Enzyme-Enabled Droplet Biobattery for Powering Synthetic Tissues.

Enzyme-enabled biobatteries are promising green options to power the next-generation of bioelectronics and implantable medical devices. However, existing power sources based on enzymatic biofuel chemistry exhibit limited scale-down feasibility due to the solid and bulky battery structures. Therefore, miniature and soft alternatives are needed for integration with implants and tissues. Here, a biobattery built from nanolitre droplets, fuelled by the enzyme-enabled oxidation of reduced nicotinamide adenine dinucleotide, generates electrical outputs and powers ion fluxes in droplet networks. Optimization of the droplet biobattery components ensures a stable output current of ~13,000 pA for over 24 h, representing a more than 600-fold increase in output over previous approaches, including light-driven processes. The enzyme-enabled droplet biobattery opens new avenues in bioelectronics and bioiontronics, exemplified by tasks such as the ability to drive electrochemical signal transmission in integrated synthetic tissues.

Integration of 3D-printed cerebral cortical tissue into an ex vivo lesioned brain slice.

Engineering human tissue with diverse cell types and architectures remains challenging. The cerebral cortex, which has a layered cellular architecture composed of layer-specific neurons organised into vertical columns, delivers higher cognition through intricately wired neural circuits. However, current tissue engineering approaches cannot produce such structures. Here, we use a droplet printing technique to fabricate tissues comprising simplified cerebral cortical columns. Human induced pluripotent stem cells are differentiated into upper- and deep-layer neural progenitors, which are then printed to form cerebral cortical tissues with a two-layer organization. The tissues show layer-specific biomarker expression and develop a structurally integrated network of processes. Implantation of the printed cortical tissues into ex vivo mouse brain explants results in substantial structural implant-host integration across the tissue boundaries as demonstrated by the projection of processes and the migration of neurons, and leads to the appearance of correlated Ca2+ oscillations across the interface. The presented approach might be used for the evaluation of drugs and nutrients that promote tissue integration. Importantly, our methodology offers a technical reservoir for future personalized implantation treatments that use 3D tissues derived from a patient's own induced pluripotent stem cells.

Preliminary study of noninvasive prenatal screening for 22q11.2 deletion/duplication syndrome using multiplex dPCR assay.

OBJECTIVE: This study aimed to establish a cell-free fetal DNA (cffDNA) assay using multiplex digital PCR (dPCR) for identifying fetuses at increased risk of 22q11.2 deletion/duplication syndrome. METHODS: Six detection sites and their corresponding probes were designed for the 22q11.2 recurrent region. A dPCR assay for the noninvasive screening of 22q11.2 deletion/duplication syndrome was established. A total of 130 plasma samples from pregnant women (including 15 samples with fetal 22q11.2 deletion/duplication syndrome) were blindly tested for evaluating the sensitivity and specificity of the established assay. RESULTS: DNA with different sizes of 22q11.2 deletion/duplication was detected via dPCR, indicating that the designed probes and detection sites were reasonable and effective. In the retrospective clinical samples, 11 out of 15 samples of pregnant women with 22q11.2 deletion/duplication were detected during the cffDNA assay, and accurate regional localization was achieved. Among the 115 normal samples, 111 were confirmed to be normal. Receiver operating characteristic curves were used for assessing the cut-off values and AUC for these samples. The sensitivity, specificity, and positive as well as negative predictive values were 73.3%, 96.5%, 73.3%, and 96.5%, respectively. CONCLUSION: The cffDNA assay based on dPCR technology for the noninvasive detection of 22q11.2 recurrent copy number variants in fetuses detected most affected cases, including smaller but relatively common nested deletions, with a low false-positive rate. It is a potential, efficient and simple method for the noninvasive screening of 22q11.2 deletion/duplication syndrome.

A microscale soft ionic power source modulates neuronal network activity.

Bio-integrated devices need power sources to operate1,2. Despite widely used technologies that can provide power to large-scale targets, such as wired energy supplies from batteries or wireless energy transduction3, a need to efficiently stimulate cells and tissues on the microscale is still pressing. The ideal miniaturized power source should be biocompatible, mechanically flexible and able to generate an ionic current for biological stimulation, instead of using electron flow as in conventional electronic devices4-6. One approach is to use soft power sources inspired by the electrical eel7,8; however, power sources that combine the required capabilities have not yet been produced, because it is challenging to obtain miniaturized units that both conserve contained energy before usage and are easily triggered to produce an energy output. Here we develop a miniaturized soft power source by depositing lipid-supported networks of nanolitre hydrogel droplets that use internal ion gradients to generate energy. Compared to the original eel-inspired design7, our approach can shrink the volume of a power unit by more than 105-fold and it can store energy for longer than 24 h, enabling operation on-demand with a 680-fold greater power density of about 1,300 W m-3. Our droplet device can serve as a biocompatible and biological ionic current source to modulate neuronal network activity in three-dimensional neural microtissues and in ex vivo mouse brain slices. Ultimately, our soft microscale ionotronic device might be integrated into living organisms.

Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua's circuit.

This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master-slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov-Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua's circuit, illustrate the feasibility and universality of the related technologies in this paper.

FET-LM: Flow-Enhanced Variational Autoencoder for Topic-Guided Language Modeling.

Variational autoencoder (VAE) is widely used in tasks of unsupervised text generation due to its potential of deriving meaningful latent spaces, which, however, often assumes that the distribution of texts follows a common yet poor-expressed isotropic Gaussian. In real-life scenarios, sentences with different semantics may not follow simple isotropic Gaussian. Instead, they are very likely to follow a more intricate and diverse distribution due to the inconformity of different topics in texts. Considering this, we propose a flow-enhanced VAE for topic-guided language modeling (FET-LM). The proposed FET-LM models topic and sequence latent separately, and it adopts a normalized flow composed of householder transformations for sequence posterior modeling, which can better approximate complex text distributions. FET-LM further leverages a neural latent topic component by considering learned sequence knowledge, which not only eases the burden of learning topic without supervision but also guides the sequence component to coalesce topic information during training. To make the generated texts more correlative to topics, we additionally assign the topic encoder to play the role of a discriminator. Encouraging results on abundant automatic metrics and three generation tasks demonstrate that the FET-LM not only learns interpretable sequence and topic representations but also is fully capable of generating high-quality paragraphs that are semantically consistent.

Neural-Network-Based Adaptive Control of Uncertain MIMO Singularly Perturbed Systems With Full-State Constraints.

This article investigates the tracking control problem for a class of nonlinear multi-input-multi-output (MIMO) uncertain singularly perturbed systems (SPSs) with full-state constraints. The underlying issues become more challenging because two-time-scale characteristics and full state constraints are involved. To this end, first, the adaptive neural network (NN) control method is designed to handle system uncertainties in the design process. Second, the nonlinear state-dependent coordinate transformation functions are employed to avoid the violation of full-state constraints and feasibility conditions for intermediate controllers. Furthermore, by introducing an appropriate ε -dependent Lyapunov function, the potential ill-conditioned numerical problems in the design process of SPSs are avoided, and the stability of the nonlinear SPSs is proven. Finally, two examples are presented to illustrate the validity of the proposed adaptive NN control scheme.

Droplet printing reveals the importance of micron-scale structure for bacterial ecology.

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array. We print strains of the gut bacterium Escherichia coli that naturally compete with one another using protein toxins. Our experiments reveal that toxin-producing strains largely eliminate susceptible non-producers when genotypes are well-mixed. However, printing strains side-by-side creates an ecological refuge where susceptible strains can persist in large numbers. Moving to competitions between toxin producers reveals that spatial structure can make the difference between one strain winning and mutual destruction. Finally, we print different potential barriers between competing strains to understand how ecological refuges form, which shows that cells closest to a toxin producer mop up the toxin and protect their clonemates. Our work provides a method to generate customised bacterial communities with defined spatial distributions, and reveals that micron-scale changes in these distributions can drive major shifts in ecology.

Single-Molecule Observation of Intermediates in Bioorthogonal 2-Cyanobenzothiazole Chemistry.

We report a single-molecule mechanistic investigation into 2-cyanobenzothiazole (CBT) chemistry within a protein nanoreactor. When simple thiols reacted reversibly with CBT, the thioimidate monoadduct was approximately 80-fold longer-lived than the tetrahedral bisadduct, with important implications for the design of molecular walkers. Irreversible condensation between CBT derivatives and N-terminal cysteine residues has been established as a biocompatible reaction for site-selective biomolecular labeling and imaging. During the reaction between CBT and aminothiols, we resolved two transient intermediates, the thioimidate and the cyclic precursor of the thiazoline product, and determined the rate constants associated with the stepwise condensation, thereby providing critical information for a variety of applications, including the covalent inhibition of protein targets and dynamic combinatorial chemistry.

Lipid-Bilayer-Supported 3D Printing of Human Cerebral Cortex Cells Reveals Developmental Interactions.

Current understanding of human brain development is rudimentary due to suboptimal in vitro and animal models. In particular, how initial cell positions impact subsequent human cortical development is unclear because experimental spatial control of cortical cell arrangement is technically challenging. 3D cell printing provides a rapid customized approach for patterning. However, it has relied on materials that do not represent the extracellular matrix (ECM) of brain tissue. Therefore, in the present work, a lipid-bilayer-supported printing technique is developed to 3D print human cortical cells in the soft, biocompatible ECM, Matrigel. Printed human neural stem cells (hNSCs) show high viability, neural differentiation, and the formation of functional, stimulus-responsive neural networks. By using prepatterned arrangements of neurons and astrocytes, it is found that hNSC process outgrowth and migration into cell-free matrix and into astrocyte-containing matrix are similar in extent. However, astrocytes enhance the later developmental event of axon bundling. Both young and mature neurons migrate into compartments containing astrocytes; in contrast, astrocytes do not migrate into neuronal domains signifying nonreciprocal chemorepulsion. Therefore, precise prepatterning by 3D printing allows the construction of natural and unnatural patterns that yield important insights into human cerebral cortex development.

Sampled-data observer-based anti-windup control for singularly perturbed systems with actuator saturation.

In this paper, the problem of sampled-data observer-based anti-windup (AW) control for singularly perturbed systems with actuator saturation is considered. A sampled-data observer-based AW controller consisting of a sampled-data observer, controller and AW compensator is proposed for the first time. Based on an ε-dependent Lyapunov-Krasovskii functional and linear matrix inequalities, the three components of sampled-data observer-based AW controller are designed simultaneously, which can reduce the conservatism. Furthermore, a convex optimization algorithm is formulated to obtain a desired stability bound and enlarge the basin of attraction at the same time. Finally, examples are provided to demonstrate the effectiveness and merits of the obtained results.

Dialdehydes lead to exceptionally fast bioconjugations at neutral pH by virtue of a cyclic intermediate.

One of the open challenges in chemical biology is to identify reactions that proceed with large rate constants at neutral pH values. As shown here, dialdehydes react with O-alkylhydroxylamines at rates of 500 M(-1) s(-1) at neutral pH values in the absence of catalysts. The key to these conjugations is an unusually stable cyclic intermediate, which ultimately undergoes dehydration to yield an oxime. The scope and limitations of the method are outlined, as well as its application in bioconjugation and a mechanistic interpretation that will facilitate further developments of reactions with alkylhydroxylamines at low substrate concentrations.

A class of 5-nitro-2-furancarboxylamides with potent trypanocidal activity against Trypanosoma brucei in vitro.

Recently, the World Health Organization approved the nifurtimox-eflornithine combination therapy for the treatment of human African trypanosomiasis, renewing interest in nitroheterocycle therapies for this and associated diseases. In this study, we have synthesized a series of novel 5-nitro-2-furancarboxylamides that show potent trypanocidal activity, ∼1000-fold more potent than nifurtimox against in vitro Trypanosoma brucei with very low cytotoxicity against human HeLa cells. More importantly, the most potent analogue showed very limited cross-resistance to nifurtimox-resistant cells and vice versa. This implies that our novel, relatively easy to synthesize and therefore cheap, 5-nitro-2-furancarboxylamides are targeting a different, but still essential, biochemical process to those targeted by nifurtimox or its metabolites in the parasites. The significant increase in potency (smaller dose probably required) has the potential for greatly reducing unwanted side effects and also reducing the likelihood of drug resistance. Collectively, these findings have important implications for the future therapeutic treatment of African sleeping sickness.

The synthesis of melohenine B and a related natural product.

A concise synthesis of melohenine B and O-ethyl-14-epimelohenine B, from eburnamonine, was achieved via a biomimetic diastereoselective singlet oxygen-mediated oxidative cleavage of the indole C2-C7 bond. These studies enabled the assignment of the absolute configuration of the natural products. In line with a proposed biosynthetic pathway, the resulting nine-membered ring containing products could be converted to the corresponding quinolones.

ALDH2 mediates 5-nitrofuran activity in multiple species.

Understanding how drugs work in vivo is critical for drug design and for maximizing the potential of currently available drugs. 5-nitrofurans are a class of prodrugs widely used to treat bacterial and trypanosome infections, but despite relative specificity, 5-nitrofurans often cause serious toxic side effects in people. Here, we use yeast and zebrafish, as well as human in vitro systems, to assess the biological activity of 5-nitrofurans, and we identify a conserved interaction between aldehyde dehydrogenase (ALDH) 2 and 5-nitrofurans across these species. In addition, we show that the activity of nifurtimox, a 5-nitrofuran anti-trypanosome prodrug, is dependent on zebrafish Aldh2 and is a substrate for human ALDH2. This study reveals a conserved and biologically relevant ALDH2-5-nitrofuran interaction that may have important implications for managing the toxicity of 5-nitrofuran treatment.

Digital video steganalysis using motion vector recovery-based features.

As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.

The G401D mutation of OPA1 causes autosomal dominant optic atrophy and hearing loss in a Chinese family.

OBJECTIVE: To describe the clinical and genetic characteristics of a Chinese family affected with optic atrophy 1 (OPA1). METHODS: Linkage analysis and DNA sequencing as well as PCR/restriction fragment length polymorphism (RFLP) analysis were performed to identify the disease-causing mutation. RESULTS: A missense mutation, G401D in the OPA1 gene was identified, and the patients demonstrate inherited syndrome of optic atrophy and hearing loss. CONCLUSION: The present study demonstrates that a mutation in the OPA1 gene can cause optic atrophy in Chinese patients, and supports the notion that OPA1 mutation may lead to OPA1 combined with hearing loss.