphery of embryo body, and yolk, providing different lines of defense against pathogen infection. A considerable number of IgZ+ B cells are found in ovarian connective tissues distributed between eggs. Moreover, pIgR, the transporter of IgZ, is also expressed in the ovary and colocalizes with IgZ in the zona radiata of eggs. Thus, IgZ is possibly secreted by ovarian IgZ+ B cells and transported to eggs through association with pIgR in a paracrine manner. Maternal IgZ in zygotes showed a broad bacteriostatic activity to different microbes examined, and this reactivity can be manipulated by orchestrating desired bacteria in water where parent fish live or immunizing the parent fish through vaccination. These observations suggest that maternal IgZ may represent a group of polyclonal Abs, providing protection against various environmental microbes encountered by a parent fish that were potentially high risk to offspring. To our knowledge, our findings provide novel insights into a previously unrecognized functional role of IgZ/IgT Ig in the maternal transfer of immunity in fish, greatly enriching current knowledge about this ancient Ig class.

Organelles entail specialized molecules to regulate their essential cellular processes. However, systematically elucidating the subcellular distribution of functional molecules such as long non-coding RNAs (lncRNAs) in tissue homeostasis and diseases has not been fully achieved. Here, we characterized the organelle-associated lncRNAs from mitochondria, lysosome, and endoplasmic reticulum (ER), respectively, and revealed the diverse and abundant distribution of lncRNAs. Among them, we identified mitochondrial lncRNA Growth-Arrest-Specific 5 (GAS5) as a tumor suppressor in maintaining cellular energy homeostasis. Mechanistically, energy stress-induced GAS5 modulated mitochondria TCA flux by declining metabolic tandem association of FH-MDH2-CS, the canonical members of the TCA cycle. Remarkably, the expression of GAS5 negatively related with levels of its associated mitochondrial metabolic enzymes and breast cancer development. Together with the detailed functional annotations, this subcellular lncRNA identification revealed the human cell’s inquisitively complex architecture, aiding in the development of new strategies for the clinical application of organelle-associated lncRNAs.

Formal methods have advanced to the point where the functional correctness of various large system components has been mechanically verified. However, the diversity of semantic models used across projects makes it difficult to connect these component to build larger certified systems. Given this, we seek to embed these models and proofs into a generalpurpose framework where they could interact. We believe that a synthesis of game semantics, the refinement calculus, and algebraic effects can provide such a framework. To combine game semantics and refinement, we replace the downset completion typically used to construct strategies from posets of plays. Using the free completely distributive completion, we construct strategy specifications equipped with arbitrary angelic and demonic choices and ordered by a generalization of alternating refinement. This provides a novel approach to nondeterminism in game semantics. Connecting algebraic effects and game semantics, we interpret effect signatures as games and define two categories of effect signatures and strategy specifications. The resulting models are sufficient to represent the behaviors of a variety of low-level components, including the certified abstraction layers used to verify the operating system kernel CertiKOS.

Deep-learning driven safety-critical autonomous systems, such as self-driving cars, must be able to detect situations where its trained model is not able to make a trustworthy prediction. This ability to determine the novelty of a new input with respect to a trained model is critical for such systems because novel inputs due to changes in the environment, adversarial attacks, or even unintentional noise can potentially lead to erroneous, perhaps life-threatening decisions. This paper proposes a learning framework that leverages information learned by the prediction model in a task-aware manner to detect novel scenarios. We use network saliency to provide the learning architecture with knowledge of the input areas that are most relevant to the decision-making and learn an association between the saliency map and the predicted output to determine the novelty of the input. We demonstrate the efficacy of this method through experiments on real-world driving datasets as well as through driving scenarios in our in-house indoor driving environment where the novel image can be sampled from another similar driving dataset with similar features or from adversarial attacked images from the training dataset. We find that our method is able to systematically detect novel inputs and quantify the deviation from the target prediction through this task-aware approach.

Objective Lipomatosis of nerve (LN) is a rare tumor-like condition with epineural and perineural infiltration by adipose and fibrous tissue. The purpose was to analyze the ultrasonographic findings of LN involving upper limb peripheral nerves. Methods This was a retrospective analysis of a series of 8 patients with LN involving upper-limb peripheral nerves between 2013 and 2019. All patients underwent preoperative ultrasonography for the upper-extremity nerves and were diagnosed as LN by surgery. The clinical manifestations, ultrasonography characteristics, and accuracy were analyzed. Results In this series, LN was involved in 10 peripheral nerves from 8 patients. The median nerve was the most commonly affected nerve (60%). Four cases presented macrodactyly combined with masses from distal forearm and extending to wrist and palm areas. Among 8 patients, 5 cases were diagnosed with LN by preoperative ultrasonography, an accuracy of 62.5%. Axial ultrasonic imaging showed the punctate hypoechoic fascicles was embedded in hyperechoic adipose tissue in the “lotus root–like” appearance; longitudinal ultrasonic imaging showed the strip hypoechoic fascicles alternates with hyperechoic adipose tissue in the “cable-like” appearance. Meanwhile, ultrasonic imaging showed the thickened of adipose tissue around the affected nerve and the enlargement of flexor tendons in some patients. Conclusions Ultrasonography has the potential to be a useful tool for the noninvasive examination of LN. The possibility of LN should be considered in patients with a mass in wrist and palm, macrodactyly, or syndactyly. Our finding may benefit the preoperative differential diagnosis with common nerve tumors.

Learning techniques are advancing the utility and capability of modern embedded systems. However, the challenge of incorporating learning modules into embedded systems is that computing resources are scarce. For such a resource-constrained environment, we have developed a framework for learning abstract information early and learning more concretely as time allows. The intermediate results can be utilized to prepare for early decisions/actions as needed. To apply this framework to a classification task, the datasets are categorized in an abstraction hierarchy. Then the framework classifies intermediate labels from the most abstract level to the most concrete. Our proposed method outperforms the existing approaches and reference baselines in terms of accuracy. We show our framework with different architectures and on various benchmark datasets CIFAR-10, CIFAR-100, and GTSRB. We measure prediction times on GPU-equipped embedded computing platforms as well.

NLRP1 inflammasome is one of the best-characterized inflammasomes in humans and other mammals. However, the existence of this inflammasome in nonmammalian species remains poorly understood. In this study, we report the molecular and functional identification of an NLRP1 homolog, Danio rerio NLRP1 (DrNLRP1) from a zebrafish (D. rerio) model. This DrNLRP1 possesses similar structural architecture to mammalian NLRP1s. It can trigger the formation of a classical inflammasome for the activation of zebrafish inflammatory caspases (D. rerio Caspase [DrCaspase]–A and DrCaspase-B) and maturation of D. rerio IL-1β in a D. rerio ASC (DrASC)–dependent manner. In this process, DrNLRP1 promotes the aggregation of DrASC into a filament with DrASCCARD core and DrASCPYD cluster. The assembly of DrNLRP1 inflammasome depends on the CARD–CARD homotypic interaction between DrNLRP1 and DrASCCARD core, and PYD–PYD interaction between DrCaspase-A/B and DrASCPYD cluster. The FIIND domain in DrNLRP1 is necessary for inflammasome assembly. To understand the mechanism of how the two DrCaspases are coordinated in DrNLRP1 inflammasome, we propose a two-step sequential activation model. In this model, the recruitment and activation of DrCaspase-A/B in the inflammasome is shown in an alternate manner, with a preference for DrCaspase-A followed by a subsequent selection for DrCaspase-B. By using morpholino oligonucleotide–based knockdown assays, the DrNLRP1 inflammasome was verified to play important functional roles in antibacterial innate immunity in vivo. These observations demonstrate that the NLRP1 inflammasome originated as early as in teleost fish. This finding not only gives insights into the evolutionary history of inflammasomes but also provides a favorable animal model for the study of NLRP1 inflammasome-mediated immunology and diseases.

Concurrent abstraction layers are ubiquitous in modern computer systems because of the pervasiveness of multithreaded programming and multicore hardware. Abstraction layers are used to hide the implementation details (e.g., fine-grained synchronization) and reduce the complex dependencies among components at different levels of abstraction. Despite their obvious importance, concurrent abstraction layers have not been treated formally. This severely limits the applicability of layer-based techniques and makes it difficult to scale verification across multiple concurrent layers. In this paper, we present CCAL---a fully mechanized programming toolkit developed under the CertiKOS project---for specifying, composing, compiling, and linking certified concurrent abstraction layers. CCAL consists of three technical novelties: a new game-theoretical, strategy-based compositional semantic model for concurrency (and its associated program verifiers), a set of formal linking theorems for composing multithreaded and multicore concurrent layers, and a new CompCertX compiler that supports certified thread-safe compilation and linking. The CCAL toolkit is implemented in Coq and supports layered concurrent programming in both C and assembly. It has been successfully applied to build a fully certified concurrent OS kernel with fine-grained locking.

Inner ear hair cells are mechanoreceptors responsible for hearing. Pathogenic defects of hair cell-specific genes are one of the major causes of deafness. The BarH class homeobox gene Barhl1 is a deafness gene expressed in developing hair cells, yet the role of Barhl1 during hair cell development remains poorly understood. In the present study, we first established an in vitro differentiation system to efficiently obtain mouse embryonic stem cell (mESC)-derived hair cell-like cells. Subsequently, a mESC line carrying a targeted disruption of Barhl1 was generated using CRISPR/Cas9 technology and subjected to the established in vitro hair cell differentiation protocol. Targeted disruption of Barhl1 does not affect the induction of mESCs toward early primitive ectoderm-like (EPL) cells and otic progenitors but strongly inhibits the differentiation of hair cell-like cells. Using RNA-sequencing and bioinformatics, we further unravel the molecular mechanism underlying Barhl1-mediated hair cell development. Our data demonstrate the essential role of Barhl1 during hair cell development and provide a basis for the treatment of Barhl1 mutation-based deafness.

CD40 and CD154 are one of the best-characterized costimulatory molecules essential for adaptive immunity, which extensively involved in T and B cell activation, IgM Ab production, isotype class switching, germinal center formation and affinity maturation. However, the functionality of CD40 and CD154 in IgZ-mediated immunity remains limited. In this study, we explored the regulatory role of Cd40-Cd154 interaction in IgZ-mediated antibacterial immunity in zebrafish. The results showed that the IgZ-mediated antibacterial response can be significantly induced in response to A. hydrophila infection. The percentage of Cd40+IgZ+ B cells and the production of IgZ Ab were substantially increased upon A. hydrophila stimulation, but these reactions were markedly declined in Cd154 blockade fish by administering anti-Cd154 Ab or recombinant sCd40-Ig protein, accompanied with the impairment of the vaccine-initiated IgZ-mediated immunoprotection of fish against A. hydrophila infection. These observations suggested the essential role of Cd40-Cd154 interaction in IgZ-mediated bacterial immunity. Notably, the Cd40 and Cd154 costimulatory signals are required for a TD antigen-induced IgZ immunity, but are not indispensable for a TI antigen-induced IgZ immune response. These findings indicated the differential role of Cd40-Cd154 interaction in bacterial TD and TI antigen-induced IgZ immunity, which suggested the existence of diverse regulatory mechanisms underlying IgZ-mediated antibacterial immune reactions. To our knowledge, this is the first report to show the functional role of Cd40-Cd154 costimulatory signaling pathway in IgZ-mediated immune defense against bacterial infection. We hope this study will improve the current understanding of the coevolution between the IgZ/IgT immunoglobins and CD40/CD154 costimulatory molecules.

An operating system (OS) kernel forms the lowest level of any system software stack. The correctness of the OS kernel is the basis for the correctness of the entire system. Recent efforts have demonstrated the feasibility of building formally verified general-purpose kernels, but it is unclear how to extend their work to verify the functional correctness of device drivers, due to the non-local effects of interrupts. In this paper, we present a novel compositional framework for building certified interruptible OS kernels with device drivers. We provide a general device model that can be instantiated with various hardware devices, and a realistic formal model of interrupts, which can be used to reason about interruptible code. We have realized this framework in the Coq proof assistant. To demonstrate the effectiveness of our new approach, we have successfully extended an existing verified non-interruptible kernel with our framework and turned it into an interruptible kernel with verified device drivers. To the best of our knowledge, this is the first verified interruptible operating system with device drivers.