The Protexin complex counters resection on stalled forks to promote homologous recombination and crosslink repair.

Protection of stalled replication forks is critical to genomic stability. Using genetic and proteomic analyses, we discovered the Protexin complex containing the ssDNA binding protein SCAI and the DNA polymerase REV3. Protexin is required specifically for protecting forks stalled by nucleotide depletion, fork barriers, fragile sites, and DNA inter-strand crosslinks (ICLs), where it promotes homologous recombination and repair. Protexin loss leads to ssDNA accumulation and profound genomic instability in response to ICLs. Protexin interacts with RNA POL2, and both oppose EXO1's resection of DNA on forks remodeled by the FANCM translocase activity. This pathway acts independently of BRCA/RAD51-mediated fork stabilization, and cells with BRCA2 mutations were dependent on SCAI for survival. These data suggest that Protexin and its associated factors establish a new fork protection pathway that counteracts fork resection in part through a REV3 polymerase-dependent resynthesis mechanism of excised DNA, particularly at ICL stalled forks.

In situ architecture and membrane fusion of SARS-CoV-2 Delta variant.

Among the current five Variants of Concern, infections caused by SARS-CoV-2 B.1.617.2 (Delta) variant are often associated with the greatest severity. Despite recent advances on the molecular basis of elevated pathogenicity using recombinant proteins, the architecture of intact Delta virions remains veiled. Moreover, pieces of molecular evidence for the detailed mechanism of S-mediated membrane fusion are missing. Here, we showed the pleomorphic nature of Delta virions from electron beam inactivated samples and reported the in situ structure and distribution of S on the authentic Delta variant. We also captured the virus-virus fusion events, which provided pieces of structural evidence for Delta's attenuated dependency on cellular factors for fusion activation, and proposed a model of S-mediated membrane fusion. Besides, site-specific glycan analysis revealed increased oligomannose-type glycosylation of native Delta S than that of the WT S. Together, these results disclose distinctive factors of Delta being the most virulent SARS-CoV-2 variant.

PIF1 helicase promotes break-induced replication in mammalian cells.

Break-induced replication (BIR) is a specialized homologous-recombination pathway for DNA double-strand break (DSB) repair, which often induces genome instability. In this study, we establish EGFP-based recombination reporters to systematically study BIR in mammalian cells and demonstrate an important role of human PIF1 helicase in promoting BIR. We show that at endonuclease cleavage sites, PIF1-dependent BIR is used for homology-initiated recombination requiring long track DNA synthesis, but not short track gene conversion (STGC). We also show that structure formation-prone AT-rich DNA sequences derived from common fragile sites (CFS-ATs) induce BIR upon replication stress and oncogenic stress, and PCNA-dependent loading of PIF1 onto collapsed/broken forks is critical for BIR activation. At broken replication forks, even STGC-mediated repair of double-ended DSBs depends on POLD3 and PIF1, revealing an unexpected mechanism of BIR activation upon replication stress that differs from the conventional BIR activation model requiring DSB end sensing at endonuclease-generated breaks. Furthermore, loss of PIF1 is synthetically lethal with loss of FANCM, which is involved in protecting CFS-ATs. The breast cancer-associated PIF1 mutant L319P is defective in BIR, suggesting a direct link of BIR to oncogenic processes.

Discovery of Hippo signaling as a regulator of CSPG4 expression and as a therapeutic target for Clostridioides difficile disease.

The signaling pathways and networks regulating expression of chondroitin sulfate proteoglycan 4 (CSPG4), a cancer-related protein that serves as a receptor for Clostridiodes difficile TcdB, are poorly defined. In this study, TcdB-resistant/CSPG4-negative HeLa cells were generated by exposure to increasing concentrations of the toxin. The cells that emerged (HeLa R5) lost expression of CSPG4 mRNA and were resistant to binding by TcdB. mRNA expression profiles paired with integrated pathway analysis correlated changes in the Hippo and estrogen signaling pathways with a CSPG4 decrease in HeLa R5 cells. Both signaling pathways altered CSPG4 expression when modulated chemically or through CRISPR-mediated deletion of key transcriptional regulators in the Hippo pathway. Based on the in vitro findings, we predicted and experimentally confirmed that a Hippo pathway inactivating drug (XMU-MP-1) provides protection from C. difficile disease in a mouse model. These results provide insights into key regulators of CSPG4 expression and identify a therapeutic for C. difficile disease.

Lanternarene-Based Self-Sorting Double-Network Hydrogels for Flexible Strain Sensors.

Conductive flexible hydrogels have attracted immense attentions recently due to their wide applications in wearable sensors. However, the poor mechanical properties of most conductive polymer limit their utilizations. Herein, a double network hydrogel is fabricated via a self-sorting process with cationic polyacrylamide as the first flexible network and the lantern[33]arene-based hydrogen organic framework nanofibers as the second rigid network. This hydrogel is endowed with good conductivity (0.25 S m-1) and mechanical properties, such as large Young's modulus (31.9 MPa), fracture elongation (487%) and toughness (6.97 MJ m-3). The stretchability of this hydrogel is greatly improved after the kirigami cutting, which makes it can be used as flexible strain sensor for monitoring human motions, such as bending of fingers, wrist and elbows. This study not only provides a valuable strategy for the construction of double network hydrogels by lanternarene, but also expands the application of the macrocycle hydrogels to flexible electronics.

Short-chain fatty acids: bridges between diet, gut microbiota, and health.

In recent years, gut microbiota has become a hot topic in the fields of medicine and life sciences. Short-chain fatty acids (SCFAs), the main metabolites of gut microbiota produced by microbial fermentation of dietary fiber, play a vital role in healthy and ill hosts. SCFAs regulate the process of metabolism, immune, and inflammation and have therapeutic effects on gastrointestinal and neurological disorders, as well as antitumor properties. This review summarized the production, distribution, and molecular mechanism of SCFAs, as well as their mechanisms of action in healthy and ill hosts. In addition, we also emphasized the negative effects of SCFAs, aiming to provide the public with a more comprehensive understanding of SCFAs.

Essential tremor is associated with reduced serum ceruloplasmin levels.

BACKGROUND: Essential tremor (ET), a prevalent movement disorder, has an elusive pathogenesis. A reduction in ceruloplasmin (Cp) levels can be found in some patients with ET. In addition, some studies have suggested an association between ET and neurodegeneration. As a ferroxidase, Cp is critical for iron metabolism, protecting against oxidative stress and neurodegeneration. Iron metabolism dysregulation, linked to ferroptosis, has implications in neurodegenerative diseases. Yet, research on Cp and ET remains limited. OBJECTIVES: This study aims to elucidate the relationship between ET and serum Cp levels. METHODS: We collected demographic and clinical data from 62 patients with ET satisfying the diagnostic criteria and compared these to data from 100 healthy controls. RESULTS: The median Cp levels in ET patients were 21.5 (18.8, 23.9) mg/dL, significantly lower than those in controls (23.1 [(20.7, 25.7) mg/dL; P = 0.006]). A reduction in Cp levels emerged as a risk factor for ET incidence (odds ratio (OR) = 0.873, 95% confidence interval (CI), 0.795, 0.959; P = 0.005). The area under the receiver operating characteristic (ROC) curve for serum Cp levels to predict the onset of ET was 0.629 (95% CI, 0.537-0.720; P = 0.006), and the optimal cut-off value for Cp levels was 19.5 mg/dL with a sensitivity of 91% and a specificity of 33.9%. CONCLUSION: Our analysis suggests that reduced Cp levels are associated with ET. We speculate that reduced Cp levels may be involved in the pathogenesis of ET, which requires further studies.

Intelligent Vehicle Path Planning Based on Optimized A* Algorithm.

With the rapid development of the intelligent driving technology, achieving accurate path planning for unmanned vehicles has become increasingly crucial. However, path planning algorithms face challenges when dealing with complex and ever-changing road conditions. In this paper, aiming at improving the accuracy and robustness of the generated path, a global programming algorithm based on optimization is proposed, while maintaining the efficiency of the traditional A* algorithm. Firstly, turning penalty function and obstacle raster coefficient are integrated into the search cost function to increase the adaptability and directionality of the search path to the map. Secondly, an efficient search strategy is proposed to solve the problem that trajectories will pass through sparse obstacles while reducing spatial complexity. Thirdly, a redundant node elimination strategy based on discrete smoothing optimization effectively reduces the total length of control points and paths, and greatly reduces the difficulty of subsequent trajectory optimization. Finally, the simulation results, based on real map rasterization, highlight the advanced performance of the path planning and the comparison among the baselines and the proposed strategy showcases that the optimized A* algorithm significantly enhances the security and rationality of the planned path. Notably, it reduces the number of traversed nodes by 84%, the total turning angle by 39%, and shortens the overall path length to a certain extent.

RBS and ABS Coordinated Control Strategy Based on Explicit Model Predictive Control.

During the braking process of electric vehicles, both the regenerative braking system (RBS) and anti-lock braking system (ABS) modulate the hydraulic braking force, leading to control conflict that impacts the effectiveness and real-time capability of coordinated control. Aiming to enhance the coordinated control effectiveness of RBS and ABS within the electro-hydraulic composite braking system, this paper proposes a coordinated control strategy based on explicit model predictive control (eMPC-CCS). Initially, a comprehensive braking control framework is established, combining offline adaptive control law generation, online optimized control law application, and state compensation to effectively coordinate braking force through the electro-hydraulic system. During offline processing, eMPC generates a real-time-oriented state feedback control law based on real-world micro trip segments, improving the adaptiveness of the braking strategy across different driving conditions. In the online implementation, the developed three-dimensional eMPC control laws, corresponding to current driving conditions, are invoked, thereby enhancing the potential for real-time braking strategy implementation. Moreover, the state error compensator is integrated into eMPC-CCS, yielding a state gain matrix that optimizes the vehicle braking status and ensures robustness across diverse braking conditions. Lastly, simulation evaluation and hardware-in-the-loop (HIL) testing manifest that the proposed eMPC-CCS effectively coordinates the regenerative and hydraulic braking systems, outperforming other CCSs in terms of braking energy recovery and real-time capability.

Combining a machine-learning derived 4-lncRNA signature with AFP and TNM stages in predicting early recurrence of hepatocellular carcinoma.

BACKGROUND: Near 70% of hepatocellular carcinoma (HCC) recurrence is early recurrence within 2-year post surgery. Long non-coding RNAs (lncRNAs) are intensively involved in HCC progression and serve as biomarkers for HCC prognosis. The aim of this study is to construct a lncRNA-based signature for predicting HCC early recurrence. METHODS: Data of RNA expression and associated clinical information were accessed from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database. Recurrence associated differentially expressed lncRNAs (DELncs) were determined by three DEG methods and two survival analyses methods. DELncs involved in the signature were selected by three machine learning methods and multivariate Cox analysis. Additionally, the signature was validated in a cohort of HCC patients from an external source. In order to gain insight into the biological functions of this signature, gene sets enrichment analyses, immune infiltration analyses, as well as immune and drug therapy prediction analyses were conducted. RESULTS: A 4-lncRNA signature consisting of AC108463.1, AF131217.1, CMB9-22P13.1, TMCC1-AS1 was constructed. Patients in the high-risk group showed significantly higher early recurrence rate compared to those in the low-risk group. Combination of the signature, AFP and TNM further improved the early HCC recurrence predictive performance. Several molecular pathways and gene sets associated with HCC pathogenesis are enriched in the high-risk group. Antitumor immune cells, such as activated B cell, type 1 T helper cell, natural killer cell and effective memory CD8 T cell are enriched in patients with low-risk HCCs. HCC patients in the low- and high-risk group had differential sensitivities to various antitumor drugs. Finally, predictive performance of this signature was validated in an external cohort of patients with HCC. CONCLUSION: Combined with TNM and AFP, the 4-lncRNA signature presents excellent predictability of HCC early recurrence.

Break-induced replication plays a prominent role in long-range repeat-mediated deletion.

Repetitive DNA sequences are often associated with chromosomal rearrangements in cancers. Conventionally, single-strand annealing (SSA) is thought to mediate homology-directed repair of double-strand breaks (DSBs) between two repeats, causing repeat-mediated deletion (RMD). In this report, we demonstrate that break-induced replication (BIR) is used predominantly over SSA in mammalian cells for mediating RMD, especially when repeats are far apart. We show that SSA becomes inefficient in mammalian cells when the distance between the DSBs and the repeats is increased to the 1-2 kb range, while BIR-mediated RMD (BIR/RMD) can act over a long distance (e.g., ~ 100-200 kb) when the DSB is close to one repeat. Importantly, oncogene expression potentiates BIR/RMD but not SSA, and BIR/RMD is used more frequently at single-ended DSBs formed at collapsed replication forks than at double-ended DSBs. In contrast to short-range SSA, H2AX is required for long-range BIR/RMD, and sequence divergence strongly suppresses BIR/RMD in a manner partially dependent on MSH2. Our finding that BIR/RMD has a more important role than SSA in mammalian cells has a significant impact on the understanding of repeat-mediated rearrangements associated with oncogenesis.

Characterization of oral bacterial and fungal microbiome in recovered COVID-19 patients.

COVID-19 has emerged as a global pandemic, challenging the world's economic and health systems. Human oral microbiota comprises the second largest microbial community after the gut microbiota and is closely related to respiratory tract infections; however, oral microbiomes of patients who have recovered from COVID-19 have not yet been thoroughly studied. Herein, we compared the oral bacterial and fungal microbiota after clearance of SARS-CoV-2 in 23 COVID-19 recovered patients to those of 29 healthy individuals. Our results showed that both bacterial and fungal diversity were nearly normalized in recovered patients. The relative abundance of some specific bacteria and fungi, primarily opportunistic pathogens, decreased in recovered patients (RPs), while the abundance of butyrate-producing organisms increased in these patients. Moreover, these differences were still present for some organisms at 12 months after recovery, indicating the need for long-term monitoring of COVID-19 patients after virus clearance.

Characterization of cross-reactive monoclonal antibodies against SARS-CoV-1 and SARS-CoV-2: Implication for rational design and development of pan-sarbecovirus vaccines and neutralizing antibodies.

Emergence of various circulating SARS-CoV-2 variants of concern (VOCs) promotes the identification of pan-sarbecovirus vaccines and broadly neutralizing antibodies (bNAbs). Here, to characterize monoclonal antibodies cross-reactive against both SARS-CoV-1 and SARS-CoV-2 and to search the criterion for bNAbs against all emerging SARS-CoV-2, we isolated several SARS-CoV-1-cross-reactive monoclonal antibodies (mAbs) from a wildtype SARS-CoV-2 convalescent donor. These antibodies showed broad binding capacity and cross-neutralizing potency against various SARS-CoV-2 VOCs, including B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta), but failed to efficiently neutralize Omicron variant and its sublineages. Structural analysis revealed how Omicron sublineages, but not other VOCs, efficiently evade an antibody family cross-reactive against SARS-CoV-1 through their escape mutations. Further evaluation of a series of SARS-CoV-1/2-cross-reactive bNAbs showed a negative correlation between the neutralizing activities against SARS-CoV-1 and SARS-CoV-2 Omicron variant. Together, these results suggest the necessity of using cross-neutralization against SARS-CoV-1 and SARS-CoV-2 Omicron as criteria for rational design and development of potent pan-sarbecovirus vaccines and bNAbs.

Force-Position Hybrid Compensation Control for Path Deviation in Robot-Assisted Bone Drilling.

Bone drilling is a common procedure in orthopedic surgery and is frequently attempted using robot-assisted techniques. However, drilling on rigid, slippery, and steep cortical surfaces, which are frequently encountered in robot-assisted operations due to limited workspace, can lead to tool path deviation. Path deviation can have significant impacts on positioning accuracy, hole quality, and surgical safety. In this paper, we consider the deformation of the tool and the robot as the main factors contributing to path deviation. To address this issue, we establish a multi-stage mechanistic model of tool-bone interaction and develop a stiffness model of the robot. Additionally, a joint stiffness identification method is proposed. To compensate for path deviation in robot-assisted bone drilling, a force-position hybrid compensation control framework is proposed based on the derived models and a compensation strategy of path prediction. Our experimental results validate the effectiveness of the proposed compensation control method. Specifically, the path deviation is significantly reduced by 56.6%, the force of the tool is reduced by 38.5%, and the hole quality is substantially improved. The proposed compensation control method based on a multi-stage mechanistic model and joint stiffness identification method can significantly improve the accuracy and safety of robot-assisted bone drilling.

A Novel A-ECMS Energy Management Strategy Based on Dragonfly Algorithm for Plug-in FCEVs.

The mechanical coupling of multiple powertrain components makes the energy management of 4-wheel-drive (4WD) plug-in fuel cell electric vehicles (PFCEVs) relatively complex. Optimizing energy management strategies (EMSs) for this complex system is essential, aiming at improving the vehicle economy and the adaptability of operating conditions. Accordingly, a novel adaptive equivalent consumption minimization strategy (A-ECMS) based on the dragonfly algorithm (DA) is proposed to achieve coordinated control of the powertrain components, front and rear motors, as well as the fuel cell system and the battery. To begin with, the equivalent consumption minimization strategy (ECMS) with extraordinary instantaneous optimization ability is used to distribute the vehicle demand power into the front and rear motor power, considering the different motor characteristics. Subsequently, under the proposed novel hierarchical energy management framework, the well-designed A-ECMS based on DA empowers PFCEVs with significant energy-saving advantages and adaptability to operating conditions, which are achieved by precise power distribution considering the operating characteristics of the fuel cell system and battery. These provide state-of-the-art energy-saving abilities for the multi-degree-of-freedom systems of PFCEVs. Lastly, a series of detailed evaluations are performed through simulations to validate the improved performance of A-ECMS. The corresponding results highlight the optimal control performance in the energy-saving performance of A-ECMS.

Circular RNA differential expression profiles and bioinformatics analysis of hsa_circRNA_079422 in human endometrial carcinoma.

The aim of our study was to explore circular RNA (circRNA) expression profiles associated with human endometrial carcinoma (EC) and to analyse the molecular mechanisms involved in cancer development and their potential clinical importance. Differential expression profiles were revealed by Arraystar human circRNA microarray analysis. The results of the circRNA microarray were confirmed by quantitative real-time PCR. Interactions between circRNAs and microRNAs (miRNAs) were predicted using Arraystar's miRNA target prediction software. The functions of the circRNA-miRNA coexpression network were identified by KEGG pathway analysis and GO analysis. Compared with para-tumorous tissues, 14 genes were significantly upregulated and 12 genes were significantly downregulated in EC tissues (P < 0.05). The quantitative real-time PCR data demonstrated consistency with the results of the microarray profile analysis. We generated a circRNA-miRNA coexpression network. Hsa_circRNA_079422 expression was significantly lower and miR-136-5p expression was higher in EC tissues than in normal endometrial tissues. KEGG pathway analysis and GO analysis indicated that hsa_circRNA_079422 might play roles in different signalling pathways and biological functions. We confirmed the presence of different circRNA expression profiles and predicted the circRNA-miRNA coexpression network in human EC tissues. Hsa_circRNA_079422 might be involved in the pathogenesis and biological process of EC via interactions with miRNAs.IMPACT STATEMENTWhat is already known on this subject? EC is a common malignancy of the female reproductive system. CircRNAs were demonstrated to exert critical roles in cancers, including EC.What do the results of this study add? The results of this study add circRNAs expression profiles, the circRNA-miRNA coexpression network and cancer-related circRNA-miRNA target genes in EC. It was first found that hsa_circRNA_079422 was downregulated, while miR-136-5p was upregulated in EC tissues.What are the implications of these findings for clinical practice and/or further research? In clinical practice, early EC diagnosis lacks specific biomarkers, so most EC patients are diagnosed at an advanced stage. In the management of EC patients, we also lack personalised adjuvant treatment that combines the clinical pathological characteristics. For the existing literature, we identified a new EC differential expression biomarker, hsa_circ_079422. It can be used to verify the correlation with EC clinical severity or poor prognosis. Its targeting can also be used to stratify EC patients with different molecular types, including to guide adjuvant therapy. In addition, we can verify and analyse regulatory pathways associated with it for the design of regulating engineering circRNA.

SGGformer: Shifted Graph Convolutional Graph-Transformer for Traffic Prediction.

Accurate traffic prediction is significant in intelligent cities' safe and stable development. However, due to the complex spatiotemporal correlation of traffic flow data, establishing an accurate traffic prediction model is still challenging. Aiming to meet the challenge, this paper proposes SGGformer, an advanced traffic grade prediction model which combines a shifted window operation, a multi-channel graph convolution network, and a graph Transformer network. Firstly, the shifted window operation is used for coarsening the time series data, thus, the computational complexity can be reduced. Then, a multi-channel graph convolutional network is adopted to capture and aggregate the spatial correlations of the roads in multiple dimensions. Finally, the improved graph Transformer based on the advanced Transformer model is proposed to extract the long-term temporal correlation of traffic data effectively. The prediction performance is evaluated by using actual traffic datasets, and the test results show that the SGGformer proposed exceeds the state-of-the-art baseline.

An Equivalent Consumption Minimization Strategy for a Parallel Plug-In Hybrid Electric Vehicle Based on an Environmental Perceiver.

An energy management strategy is a key technology used to exploit the energy-saving potential of a plug-in hybrid electric vehicle. This paper proposes the environmental perceiver-based equivalent consumption minimization strategy (EP-ECMS) for parallel plug-in hybrid vehicles. In this method, the traffic characteristic information obtained from the intelligent traffic system is used to guide the adjustment of the equivalence factor, improving the environmental adaptiveness of the equivalent consumption minimization strategy (ECMS). Two main works have been completed. First, a high-accuracy environmental perceiver was developed based on a graph convolutional network (GCN) and attention mechanism to complete the traffic state recognition of all graph regions based on historical information. Moreover, it provides the grade of the corresponding region where the vehicle is located (for the ECMS). Secondly, in the offline process, the search for the optimal equivalent factor is completed by using the Harris hawk optimization algorithm based on the representative working conditions under various grades. Based on the identified traffic grades in the online process, the optimized equivalence factor tables are checked for energy management control. The simulation results show that the improved EP-ECMS can achieve 7.25% energy consumption optimization compared with the traditional ECMS.

BLM prevents instability of structure-forming DNA sequences at common fragile sites.

Genome instability often arises at common fragile sites (CFSs) leading to cancer-associated chromosomal rearrangements. However, the underlying mechanisms of how CFS protection is achieved is not well understood. We demonstrate that BLM plays an important role in the maintenance of genome stability of structure-forming AT-rich sequences derived from CFSs (CFS-AT). BLM deficiency leads to increased DSB formation and hyper mitotic recombination at CFS-AT and induces instability of the plasmids containing CFS-AT. We further showed that BLM is required for suppression of CFS breakage upon oncogene expression. Both helicase activity and ATR-mediated phosphorylation of BLM are important for preventing genetic instability at CFS-AT sequences. Furthermore, the role of BLM in protecting CFS-AT is not epistatic to that of FANCM, a translocase that is involved in preserving CFS stability. Loss of BLM helicase activity leads to drastic decrease of cell viability in FANCM deficient cells. We propose that BLM and FANCM utilize different mechanisms to remove DNA secondary structures forming at CFS-AT on replication forks, thereby preventing DSB formation and maintaining CFS stability.

National response strategies and marketing innovations during the COVID-19 pandemic.

During the COVID-19 pandemic, different nations have adopted a variety of response strategies to fight and contain the new coronavirus. Such national response strategies can be classified into three categories based on their underlying philosophy: strict control with unlimited resources, relentless contribution with limited resources, and rough rationality with limited resources. We discuss the philosophies, characteristics, and performances of the three response strategies and when they should be adopted. We also examine what marketing innovation strategies enterprises should adopt to survive and grow their businesses in both the short and long term. This study provides important strategic implications for national policymakers and enterprises on the use of response strategies as well as marketing innovation tactics and strategies to be used both during and after the pandemic.