Targeted, programmable, and precise tandem duplication in the mammalian genome.

Tandem duplications are frequent structural variations of the genome and play important roles in genetic disease and cancer. However, interpreting the phenotypic consequences of tandem duplications remains challenging, in part owing to the lack of genetic tools to model such variations. Here, we developed a strategy, tandem duplication via prime editing (TD-PE), to create targeted, programmable, and precise tandem duplication in the mammalian genome. In this strategy, we design a pair of in trans prime editing guide RNAs (pegRNAs) for each targeted tandem duplication, which encode the same edits but prime the single-stranded DNA (ssDNA) extension in opposite directions. The reverse transcriptase (RT) template of each extension is designed homologous to the target region of the other single guide RNA (sgRNA) to promote the reannealing of the edited DNA strands and the duplication of the fragment in between. We showed that TD-PE produced robust and precise in situ tandem duplications of genomic fragments ranging from ∼50 bp to ∼10 kb, with a maximal efficiency up to 28.33%. By fine-tuning the pegRNAs, we achieved simultaneous targeted duplication and fragment insertion. Finally, we successfully produced multiple disease-relevant tandem duplications, showing the general utility of TD-PE in genetic research.

In Situ Fabrication of SnO2 Nanowalls for Robust Acetylene Sensing at Low Temperature.

Acetylene (C2 H2 ) monitoring in real time and online is essential for erasing transformer risks and guaranteeing normal equipment operation and operator safety. This study examines the direct fabrication of ultrathin SnO2 nanowalls on Ag-Pd substrates using a simple solvothermal method that doesn't demand the use of any additional motivators or templates. The thickness and shape of the nanowalls can be controlled by varying the cetyl trimethyl ammonium bromide (CTAB) concentration in the solvent. As observed, the gas sensor (SnO2 -3) fabricated by 2.4 g CTAB exhibits superior gas-sensing features. This is primarily due to the hollow structure constructed by the arrangement of nanowalls, which delivers not only enough gas diffusion pathways but also enough reaction sites during the gas sensing processes. The findings suggest that low-cost SnO2 nanowalls created using a straightforward procedure could be taken into consideration as prospective candidates for use in industrial C2 H2 sensing applications.

Direct cellular reprogramming techniques for cardiovascular regenerative therapeutics.

Cardiovascular diseases remain a leading cause of hospitalization affecting approximately 38 million people worldwide. While pharmacological and revascularization techniques can improve the patient's survival and quality of life, they cannot help reversing myocardial infarction injury and heart failure. Direct reprogramming of somatic cells to cardiomyocyte and cardiac progenitor cells offers a new approach to cellular reprogramming and paves the way for translational regenerative medicine. Direct reprogramming can bypass the pluripotent stage with the potential advantage of non-immunogenic cell products, reduced carcinogenic risk, and no requirement for embryonic tissue. The process of directly reprogramming cardiac cells was first achieved through the overexpression of transcription factors such as GATA4, MEF2C, and TBX5. However, over the past decade, significant work has been focused on enhancing direct reprogramming using a mixture of transcription factors, microRNAs, and small molecules to achieve cardiac cell fate. This review discusses the evolution of direct reprogramming, recent progress in achieving efficient cardiac cell fate conversion, and describes the reprogramming mechanisms at a molecular level. We also explore various viral and non-viral delivery methods currently being used to aid in the delivery of reprogramming factors to improve efficiency. However, further studies will be needed to overcome molecular and epigenetic barriers to successfully achieve translational cardiac regenerative therapeutics.

Cuproptosis related gene PDHB is identified as a biomarker inversely associated with the progression of clear cell renal cell carcinoma.

BACKGROUND: Cuproptosis is a newly discovered programmed cell death dependent on mitochondrial respiratory disorder induced by copper overload. Pyruvate dehydrogenase E1 subunit beta (PDHB) is one of the cuproptosis genesand is a nuclear-encoded pyruvate dehydrogenase, which catalyzes the conversion of pyruvate to acetyl coenzyme A. However, the mechanism of PDHB in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: We used data from TCGA and GEO to assess the expression of PDHB in normal and tumor tissues. We further analyzed the relationship between PDHB and somatic mutations and immune infiltration. Finally, we preliminarily explored the impact of PDHB on ccRCC. RESULTS: The expression level of PDHB was lower in tumor tissue compared with normal tissue. Meanwhile, the expression level of PDHB was also lower in high-grade tumors than low-grade tumors. PDHB is positively correlated with prognosis in ccRCC. Furthermore, PDHB may be associated with decreased risk of VHL, PBRM1 and KDM5C mutations. In 786-O cells, copper chloride could promote the expression of cuproptosis genes (DLAT, PDHB and FDX1) and inhibit cell growth. Last but not least, we found that PDHB could inhibit the proliferation and migration of ccRCC cells. CONCLUSION: Our results demonstrated that PDHB could inhibit the proliferation, migration and invasion in ccRCC cells, which might be a prognostic predictor of ccRCC. Targeting this molecular might provide a new therapeutic strategy for patients with advanced ccRCC.

A new multimodality fusion classification approach to explore the uniqueness of schizophrenia and autism spectrum disorder.

Schizophrenia (SZ) and autism spectrum disorder (ASD) sharing overlapping symptoms have a long history of diagnostic confusion. It is unclear what their differences at a brain level are. Here, we propose a multimodality fusion classification approach to investigate their divergence in brain function and structure. Using brain functional network connectivity (FNC) calculated from resting-state fMRI data and gray matter volume (GMV) estimated from sMRI data, we classify the two disorders using the main data (335 SZ and 380 ASD patients) via an unbiased 10-fold cross-validation pipeline, and also validate the classification generalization ability on an independent cohort (120 SZ and 349 ASD patients). The classification accuracy reached up to 83.08% for the testing data and 72.10% for the independent data, significantly better than the results from using the single-modality features. The discriminative FNCs that were automatically selected primarily involved the sub-cortical, default mode, and visual domains. Interestingly, all discriminative FNCs relating to the default mode network showed an intermediate strength in healthy controls (HCs) between SZ and ASD patients. Their GMV differences were mainly driven by the frontal gyrus, temporal gyrus, and insula. Regarding these regions, the mean GMV of HC fell intermediate between that of SZ and ASD, and ASD showed the highest GMV. The middle frontal gyrus was associated with both functional and structural differences. In summary, our work reveals the unique neuroimaging characteristics of SZ and ASD that can achieve high and generalizable classification accuracy, supporting their potential as disorder-specific neural substrates of the two entwined disorders.

A Hierarchical Blockchain-Assisted Conditional Privacy-Preserving Authentication Scheme for Vehicular Ad Hoc Networks.

Through information sharing, vehicles can know the surrounding road condition information timely in Vehicular Adhoc Networks. To ensure the validity of these messages and the security of vehicles, the message authentication, privacy-preserving, and delay problems are three important issues. Although many conditional privacy-preserving authentication schemes have been proposed to ensure secure communication, there still exist some imperfections such as frequent interactions or unlinkability. From this, our paper proposes a novel hierarchical blockchain-assisted authentication scheme to solve these existing issues comprehensively. First, unlinkability is achieved by a dynamic key derivation algorithm. Second, the proposed scheme can reduce correlation processing delay, queuing delay, and deployment costs by adopting hierarchical Vehicle Fog Computing. Third, cross-region authentication is achieved by taking advantage of the properties of blockchain. In addition, we demonstrate our scheme can fulfill the security criteria of the Vehicular Adhoc Network by security analysis. Furthermore, the simulations are carried out to show its availability by using JAVA and NS-3. The findings reveal that the suggested method outperforms earlier schemes in terms of computation cost and communication cost. All in all, making the authentication scheme more efficient and concise is the focus of our future research.

Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks.

The working⁻sleeping cycle strategy used for sensor nodes with limited power supply in wireless sensor networks can effectively save their energy, but also causes opportunistic node connections due to the intermittent communication mode, which can affect the reliability of data transmission. To address this problem, a data collection scheme based on opportunistic node connections is proposed to achieve efficient data collection in a network with a mobile sink. In this scheme, the mobile sink first broadcasts a tag message to start a data collection period, and all nodes that receive this message will use the probe message to forward their own source information to the mobile sink. On receiving these probe messages, the mobile sink then constructs an opportunistic connection random graph by analyzing the source information included in them, and calculates the optimal path from itself to each node in this random graph, therefore a spanning tree could be generated with the mobile sink play as the root node, finally, it broadcasts this spanning tree so that each node could obtain an optimal path from itself to the mobile sink to forward the sensing data. In addition, a routing protocol that adapts to different nodes operating statuses is proposed to improve the reliability of data transmission. Simulation results show that the proposed scheme works better concerning the packet delivery rate, energy consumption and network lifetime.

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs.

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network's movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes' transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density.

Tracking Mobile Sinks via Analysis of Movement Angle Changes in WSNs.

Existing methods for tracking mobile sinks in Wireless Sensor Networks (WSNs) often incur considerable energy consumption and overhead. To address this issue, we propose a Detour-Aware Mobile Sink Tracking (DAMST) method via analysis of movement angle changes of mobile sinks, for collecting data in a low-overhead and energy efficient way. In the proposed method, while a mobile sink passes through a region, it appoints a specific node as a region agent to collect information of the whole region, and records nodes near or on its trajectory as footprints. If it needs information from the region agent in a future time it will construct an energy efficient path from the region agent to itself by calculating its own movement angles according to the footprints, as well as getting rid of detours by analyzing these movement angles. Finally, the performance of the tracking method is evaluated systematically under different trajectory patterns and footprint appointment intervals. The simulation results consolidate that DAMST has advantages in reducing energy consumption and data overhead.

Cardiomyocyte proliferation and regeneration in congenital heart disease.

Despite advances in prenatal screening and a notable decrease in mortality rates, congenital heart disease (CHD) remains the most prevalent congenital disorder in newborns globally. Current therapeutic surgical approaches face challenges due to the significant rise in complications and disabilities. Emerging cardiac regenerative therapies offer promising adjuncts for CHD treatment. One novel avenue involves investigating methods to stimulate cardiomyocyte proliferation. However, the mechanism of altered cardiomyocyte proliferation in CHD is not fully understood, and there are few feasible approaches to stimulate cardiomyocyte cell cycling for optimal healing in CHD patients. In this review, we explore recent progress in understanding genetic and epigenetic mechanisms underlying defective cardiomyocyte proliferation in CHD from development through birth. Targeting cell cycle pathways shows promise for enhancing cardiomyocyte cytokinesis, division, and regeneration to repair heart defects. Advancements in human disease modeling techniques, CRISPR-based genome and epigenome editing, and next-generation sequencing technologies will expedite the exploration of abnormal machinery governing cardiomyocyte differentiation, proliferation, and maturation across diverse genetic backgrounds of CHD. Ongoing studies on screening drugs that regulate cell cycling are poised to translate this nascent technology of enhancing cardiomyocyte proliferation into a new therapeutic paradigm for CHD surgical interventions.