SNHG18 controls vascular smooth muscle cell contractile phenotype and neointimal hyperplasia.

AIMS: Long non-coding RNA (LncRNA) small nucleolar RNA host gene 18 (SNHG18) has been widely implicated in cancers. However, little is known about its functional involvement in vascular diseases. Herein, we attempted to explore a role for SNHG18 in modulating vascular smooth muscle cell (VSMC) contractile phenotype and injury-induced neointima formation. METHODS AND RESULTS: Analysis of single cell RNA sequencing and transcriptomic datasets showed decreased levels of SNHG18 in injured and atherosclerotic murine and human arteries, which is positively associated with VSMC contractile genes. SNHG18 was upregulated in VSMCs by TGFß1 through transcription factors Sp1 and SMAD3. SNHG18 gene gain/loss-of-function studies revealed that VSMC contractile phenotype was positively regulated by SNHG18. Mechanistic studies showed that SNHG18 promotes a contractile VSMC phenotype by up-regulating miR-22-3p. SNHG18 up-regulates miR-22 biogenesis and miR-22-3p production by competitive binding with the A-to-I RNA editing enzyme, adenosine deaminase acting on RNA-2 (ADAR2). Surprisingly, we observed that ADAR2 inhibited miR-22 biogenesis not through increasing A-to-I editing within primary miR-22, but by interfering the binding of microprocessor complex subunit DGCR8 to primary miR-22. Importantly, perivascular SNHG18 overexpression in the injured vessels dramatically up-regulated the expression levels of miR-22-3p and VSMC contractile genes, and prevented injury-induced neointimal hyperplasia. Such modulatory effects were reverted by miR-22-3p inhibition in the injured arteries. Finally, we observed a similar regulator role for SNHG18 in human VSMCs, and a decreased expression level of both SNHG18 and miR-22-3p in diseased human arteries; and we found that the expression level of SNHG18 was positively associated with that of miR-22-3p in both healthy and diseased human arteries. CONCLUSION: We demonstrate that SNHG18 is a novel regulator in governing VSMC contractile phenotype and preventing injury-induced neointimal hyperplasia. Our findings have important implications for therapeutic targeting snhg18/miR-22-3p signalling in vascular diseases.

Optimized production of full-length PCV2d virus-like particles in Escherichia coli: A cost-effective and high-yield approach for potential vaccine antigen development.

Porcine circovirus type 2 (PCV2) is a globally prevalent infectious pathogen affecting swine, with its capsid protein (Cap) being the sole structural protein critical for vaccine development. Prior research has demonstrated that PCV2 Cap proteins produced in Escherichia coli (E. coli) can form virus-like particles (VLPs) in vitro, and nuclear localization signal peptides (NLS) play a pivotal role in stabilizing PCV2 VLPs. Recently, PCV2d has emerged as an important strain within the PCV2 epidemic. In this study, we systematically optimized the PCV2d Cap protein and successfully produced intact PCV2d VLPs containing NLS using E. coli. The recombinant PCV2d Cap protein was purified through affinity chromatography, yielding 7.5 mg of recombinant protein per 100 ml of bacterial culture. We augmented the conventional buffer system with various substances such as arginine, ß-mercaptoethanol, glycerol, polyethylene glycol, and glutathione to promote VLP assembly. The recombinant PCV2d Cap self-assembled into VLPs approximately 20 nm in diameter, featuring uniform distribution and exceptional stability in the optimized buffer. We developed the vaccine and immunized pigs and mice, evaluating the immunogenicity of the PCV2d VLPs vaccine by measuring PCV2-IgG, IL-4, TNF-α, and IFN-γ levels, comparing them to commercial vaccines utilizing truncated PCV2 Cap antigens. The HE staining and immunohistochemical tests confirmed that the PCV2 VLPs vaccine offered robust protection. The results revealed that animals vaccinated with the PCV2d VLPs vaccine exhibited high levels of PCV2 antibodies, with TNF-α and IFN-γ levels rapidly increasing at 14 days post-immunization, which were higher than those observed in commercially available vaccines, particularly in the mouse trial. This could be due to the fact that full-length Cap proteins can assemble into more stable PCV2d VLPs in the assembling buffer. In conclusion, our produced PCV2d VLPs vaccine elicited stronger immune responses in pigs and mice compared to commercial vaccines. The PCV2d VLPs from this study serve as an excellent candidate vaccine antigen, providing insights for PCV2d vaccine research.

Comparative analysis of robotically-assisted versus conventional sternotomy approach in left atrial myxoma resection: A single-center retrospective observational study.

BACKGROUND: Minimally invasive surgery has emerged as a favorable alternative to conventional surgery for various cardiac conditions. This study aimed to compare the perioperative outcomes and follow-up results of the robotic approach versus the sternotomy approach for left atrial myxoma (LAM) resection. METHOD: We retrospectively analyzed the perioperative outcomes and follow-up results of 94 patients who underwent left atrial myxoma resection using either the sternotomy approach (n = 64) or the robotic approach (n = 30) at our center between January 2017 and April 2023. Multiple linear regressions were employed to examine the actual impact of the surgical approach on perioperative outcomes while controlling for potential confounding factors. RESULTS: There were no in-hospital deaths or follow-up deaths in the robotic group. Univariate analyses revealed that robotic LAM resection had a longer cardiopulmonary bypass (CPB) time (99.93 ± 22.30 vs. 76.28 ± 24.92, P < 0.001), longer aortic clamping time (57.80 ± 20.27 vs. 47.89 ± 18.10, P = 0.019), reduced postoperative drainage (P < 0.001), shorter mechanical ventilation time (P = 0.005), shorter postoperative bed-stay time (P < 0.001), shorter postoperative hospitalization time (P = 0.040), and higher hospital costs (P = 0.001) compared to the sternotomy group. After adjusting for baseline characteristics in a multiple regression model, a longer CPB time (B = 28.328; CI, 18.609-38.047; P < 0.001), longer aortic clamping time (B = 11.856; CI, 4.069-19.644; P = 0.003), reduced postoperative drainage (B = -200.224; CI, -254.962- -145.486; P < 0.001), shorter mechanical ventilation time (B = -3.429; CI, -6.562- -0.295; P = 0.032), shorter postoperative bed-stay time (B = -2.230; CI, -3.267- -1.193; P < 0.001), shorter postoperative hospitalization time (B = -1.998; CI, -3.747- -0.250; P = 0.026), and higher hospital costs (B = 2096.866, P = 0.002) were found in the robotic group. Furthermore, the robotic group exhibited a faster return to exercise compared to the sternotomy group (Log-Rank χ2 = 34.527, P < 0.001). CONCLUSION: Both the robotic and sternotomy approaches are viable and safe options for LAM resection. However, despite the higher costs, longer CPB time, and longer aortic clamping time associated with robotic LAM resection, this technique was correlated with reduced postoperative drainage and faster postoperative recovery compared to the sternotomy technique.

Risk factors for prolonged postoperative ICU stay in the patients with Stanford type A aortic dissection.

OBJECTIVE: To investigate the independent risk factors for postoperative prolonged ICU stay in patients with Stanford type A aortic dissection (TAAD) and assess the clinical outcomes of prolonged ICU stay. METHOD: The clinical data of 100 patients with TAAD admitted to the Department of Cardiovascular Surgery, First Affiliated Hospital of Anhui Medical University from December 2018 to September 2022 were retrospectively collected and analyzed. Patients were divided into two groups, based on the postoperative ICU stay (7 days as the threshold), regular ICU stay group (< 7 days) and prolonged ICU stay group (≥ 7 days). First, preoperative and intraoperative materials were collected for univariate analysis. Then, the significant variables after univariate analysis were analyzed using logistic regression, and the final independent risk factors for prolonged ICU stay were determined. Meanwhile, the postoperative clinical outcomes were analyzed with the aim of assessing the clinical outcomes due to prolonged ICU stay. RESULTS: There were 65 and 35 patients in the regular ICU stay group and the prolonged ICU stay group, respectively. In accordance with the result of univariate analysis in the two groups, emergency surgery (χ2 = 13.598; P < 0.001), preoperative urea nitrogen (t = 3.006; P = 0.004), cardiopulmonary bypass (CPB) time (t = 2.671; P = 0.001) and surgery time (t = 2.630; P = 0.010) were significant. All significant variates were analyzed through logistic regression, and it was found that emergency surgery (OR = 0.192; 95% CI: 0.065-0.561), preoperative urea nitrogen (OR = 0.775; 95% CI: 0.634-0.947) and cardiopulmonary time (OR = 0.988; 95% CI: 0.979-0.998) were independent risk factors for prolonged postoperative ICU stay. The Receiver Operating Characteristic (ROC) curves of these three factors were also effective in predicting postoperative prolonged ICU stay (Emergency surgery, AUC = 0.308, 95% CI: 0.201-0.415; Preoperative urea nitrogen, AUC = 0.288, 95% CI: 0.185-0.392; cardiopulmonary time, AUC = 0.340, 95% CI: 0.223-0.457). Moreover, compared with a single factor, the predictive value of combined factors was more significant (AUC = 0.810, 95% CI: 0.722-0.897). For the comparison of postoperative data in the two groups,, compared with the regular ICU stay group, the incidence of adverse events in the prolonged ICU stay group increased significantly, including limb disability of limbs (χ2 = 22.182; P < 0.001), severe organ injury (χ2 = 23.077; P < 0.001), tracheotomy (χ2 = 17.582; P < 0.001), reintubation (χ2 = 28.020; P < 0.001), 72 h tracheal extubation after surgery (χ2 = 29.335; P < 0.001), 12 h consciousness recovery after surgery (χ2 = 18.445; P < 0.001), ICU re-entering (χ2 = 9.496; P = 0.002) and irregular discharging (χ2 = 24.969; P < 0.001). CONCLUSION: Emergency surgery, preoperative urea nitrogen, and CPB time are risk factors for postoperative prolonged ICU stay after TAAD surgery. Furthermore, prolonged ICU stay is associated with worse clinical outcomes. Hence, a reasonable strategy should be adopted proactively focusing on the risk factors to shorten ICU stays and improve clinical outcomes.

Live streaming E-commerce platform characteristics: Influencing consumer value co-creation and co-destruction behavior.

Live streaming with goods is developing rapidly as an emerging platform economic model. Consumers can interact with the e-commerce platform in real-time and get a good shopping experience. This in turn generates value co-creation behaviors such as word-of-mouth communication. However, due to the lack of effective audit mechanisms on some platforms, the phenomenon of value co-destruction among them is becoming more and more common. This brings value loss to consumers, e-commerce platforms, and other multiple subjects. Based on the SOR model, this paper collects 212 sample data by using a questionnaire survey. The impact of live banding platform characteristics on consumers' value co-creation and value co-destruction behaviors is analyzed through multiple regression and other methods. The results show that platform information quality, functional quality, and interactive quality all positively affect consumers' value co-creation behavior and negatively affect value co-destruction behavior. Perceived value plays a mediating role, and promotional incentives enhance the positive relationship between platform features and perceived value. Therefore, if the live streaming bandwagon platform provides consumers with sufficiently rich, complete, and timely product information, responds quickly to consumer needs, and has high interaction quality. Consumers are more likely to exhibit value co-creation behavior. This study enriches the theoretical results of value co-creation and value co-destruction. It provides theoretical references for live streaming platforms to inhibit consumers' value co-destructive behaviors and promote value co-creation behaviors. In practice, it is pointed out that live streaming platforms should provide consumers with real information on all aspects of the products, update and improve the performance of the platform in a timely manner, and provide regular training to the staff.

TM-search: An Efficient and Effective Tool for Protein Structure Database Search.

The quickly increasing size of the Protein Data Bank is challenging biologists to develop a more scalable protein structure alignment tool for fast structure database search. Although many protein structure search algorithms and programs have been designed and implemented for this purpose, most require a large amount of computational time. We propose a novel protein structure search approach, TM-search, which is based on the pairwise structure alignment program TM-align and a new iterative clustering algorithm. Benchmark tests demonstrate that TM-search is 27 times faster than a TM-align full database search while still being able to identify ∼90% of all high TM-score hits, which is 2-10 times more than other existing programs such as Foldseek, Dali, and PSI-BLAST.

Proteomic screens of SEL1L-HRD1 ER-associated degradation substrates reveal its role in glycosylphosphatidylinositol-anchored protein biogenesis.

Endoplasmic reticulum-associated degradation (ERAD) plays indispensable roles in many physiological processes; however, the nature of endogenous substrates remains largely elusive. Here we report a proteomics strategy based on the intrinsic property of the SEL1L-HRD1 ERAD complex to identify endogenous ERAD substrates both in vitro and in vivo. Following stringent filtering using a machine learning algorithm, over 100 high-confidence potential substrates are identified in human HEK293T and mouse brown adipose tissue, among which ~88% are cell type-specific. One of the top shared hits is the catalytic subunit of the glycosylphosphatidylinositol (GPI)-transamidase complex, PIGK. Indeed, SEL1L-HRD1 ERAD attenuates the biogenesis of GPI-anchored proteins by specifically targeting PIGK for proteasomal degradation. Lastly, several PIGK disease variants in inherited GPI deficiency disorders are also SEL1L-HRD1 ERAD substrates. This study provides a platform and resources for future effort to identify proteome-wide endogenous substrates in vivo, and implicates SEL1L-HRD1 ERAD in many cellular processes including the biogenesis of GPI-anchored proteins.

Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data.

Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and effective model selection, and in the power of integrating huge metagenomics databases. These results demonstrate a new avenue to improve deep learning protein structure prediction through advanced MSA construction and provide additional evidence that optimization of input information to deep learning-based structure prediction methods must be considered with as much care as the design of the predictor itself.

BioLiP2: an updated structure database for biologically relevant ligand-protein interactions.

With the progress of structural biology, the Protein Data Bank (PDB) has witnessed rapid accumulation of experimentally solved protein structures. Since many structures are determined with purification and crystallization additives that are unrelated to a protein's in vivo function, it is nontrivial to identify the subset of protein-ligand interactions that are biologically relevant. We developed the BioLiP2 database (https://zhanggroup.org/BioLiP) to extract biologically relevant protein-ligand interactions from the PDB database. BioLiP2 assesses the functional relevance of the ligands by geometric rules and experimental literature validations. The ligand binding information is further enriched with other function annotations, including Enzyme Commission numbers, Gene Ontology terms, catalytic sites, and binding affinities collected from other databases and a manual literature survey. Compared to its predecessor BioLiP, BioLiP2 offers significantly greater coverage of nucleic acid-protein interactions, and interactions involving large complexes that are unavailable in PDB format. BioLiP2 also integrates cutting-edge structural alignment algorithms with state-of-the-art structure prediction techniques, which for the first time enables composite protein structure and sequence-based searching and significantly enhances the usefulness of the database in structure-based function annotations. With these new developments, BioLiP2 will continue to be an important and comprehensive database for docking, virtual screening, and structure-based protein function analyses.

Risk factors analysis and survival prediction model establishment of patients with lung adenocarcinoma based on different pyroptosis-related gene subtypes.

BACKGROUND: Lung adenocarcinoma (LUAD) is a common cancer with a poor prognosis. Pyroptosis is an important process in the development and progression of LUAD. We analyzed the risk factors affecting the prognosis of patients and constructed a nomogram to predict the overall survival of patients based on different pyroptosis-related genes (PRGs) subtypes. METHODS: The genomic data of LUAD were downloaded from the TCGA and GEO databases, and all data were filtered and divided into TCGA and GEO cohorts. The process of data analysis and visualization was performed via R software. The data were classified based on different PRGs subtypes using the K-means clustering method. Then, the differentially expressed genes were identified between two different subtypes, and risk factors analysis, survival analysis, functional enrichment analysis, and immune cells infiltration landscape analysis were conducted. The COX regression analysis was used to construct the prediction model. RESULTS: Based on the PRGs of LUAD, the patients were divided into two subtypes. We found the survival probability of patients in subtype 1 is higher than that in subtype 2. The results of the logistics analysis showed that gene risk score was closely associated with the prognosis of LUAD patients. The results of GO analysis and KEGG analysis revealed important biological processes and signaling pathways involved in the differentially expressed proteins between the two subtypes. Then we constructed a prediction model of patients' prognosis based on 13 genes, including IL-1A, P2RX1, GSTM2, ESYT3, ZNF682, KCNF1, STK32A, HHIPL2, GDF10, NDC80, GSTA1, BCL2L10, and CCR2. This model was strongly related to the overall survival (OS) and also reflects the immune status in patients with LUAD. CONCLUSION: In our study, we examined LUAD heterogeneity with reference to pyroptosis and found different prognoses between the two subtypes. And a novel prediction model was constructed to predict the OS of LUAD patients based on different PRGs signatures. The model has shown excellent predictive efficiency through validation.

A large-scale assessment of sequence database search tools for homology-based protein function prediction.

Sequence database searches followed by homology-based function transfer form one of the oldest and most popular approaches for predicting protein functions, such as Gene Ontology (GO) terms. Although sequence search tools are the basis of homology-based protein function prediction, previous studies have scarcely explored how to select the optimal sequence search tools and configure their parameters to achieve the best function prediction. In this paper, we evaluate the effect of using different options from among popular search tools, as well as the impacts of search parameters, on protein function prediction. When predicting GO terms on a large benchmark dataset, we found that BLASTp and MMseqs2 consistently exceed the performance of other tools, including DIAMOND - one of the most popular tools for function prediction - under default search parameters. However, with the correct parameter settings, DIAMOND can perform comparably to BLASTp and MMseqs2 in function prediction. This study emphasizes the critical role of search parameter settings in homology-based function transfer.

Risk prediction for <1 cm lateral lymph node metastasis in papillary thyroid microcarcinoma.

Background: Because the diameter of the suspicious lymph nodes is less than 1 cm and adjacent to important structures in the neck, the diagnosis of small LLNM is important but difficult without the help of fine needle aspiration (FNA). There are no relevant reports of risk factors that predict the risk of suspicious <1 cm LLNM. Methods: A total of 159 PTMC patients with suspicious <1 cm LLNM were included in the study. Multivariate logistic regression analysis was used to identify ultrasound independent predictors of LLNM. A predictive model was developed according to multivariate logistic regression and evaluated by Hosmer-Lemeshow fit test. Results: Age ≤ 38 years old, the largest PTMC was located in the upper part, and the presence of liquefaction or microcalcification in suspicious lymph nodes were independent risk factors for LLNM (univariate analysis P = 0.00, 0.00, 0.00; multivariate analysis P = 0.00, 0.02, 0.00. OR = 4.66 [CI: 1.78-12.21], 3.04 [CI: 1.24-7.46], 6.39 [CI: 1.85-22.00]). The predictive model for the diagnosis of suspicious <1 cm lymph nodes was established as: P = ex/(1 + ex). X = -1.29 + (1.11 × whether the largest tumor is located in the upper part) + (1.54 × whether the age is ≤ 38 years) + (1.85 × whether the suspicious lymph nodes have liquefaction/microcalcification). The Hosmer-Lemeshow fit test was used to test the predicted ability, and it found that the predictive model had a good fit and prediction accuracy (X2 = 6.214, P = 0.623 > 0.05). Chi squared trend analysis showed that the increase in the number of risk factors gradually increased the malignancy possibility of suspicious <1 cm lymph nodes (chi squared trend test, P = 0.00). Conclusions: Age ≤ 38 years old, the largest PTMC located in the upper part, and the presence of liquefaction or microcalcification in suspicious lymph nodes were independent risk factors for suspicious <1 cm LLNM in PTMC patients. Our result show that it is feasible to evaluate the malignant possibility of these lymph nodes using the number of risk factors.

Long-term observations of NO2 using GEMS in China: Validations and regional transport.

In 2019, South Korea launched the Geostationary Environment Monitoring Spectrometer (GEMS) to observe trace gases with an hourly temporal resolution. Compared to previous payloads on polar-orbiting satellites, the GEMS payload has significant advantages in detecting the diurnal variation characteristics of NO2. However, there is still a lack of ground-based validations regarding the overall accuracy of GEMS in the Chinese region. In this study, we conducted a systematic ground validation of GEMS NO2 data in China for the first time. We validated the accuracy of GEMS NO2 data in four typical pollution regions in China, namely the Beijing-Tianjin-Hebei region (JJJ), the Yangtze River Delta region (YRD), the Pearl River Delta region (PRD), and the Sichuan Basin region (SCB), based on MAX-DOAS and CNEMC data. The averaged correlations using the two datasets for validation were 0.81 and 0.57, respectively, indicating a high level of accuracy for the data in China. Using the GEMS seasonal averaged NO2 data, we studied the distribution of NO2 levels in the four regions. We found that the highest NO2 in all four regions occurred during winter with concentrations of 1.84 × 1016 molecules cm-2, 1.59 × 1016 molecules cm-2, 1.58 × 1016 molecules cm-2 and 9.47 × 1015 molecules cm-2, respectively. The distribution of NO2 was closely related to the terrain. Additionally, we observed a significant underestimation issue with TROPOMI, exceeding 30 % in many regions. Based on MAX-DOAS, we investigated the vertical distribution of NO2 in the four regions and found that NO2 was mainly concentrated below 0.5 km. with the HNU station having the lowest concentration, averaging only 2.12 ppb, which was approximately 41 % of the highest concentration recorded at the CQ station. Furthermore, we conducted a study on regional and cross-regional transport using a combination of MAX-DOAS and GEMS data. We found that the transport flux of NO2 could increase by over 500 % within 1 h, making a significant contribution to local NO2 concentrations. The joint observations of GEMS and MAX-DOAS will provide reliable data support for NO2 research and control in China, making a substantial contribution to environmental protection and sustainable development.

Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction.

RNAs are fundamental in living cells and perform critical functions determined by their tertiary architectures. However, accurate modeling of 3D RNA structure remains a challenging problem. We present a novel method, DRfold, to predict RNA tertiary structures by simultaneous learning of local frame rotations and geometric restraints from experimentally solved RNA structures, where the learned knowledge is converted into a hybrid energy potential to guide RNA structure assembly. The method significantly outperforms previous approaches by >73.3% in TM-score on a sequence-nonredundant dataset containing recently released structures. Detailed analyses showed that the major contribution to the improvements arise from the deep end-to-end learning supervised with the atom coordinates and the composite energy function integrating complementary information from geometry restraints and end-to-end learning models. The open-source DRfold program with fast training protocol allows large-scale application of high-resolution RNA structure modeling and can be further improved with future expansion of RNA structure databases.

Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China.

Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.

IQGAP1 promotes mitochondrial damage and activation of the mtDNA sensor cGAS-STING pathway to induce endothelial cell pyroptosis leading to atherosclerosis.

Atherosclerosis (AS) is the most common cardiovascular disease and has limited therapeutic options. IQ motif-containing GTPase-activating protein 1 (IQGAP1) is an important scaffolding protein regulating mitochondrial function influencing endothelial cell activity. Evidence suggests that mitochondrial damage can lead to leakage of mtDNA into the cytoplasm to activate the DNA sensor cGAS-STING to mediate pyroptosis. However, whether IQGAP1 induces NLRP3-mediated endothelial cell pyroptosis by regulating mitochondrial function and activating the DNA sensor cGAS-STING, and its underlying mechanisms remain unclear. In vivo, ApoE-/- C57BL/J and Ldlr-/- C57BL/J mice were pre-injected with adeno-associated virus (AAV) by the tail vein to specifically silence IQGAP1 expression and were fed a high-fat diet (HFD) for 12 weeks. IQGAP1 knockdown reduced mtDNA release and decreased the expression of DNA receptors and pyroptosis-related molecules as determined by immunohistochemistry and immunofluorescence. In vitro, palmitic acid (0.3 mmol/L) was incubated with human umbilical vein endothelial cells (HUVECs) for 24 h. Overexpression of IQGAP1 in HUVECs, flow cytometry, and mitochondrial superoxide staining revealed increased levels of ROS. Moreover, the mitochondrial tracker with dsDNA co-localization showed the release of mtDNA into the cytoplasm increased, which activated the DNA receptor cGAS-STING. Protein blotting and TUNEL staining revealed that IQGAP1 promoted NLRP3-mediated pyroptosis. Furthermore, cGAS or STING small-molecule inhibitors RU.521 or C-176 reverse IQGAP1-promoted HUVECs from undergoing NLRP3-mediated pyroptosis. These results suggest that IQGAP1 promotes oxidative stress and mtDNA release, activates the DNA sensor cGAS-STING, and leads to NLRP3-mediated pyroptosis. The present study provides new insights into the mechanisms underlying AS and identifies new pharmacological targets for treatment.

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models.

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.

Postoperative hypoxemia for patients undergoing Stanford type A aortic dissection.

Clinically, it is widely recognized that surgical treatment is the preferred and reliable option for Stanford type A aortic dissection. Stanford type A aortic dissection is an emergent and serious cardiovascular disease characterized with an acute onset, poor prognosis, and high mortality. However, the incidences of postoperative complications are relatively higher due to the complexity of the disease and its intricate procedure. It has been considered that hypoxemia, one of the most common postoperative complications, plays an important role in having a worse clinical prognosis. Therefore, the effective intervention of postoperative hypoxemia is significant for the improved prognosis of patients with Stanford type A aortic dissection.

BeEM: fast and faithful conversion of mmCIF format structure files to PDB format.

BACKGROUND: Although mmCIF is the current official format for deposition of protein and nucleic acid structures to the protein data bank (PDB) database, the legacy PDB format is still the primary supported format for many structural bioinformatics tools. Therefore, reliable software to convert mmCIF structure files to PDB files is needed. Unfortunately, existing conversion programs fail to correctly convert many mmCIF files, especially those with many atoms and/or long chain identifies. RESULTS: This study proposed BeEM, which converts any mmCIF format structure files to PDB format. BeEM conversion faithfully retains all atomic and chain information, including chain IDs with more than 2 characters, which are not supported by any existing mmCIF to PDB converters. The conversion speed of BeEM is at least ten times faster than existing converters such as MAXIT and Phenix. Part of the reason for the speed improvement is the avoidance of conversion between numerical values and text strings. CONCLUSION: BeEM is a fast and accurate tool for mmCIF-to-PDB format conversion, which is a common procedure in structural biology. The source code is available under the BSD licence at https://github.com/kad-ecoli/BeEM/ .