Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.

Objective.Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring its quality, insufficient training data often leads to overfitting and inadequate generalization capabilities of deep learning-based classification networks. Therefore, we propose a novel data augmentation method and deep learning classification model to enhance the decoding performance of MI-EEG further.Approach.The raw EEG signals were transformed into the time-frequency maps as the input to the model by continuous wavelet transform. An improved Wasserstein generative adversarial network with gradient penalty data augmentation method was proposed, effectively expanding the dataset used for model training. Additionally, a concise and efficient deep learning model was designed to improve decoding performance further.Main results.It has been demonstrated through validation by multiple data evaluation methods that the proposed generative network can generate more realistic data. Experimental results on the BCI Competition IV 2a and 2b datasets and the actual collected dataset show that classification accuracies are 83.4%, 89.1% and 73.3%, and Kappa values are 0.779, 0.782 and 0.644, respectively. The results indicate that the proposed model outperforms state-of-the-art methods.Significance.Experimental results demonstrate that this method effectively enhances MI-EEG data, mitigates overfitting in classification networks, improves MI classification accuracy, and holds positive implications for MI tasks.

An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis.

Precise diagnostic biomarkers of anticitrullination protein antibody (ACPA)-negative and early-stage RA are still to be improved. We aimed to screen autoantibodies in ACPA-negative patients and evaluated their diagnostic performance. The human genome-wide protein arrays (HuProt arrays) were used to define specific autoantibodies from the sera of 182 RA patients and 261 disease and healthy controls. Statistical analysis was performed with SPSS 17.0. In Phase I study, 51 out of 19,275 recombinant proteins covering the whole human genome were selected. In Phase II validation study, anti-ANAPC15 (anaphase promoting complex subunit 15) exhibited 41.8% sensitivity and 91.5% specificity among total RA patients. There were five autoantibodies increased in ACPA-negative RA, including anti-ANAPC15, anti-LSP1, anti-APBB1, anti-parathymosin, and anti-UBL7. Anti-parathymosin showed the highest prevalence of 46.2% (p = 0.016) in ACPA-negative early stage (<2 years) RA. To further improve the diagnostic efficacy, a prediction model was constructed with 44 autoantibodies. With increased threshold for RA calling, the specificity of the model is 90.8%, while the sensitivity is 66.1% (87.8% in ACPA-positive RA and 23.8% in ACPA-negative RA) in independent testing patients. Therefore, HuProt arrays identified RA-associated autoantibodies that might become possible diagnostic markers, especially in early stage ACPA-negative RA.

Limosilactobacillus fermentum HNU312 alleviates lipid accumulation and inflammation induced by a high-fat diet: improves lipid metabolism pathways and increases short-chain fatty acids in the gut microbiome.

A high-fat diet can cause health problems, such as hyperlipidemia, obesity, cardiovascular disease, and metabolic disorders. Dietary supplementation with beneficial microbes might reduce the detrimental effects of a high-fat diet by modulating the gut microbiome, metabolic pathways and metabolites. This study assessed the effects of Limosilactobacillus fermentum HNU312 (L. fermentum HNU312) on blood lipid levels, fat accumulation, inflammation and the gut microbiome in mice on a high-fat diet. The results indicate that L. fermentum HNU312 supplementation to high-fat diet-fed mice led to decreases of 7.52% in the final body weight, 22.30% in total triglyceride, 24.87% in total cholesterol, and 27.3% in low-density lipoprotein cholesterol. Furthermore, the addition of L. fermentum HNU312 significantly reduced the fat accumulation in the liver and adipose tissue by 18.99% and 32.55%, respectively, and decreased chronic inflammation induced by a high-fat diet. Further analysis of the gut microbiome revealed that on the one hand, L. fermentum HNU312 changed the structure of the intestinal microbiota, increased the abundance of beneficial intestinal bacteria related to lipid metabolism, and reversed the enrichment of lipid-related metabolic pathways. On the other hand, L. fermentum HNU312 increased the production of short-chain fatty acids, which can reduce liver inflammation and chronic inflammation induced by a high-fat diet. In summary, by regulating gut microbiota, L. fermentum HNU312 improved lipid metabolism pathways and increased short-chain fatty acids, which reduced body weight, blood lipids, fat accumulation and chronic inflammation caused by high-fat diets. Therefore, L. fermentum HNU312 could be a good candidate probiotic for ameliorating metabolic syndrome.

Rapid diagnosis of celiac disease based on plasma Raman spectroscopy combined with deep learning.

Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small intestine, ulcerative jejunitis, and enteritis, ultimately causing severe malnutrition. Therefore, an effective and rapid differentiation between healthy individuals and those with celiac disease is crucial for early diagnosis and treatment. This study utilizes Raman spectroscopy combined with deep learning models to achieve a non-invasive, rapid, and accurate diagnostic method for celiac disease and healthy controls. A total of 59 plasma samples, comprising 29 celiac disease cases and 30 healthy controls, were collected for experimental purposes. Convolutional Neural Network (CNN), Multi-Scale Convolutional Neural Network (MCNN), Residual Network (ResNet), and Deep Residual Shrinkage Network (DRSN) classification models were employed. The accuracy rates for these models were found to be 86.67%, 90.76%, 86.67% and 95.00%, respectively. Comparative validation results revealed that the DRSN model exhibited the best performance, with an AUC value and accuracy of 97.60% and 95%, respectively. This confirms the superiority of Raman spectroscopy combined with deep learning in the diagnosis of celiac disease.

LC-MS/MS-based chemical profiling of water extracts of Moringa oleifera leaves and pharmacokinetics of their major constituents in rat plasma.

Moringa oleifera leaves (MOL) are native to India and have high biological activities. To better understand the basic pharmacodynamic materials, the chemical components in MOL and their pharmacokinetic properties were studied and quantitated using UPLC-Q-Exactive Orbitrap-MS. Forty-two compounds were identified, including phenolic acids and their derivatives, flavonoids, isothiocyanates, nucleosides, alkaloids, and other compounds. Two phenolic acids and six flavonoids were studied for their pharmacokinetic properties using UHPLC-MS/MS. Precision, accuracy, stability, matrix effects, and extraction recovery were verified. All substances that were measured reached their maximum within 0.5 h. Vicenin-2 had a high peak concentration and bioavailability. Kaempferol-3-O-rutinoside had a longer biological half-life than other components. The results from this study provide the data basis for subsequent comprehensive qualitative evaluation and potential MOL use in clinical applications.

Precision targeting in oncology: The future of conjugated drugs.

Coupled drugs, especially antibody-coupled drugs (ADCs), are a hot topic in oncology. As the development of ADCs has progressed, different coupling modes have emerged, inspired by their structural design have emerged. Technological advances have led to interweaving and collision of old and new concepts of coupled drugs, and have even challenged the concepts and techniques of coupled drugs at this stage. For example, antibody-oligonucleotide conjugates are a new class of chimeric biomolecules synthesized by coupling oligonucleotides with monoclonal antibodies through linkers, offering precise targeting and improved pharmacokinetic properties. This study aimed to elucidate the mechanism of action of coupled drugs and their current development status in antitumor therapy to provide better strategies for antitumor therapy.

Nonpathogenic E. coli engineered to surface display cytokines as a new platform for immunotherapy.

Given the safety, tumor tropism, and ease of genetic manipulation in non-pathogenic Escherichia coli (E. coli), we designed a novel approach to deliver biologics to overcome poor trafficking and exhaustion of immune cells in the tumor microenvironment, via the surface display of key immune-activating cytokines on the outer membrane of E. coli K-12 DH5α. Bacteria expressing murine decoy-resistant IL18 mutein (DR18) induced robust CD8+ T and NK cell-dependent immune responses leading to dramatic tumor control, extending survival, and curing a significant proportion of immune-competent mice with colorectal carcinoma and melanoma. The engineered bacteria demonstrated tumor tropism, while the abscopal and recall responses suggested epitope spreading and induction of immunologic memory. E. coli K-12 DH5α engineered to display human DR18 potently activated mesothelin-targeting CAR NK cells and safely enhanced their trafficking into the tumors, leading to improved control and survival in xenograft mice bearing mesothelioma tumor cells, otherwise resistant to NK cells. Gene expression analysis of the bacteria-primed CAR NK cells showed enhanced TNFα signaling via NFkB and upregulation of multiple activation markers. Our novel live bacteria-based immunotherapeutic platform safely and effectively induces potent anti-tumor responses in otherwise hard-to-treat solid tumors, motivating further evaluation of this approach in the clinic.

EvHandPose: Event-Based 3D Hand Pose Estimation With Sparse Supervision.

Event camera shows great potential in 3D hand pose estimation, especially addressing the challenges of fast motion and high dynamic range in a low-power way. However, due to the asynchronous differential imaging mechanism, it is challenging to design event representation to encode hand motion information especially when the hands are not moving (causing motion ambiguity), and it is infeasible to fully annotate the temporally dense event stream. In this paper, we propose EvHandPose with novel hand flow representations in Event-to-Pose module for accurate hand pose estimation and alleviating the motion ambiguity issue. To solve the problem under sparse annotation, we design contrast maximization and hand-edge constraints in Pose-to-IWE (Image with Warped Events) module and formulate EvHandPose in a weakly-supervision framework. We further build EvRealHands, the first large-scale real-world event-based hand pose dataset on several challenging scenes to bridge the real-synthetic domain gap. Experiments on EvRealHands demonstrate that EvHandPose outperforms previous event-based methods under all evaluation scenes, achieves accurate and stable hand pose estimation with high temporal resolution in fast motion and strong light scenes compared with RGB-based methods, generalizes well to outdoor scenes and another type of event camera, and shows the potential for the hand gesture recognition task.

FAM20A is a golgi-localized Type II transmembrane protein.

Family with sequence similarity 20, member A (FAM20A) is a pseudo-kinase in the secretory pathway and is essential for enamel formation in humans. Here we examine if FAM20A is a membrane-associated protein. We show that the full-length FAM20A can be purified from HEK293 cells transfected with a FAM20A-expresing construct. Further, it is only found in the membrane fraction, but not in the soluble fraction, of cell lysate. Consistently, it is not secreted out of the expressing cells. Moreover, it is co-localized with GM130, a cis-Golgi network marker, and membrane topology analysis indicates that it has its C-terminus oriented towards the lumen of the organelle. Our results support that FAM20A is a Type II transmembrane protein within the secretory compartments.

Enhancing the electric charge output in LiNbO3-based piezoelectric pressure sensors.

Lithium niobate (LiNbO3) single crystals are a kind of ferroelectric material with a high piezoelectric coefficient and Curie temperature, which is suitable for the preparation of piezoelectric pressure sensors. However, there is little research reporting on the use of LiNbO3 single crystals to prepare piezoelectric pressure sensors. Therefore, in this paper, LiNbO3 was used to prepare piezoelectric pressure sensors to study the feasibility of using LiNbO3 single crystals as a sensitive material for piezoelectric pressure sensors. In addition, chemical mechanical polishing (CMP) technology was used to prepare LiNbO3 crystals with different thicknesses to study the influence of these LiNbO3 crystals on the electric charge output of the sensors. The results showed that the sensitivity of a 300 µm sample (0.218 mV kPa-1) was about 1.23 times that of a 500 µm sample (0.160 mV kPa-1). Low-temperature polymer heterogeneous integration and oxygen plasma activation technologies were used to realize the heterogeneous integration of LiNbO3 and silicon to prepare piezoelectric pressure sensors, which could significantly improve the sensitivity of the sensor by approximately 16.06 times (2.569 mV kPa-1) that of the original sample (0.160 mV kPa-1) due to an appropriate residual stress that did not shatter LiNbO3 or silicon, thus providing a possible method for integrating piezoelectric pressure sensors and integrated circuits.

What can be done to protect toddlers from air pollution: Current evidence.

PROBLEM: Toddlers are more prone to exposure to widely distributed air pollution and to health damage from it. However, systematic summaries of evidence on protective behaviors against air pollution for toddlers are lacking. OBJECTIVE: To identify currently available evidence on protective behaviors against air pollution for toddlers. METHODS: The literature retrieval was performed in selected databases, limited from 2002 to 2022. Studies meeting the following criteria were included and praised: 1) clinical practice guideline, systematic review, expert consensus, recommended practice, randomized control test (RCT) or cohort study published in Chinese or English; 2) studies reporting effects of protective behaviors against air pollution on toddlers' health outcomes or providing recommendation on these behaviors. The evidence in the included studies was extracted, synthesized and graded for evidence summary. RESULTS: Studies (N = 19) were used for evidence summary development and 35 pieces of best evidence were synthesized, which were divided into three categories, including "avoiding or reducing air pollution generation", "removing existing air pollution", and "avoiding or reducing exposure to existing air pollution". CONCLUSIONS: More evidence is needed to identify protective measures against outdoor air pollution and tobacco smoke. Research in the future should focus on the safety, effectiveness and feasibility of universal measures implemented in toddlers, and try to develop protective measures specific to toddlers which highlight their special nature. IMPLICATIONS: The results of this study can help pediatric nurses provide individualized advice and assistance for toddlers and their families, and conduct research on the effectiveness of toddler-targeting protective behaviors more efficiently.

Screening the components in multi-biological samples and the comparative pharmacokinetic study in healthy and depression model rats of Suan-Zao-Ren decoction combined with a network pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Suanzaoren Decoction (SZRD) is a classic traditional Chinese prescription, which has been commonly used for treating insomnia, depression and other nerve system diseases for a long time. AIM OF THIS STUDY: The present study aimed to explore the metabolic profiles in multi-biological samples and pharmacokinetic mechanism between healthy and depression model rats combined with a network pharmacology approach after administration of SZRD. MATERIALS AND METHODS: In our study, an ultra-high performance liquid chromatography (UPLC)-Q-Exactive Orbitrap Mass Spectrometry method was firstly used to study the prototype components and metabolites of SZRD in plasma, brain, urine, and feces between healthy and depressed rats. The possible metabolic pathways were also speculated. Then a network pharmacological study was conducted on the components in the plasma of model rats. According to the above components screened by network pharmacology and the other reported representative active components, the comparative pharmacokinetic study was established for the simultaneous determination of mangiferin, spinosin, ferulic acid, liquiritin, formononetin. magnoflorine and isoliquiritin between healthy and depression model rats. Finally, molecular docking was used to validate the binding affinity between key potential targets and active components in pharmacokinetics. RESULTS: A total of 115 components were identified in healthy rats, and 101 components were identified in model rats. The prototype components and metabolites in plasma, brain, urine, and feces were also distinguished. The main metabolic pathways included phase I and phase II metabolic reactions, such as dehydrogenation, oxidation, hydroxylation, gluconaldehyde conjugation, glutathione conjugation and so on. These results provided a basis for the further study of antidepressive pharmacokinetic and pharmacological action in SZRD. Then, according to the degree value of network pharmacological study, it was predicted that 10 components and 10 core targets, which involved in the critical pathways such as neuroactive ligand-receptor interaction, cyclic adenosine monophosphate (cAMP) signaling pathway, serotonergic synapse, phosphatidylinositol-3 kinase (PI3K)-Akt signaling pathway, etc. Finally, the established pharmacokinetic method was successfully applied to compare the pharmacokinetic behavior of these 7 active components in plasma of healthy and depressed rats after oral administration of SZRD. It showed that except magnoflorine, the pharmacokinetic parameters of each component were different between healthy and depressed rats. Molecular docking analysis also indicated that the active compounds in pharmacokinetics could bind tightly to the key targets of network pharmacological study. CONCLUSION: This study may provide important information for studying the action mechanism of SZRD in treating depression.

Voluntary wheel running prevents formation of membrane attack complexes and myelin degradation after peripheral nerve injury.

Regular aerobic activity is associated with a reduced risk of chronic pain in humans and rodents. Our previous studies in rodents have shown that prior voluntary wheel running can normalize redox signaling at the site of peripheral nerve injury, attenuating subsequent neuropathic pain. However, the full extent of neuroprotection offered by voluntary wheel running after peripheral nerve injury is unknown. Here, we show that six weeks of voluntary wheel running prior to chronic constriction injury (CCI) reduced the terminal complement membrane attack complex (MAC) at the sciatic nerve injury site. This was associated with increased expression of the MAC inhibitor CD59. The levels of upstream complement components (C3) and their inhibitors (CD55, CR1 and CFH) were altered by CCI, but not increased by voluntary wheel running. Since MAC can degrade myelin, which in turn contributes to neuropathic pain, we evaluated myelin integrity at the sciatic nerve injury site. We found that the loss of myelinated fibers and decreased myelin protein which occurs in sedentary rats following CCI was not observed in rats with prior running. Substitution of prior voluntary wheel running with exogenous CD59 also attenuated mechanical allodynia and reduced MAC deposition at the nerve injury site, pointing to CD59 as a critical effector of the neuroprotective and antinociceptive actions of prior voluntary wheel running. This study links attenuation of neuropathic pain by prior voluntary wheel running with inhibition of MAC and preservation of myelin integrity at the sciatic nerve injury site.

Short-term Exposure to Air Pollution and the Incidence and Mortality of Stroke: A Meta-Analysis.

BACKGROUND: The relationship between short-term exposure to various air pollutants [particulate matter <10 µm (PM10), particulate matter <2.5 µm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide, and ozone (O3)] and the incidence and mortality of stroke remain unclear. REVIEW SUMMARY: We conducted a comprehensive search across databases, including PubMed, Web of Science, and others. A random-effects model was employed to estimate the odds ratios (OR) and their 95% CIs. Short-term exposure to PM10, PM2.5, NO2, SO2, and O3 was associated with increased stroke incidence [per 10 µg/m3 increase in PM2.5: OR = 1.005 (95% CI: 1.004-1.007), per 10 µg/m3 increase in PM10: OR = 1.006 (95% CI: 1.004-1.009), per 10 µg/m3 increase in SO2: OR = 1.034 (95% CI: 1.020-1.048), per 10 µg/m3 increase in NO2: OR = 1.029 (95% CI: 1.015-1.043), and O3 for per 10 µg/m3 increase: OR: 1.006 (95% CI: 1.004-1.007)]. In addition, short-term exposure to PM2.5, PM10, SO2, and NO2 was correlated with increased mortality from stroke [per 10 µg/m3 increase in PM2.5: OR = 1.010 (95% CI: 1.006-1.013), per 10 µg/m3 increase in PM10: OR = 1.004 (95% CI: 1.003-1.006), per 10 µg/m3 increase in SO2: OR = 1.013 (95% CI: 1.007-1.019) and per 10 µg/m3 increase in NO2: OR = 1.012 (95% CI: 1.008-1.015)]. CONCLUSION: Reducing outdoor air pollutant levels may yield a favorable outcome in reducing the incidence and mortality associated with strokes.

Engineered Bacillus subtilis as oral probiotics to target circulating lactic acid.

Lactic acid or lactate, a key byproduct of anaerobic glycolysis, plays pivotal roles in routine metabolism. An increase in lactic acid is observed in various pathological conditions such as cancer, diabetes, genetic mitochondrial disease, and aging. While several groups have proposed small molecule inhibitors to reduce circulating lactic acid, there are few clinically relevant ways to manage acute or chronic elevations in lactic acid in patients. In addition, recent evidence suggests that lactic acid exchanges between the gut, blood, and peripheral tissues, and professional marathon runners harbor specific gut microbial species that more efficiently metabolize lactic acid. Inspired by these findings, this work sought to engineer probiotic B. subtilis strains to express lactate oxidase that could increase circulating lactic acid catabolism after delivery to the gut. After optimization, oral administration of engineered B. subtilis to the gut of mice reduced the elevation in blood lactic acid levels after exogenous lactic acid challenge without affecting normal gut microbiota composition, inflammation or liver enzymes. Taken together, through the oral delivery of engineered probiotics to the gastrointestinal tract, our proof-of-concept study offers a new opportunity to therapeutically target diseases where blood lactic acid is elevated, and provides a new approach to "knocking down" metabolites to help understand the roles of metabolites in host physiological and pathological processes.

Engineering Tripartite Gene Editing Machinery for Highly Efficient Non-Viral Targeted Genome Integration.

Non-viral DNA donor template has been widely used for targeted genomic integration by homologous recombination (HR). This process has become more efficient with RNA guided endonuclease editor system such as CRISPR/Cas9. Circular single stranded DNA (cssDNA) has been harnessed previously as a genome engineering catalyst (GATALYST) for efficient and safe targeted gene knock-in. Here we developed enGager, a system with enhanced GATALYST associated genome editor, comprising a set of novel genome editors in which the integration efficiency of a circular single-stranded (css) donor DNA is elevated by directly tethering of the cssDNA to a nuclear-localized Cas9 fused with ssDNA binding peptides. Improvements in site-directed genomic integration and expression of a knocked-in DNA encoding GFP were observed at multiple genomic loci in multiple cell lines. The enhancement of integration efficiency, compared to unfused Cas9 editors, ranges from 1.5- to more than 6-fold, with the enhancement most pronounced for transgenes of > 4Kb in length in primary cells. enGager-enhanced genome integration prefers ssDNA donors which, unlike traditional dsDNA donors, are not concatemerized or rearranged prior to and during integration Using an enGager fused to an optimized cssDNA binding peptide, exceptionally efficient, targeted integration of the chimeric antigen receptor (CAR) transgene was achieved in 33% of primary human T cells. Enhanced anti-tumor function of these CAR-T primary cells demonstrated the functional competence of the transgenes. The 'tripartite editors with ssDNA optimized genome engineering' (TESOGENASE™) systems help address the efficacy needs for therapeutic gene modification while avoiding the safety and payload size limitations of viral vectors currently used for CAR-T engineering.

Correction: Silver complexes with substituted terpyridines as promising anticancer metallodrugs and their crystal structure, photoluminescence, and DNA interactions.

Correction for 'Silver complexes with substituted terpyridines as promising anticancer metallodrugs and their crystal structure, photoluminescence, and DNA interactions' by Jiahe Li et al., Dalton Trans., 2023, 52, 9607-9621, https://doi.org/10.1039/D2DT03463H.

Inverse design of chiral functional films by a robotic AI-guided system.

Artificial chiral materials and nanostructures with strong and tuneable chiroptical activities, including sign, magnitude, and wavelength distribution, are useful owing to their potential applications in chiral sensing, enantioselective catalysis, and chiroptical devices. Thus, the inverse design and customized manufacturing of these materials is highly desirable. Here, we use an artificial intelligence (AI) guided robotic chemist to accurately predict chiroptical activities from the experimental absorption spectra and structure/process parameters, and generate chiral films with targeted chiroptical activities across the full visible spectrum. The robotic AI-chemist carries out the entire process, including chiral film construction, characterization, and testing. A machine learned reverse design model using spectrum embedded descriptors is developed to predict optimal structure/process parameters for any targeted chiroptical property. A series of chiral films with a dissymmetry factor as high as 1.9 (gabs ~ 1.9) are identified out of more than 100 million possible structures, and their feasible application in circular polarization-selective color filters for multiplex laser display and switchable circularly polarized (CP) luminescence is demonstrated. Our findings not only provide chiral films with the highest reported chiroptical activity, but also have great fundamental value for the inverse design of chiroptical materials.

TESOGENASE, An Engineered Nuclease Editor for Enhanced Targeted Genome Integration.

Non-viral DNA donor template has been widely used for targeted genomic integration by homologous recombination (HR). This process has become more efficient with RNA guided endonuclease editor system such as CRISPR/Cas9. Circular single stranded DNA (cssDNA) has been harnessed previously as a g enome engineering c atalyst (GATALYST) for efficient and safe targeted gene knock-in. However, the engineering efficiency is bottlenecked by the nucleoplasm trafficking and genomic tethering of cssDNA donor, especially for extra-large transgene integration. Here we developed enGager, en hanced G ATALYST a ssociated g enome e ditor system by fusion of nucleus localization signal (NLS) peptide tagged Cas9 with various single stranded DNA binding protein modules through a GFP reporter Knock-in screening. The enGager system assembles an integrative genome integration machinery by forming tripartite complex for engineered nuclease editors, sgRNA and ssDNA donors, thereby facilitate the nucleus trafficking of DNA donors and increase their active local concentration at the targeted genomic site. When applied for genome integration with cssDNA donor templates to diverse genomic loci in various cell types, these enGagers outperform unfused editors. The enhancement of integration efficiency ranges from 1.5- to more than 6-fold, with the effect being more prominent for > 4Kb transgene knock-in in primary cells. We further demonstrated that enGager mediated enhancement for genome integration is ssDNA, but less dsDNA dependent. Using one of the mini-enGagers, we demonstrated large chimeric antigen receptor (CAR) transgene integration in primary T cells with exceptional efficiency and anti-tumor function. These tripartite e ditors with s sDNA o ptimized g enome en gineering system (TESOGENASE TM ) add a set of novel endonuclease editors into the gene-editing toolbox for potential cell and gene therapeutic development based on ssDNA mediated non-viral genome engineering. Highlight: A reporter Knock-in screening establishes enGager system to identify TESOGENASE editor to improving ssDNA mediated genome integrationMini-TESOGENASEs developed by fusing Cas9 nuclease with novel ssDNA binding motifsmRNA mini-TESOGENASEs enhance targeted genome integration via various non-viral delivery approachesEfficient functional CAR-T cell engineering by mini-TESOGENASE.

3D Printing of Interpenetrating Network Flexible Hydrogels with Enhancement of Adhesiveness.

3D printing of hydrogels has been widely explored for the rapid fabrication of complex soft structures and devices. However, using 3D printing to customize hydrogels with both adequate adhesiveness and toughness remains a fundamental challenge. Here, we demonstrate mussel-inspired (polydopamine) PDA hydrogel through the incorporation of a classical double network (2-acrylamido-2-methylpropanesulfonic acid) PAMPS/(polyacrylamide) PAAm to achieve simultaneously tailored adhesiveness, toughness, and biocompatibility and validate the 3D printability of such a hydrogel into customized architectures. The strategy of combining PDA with PAMPS/PAAm hydrogels leads to favorable adhesion on either hydrophilic or hydrophobic surfaces. The hydrogel also shows excellent flexibility, which is attributed to the reversible cross-linking of PDA and PAMPS, together with the long-chain PAAm cross-linking network. Among them, the reversible cross-linking of PDA and PAMPS is capable of dissipating mechanical energy under deformation. Meanwhile, the long-chain PAAm network contributes to maintaining a high deformation capability. We establish a theoretical framework to quantify the contribution of the interpenetrating networks to the overall toughness of the hydrogel, which also provides guidance for the rational design of materials with the desired properties. Our work manifests a new paradigm of printing adhesive, tough, and biocompatible interpenetrating network hydrogels to meet the requirements of broad potential applications in biomedical engineering, soft robotics, and intelligent and superabsorbent devices.