Training Data Diversity Enhances the Basecalling of Novel RNA Modification-Induced Nanopore Sequencing Readouts.

Accurately basecalling sequence backbones in the presence of nucleotide modifications remains a substantial challenge in nanopore sequencing bioinformatics. It has been extensively demonstrated that state-of-the-art basecallers are less compatible with modification-induced sequencing signals. A precise basecalling, on the other hand, serves as the prerequisite for virtually all the downstream analyses. Here, we report that basecallers exposed to diverse training modifications gain the generalizability to analyze novel modifications. With synthesized oligos as the model system, we precisely basecall various out-of-sample RNA modifications. From the representation learning perspective, we attribute this generalizability to basecaller representation space expanded by diverse training modifications. Taken together, we conclude increasing the training data diversity as a novel paradigm for building modification-tolerant nanopore sequencing basecallers.

CT perfusion parameter estimation in stroke using neural network with transformer and physical model priors.

OBJECTIVES: CT perfusion (CTP) imaging is vital in treating acute ischemic stroke by identifying salvageable tissue and the infarcted core. CTP images allow quantitative estimation of CT perfusion parameters, which can provide information on the degree of tissue hypoperfusion and its salvage potential. Traditional methods for estimating perfusion parameters, such as singular value decomposition (SVD) and its variations, are known to be sensitive to noise and inaccuracies in the arterial input function. To our knowledge, there has been no implementation of deep learning methods for CT perfusion parameter estimation. MATERIALS & METHODS: In this work, we propose a deep learning method based on the Transformer model, named CTPerformer-Net, for CT perfusion parameter estimation. In addition, our method incorporates some physical priors. We integrate physical consistency prior, smoothness prior and the physical model prior through the design of the loss function. We also generate a simulation dataset based on physical model prior for training the network model. RESULTS: In the simulation dataset, CTPerformer-Net exhibits a 23.4 % increase in correlation coefficients, a 95.2 % decrease in system error, and a 90.7 % reduction in random error when contrasted with block-circulant SVD. CTPerformer-Net successfully identifies hypoperfused and infarcted lesions in 103 real CTP images from the ISLES 2018 challenge dataset. It achieves a mean dice score of 0.36 for the infarct core segmentation, which is slightly higher than the commercially available software (dice coefficient: 0.34) used as a reference level by the challenge. CONCLUSION: Experimental results on the simulation dataset demonstrate that CTPerformer-Net achieves better performance compared to block-circulant SVD. The real-world patient dataset confirms the validity of CTPerformer-Net.

Deciphering the impact of aggregated autophagy-related genes TUBA1B and HSP90AA1 on colorectal cancer evolution: a single-cell sequencing study of the tumor microenvironment.

BACKGROUND: Colorectal cancer (CRC) is the third most prevalent cancer worldwide, with the tumor microenvironment (TME) playing a crucial role in its progression. Aggregated autophagy (AA) has been recognized as a factor that exacerbates CRC progression. This study aims to study the relationship between aggregated autophagy and CRC using single-cell sequencing techniques. Our goal is to explain the heterogeneity of the TME and to explore the potential for targeted personalized therapies. OBJECTIVE: To study the role of AA in CRC, we employed single-cell sequencing to discern distinct subpopulations within the TME. These subpopulations were characterized by their autophagy levels and further analyzed to identify specific biological processes and marker genes. RESULTS: Our study revealed significant correlations between immune factors and both clinical and biological characteristics of the tumor microenvironment (TME), particularly in cells expressing TUBA1B and HSP90AA1. These immune factors were associated with T cell depletion, a reduction in protective factors, diminished efficacy of immune checkpoint blockade (ICB), and enhanced migration of cancer-associated fibroblasts (CAFs), resulting in pronounced inflammation. In vitro experiments showd that silencing TUBA1B and HSP90AA1 using siRNA (Si-TUBA1B and Si-HSP90AA1) significantly reduced the expression of IL-6, IL-7, CXCL1, and CXCL2 and inhibition of tumor cell growth in Caco-2 and Colo-205 cell lines. This reduction led to a substantial alleviation of chronic inflammation and highlighted the heterogeneous nature of the TME. CONCLUSION: This study marks an initial foray into understanding how AA-associated processes may potentiate the TME and weaken immune function. Our findings provide insights into the complex dynamics of the TME and highlight potential targets for therapeutic intervention, suggesting a key role for AA in the advancement of colorectal cancer.

Heterozygous de novo dominant negative mutation of REXO2 results in interferonopathy.

Mitochondrial RNA (mtRNA) in the cytosol can trigger the innate immune sensor MDA5, and autoinflammatory disease due to type I IFN. Here, we show that a dominant negative mutation in the gene encoding the mitochondrial exonuclease REXO2 may cause interferonopathy by triggering the MDA5 pathway. A patient characterized by this heterozygous de novo mutation (p.T132A) presented with persistent skin rash featuring hyperkeratosis, parakeratosis and acanthosis, with infiltration of lymphocytes and eosinophils around small blood vessels. In addition, circulating IgE levels and inflammatory cytokines, including IFNα, are found consistently elevated. Transcriptional analysis highlights a type I IFN gene signature in PBMC. Mechanistically, REXO2 (T132A) lacks the ability to cleave RNA and inhibits the activity of wild-type REXO2. This leads to an accumulation of mitochondrial dsRNA in the cytosol, which is recognized by MDA5, leading to the associated type I IFN gene signature. These results demonstrate that in the absence of appropriate regulation by REXO2, aberrant cellular nucleic acids may accumulate and continuously trigger innate sensors, resulting in an inborn error of immunity.

A Deep Learning-Based Framework for Predicting Intracerebral Hemorrhage Hematoma Expansion Using Head Non-contrast CT Scan.

RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework based on deep learning for predicting HE using only clinical non-contrast CT (NCCT) scans. MATERIALS AND METHODS: A large retrospective dataset (n = 2484) was collected from 84 centers, while a prospective dataset (n = 500) was obtained from 26 additional centers. Baseline NCCT scans and follow-up NCCT scans were conducted within 6 h and 48 h from symptom onset, respectively. HE was defined as a volume increase of more than 6 mL on the follow-up NCCT. The retrospective dataset was divided into a training set (n = 1876) and a validation set (n = 608) by patient inclusion time. A two-stage framework was trained to predict HE, and its performance was evaluated on both the validation and prospective sets. Receiver operating characteristics area under the curve (AUC), sensitivity, and specificity were leveraged. RESULTS: Our two-stage framework achieved an AUC of 0.760 (95% CI 0.724-0.799) on the retrospective validation set and 0.806 (95% CI 0.750-0.859) on the prospective set, outperforming the commonly used BAT score, which had AUCs of 0.582 and 0.699, respectively. CONCLUSION: Our framework can automatically and robustly identify ICH patients at high risk of HE using admission head NCCT scans, providing more accurate predictions than the BAT score.

Comparative Cardiovascular Risks of Radical Prostatectomy and External Beam Radiation Therapy in Early-Stage Prostate Cancer: A Comprehensive Retrospective Analysis.

BACKGROUND: The risk of cardiac disease mortality has recently become a focal point of concern within the medical community for patients with prostate cancer (PCa). Given that radical prostatectomy (RP) and external beam radiation therapy (EBRT) are the main treatment modalities for localized PCa, their specific impact on cardiovascular-specific mortality (CSM) remains unclear. This study explored the specific effects of RP and EBRT on CSM risk to guide clinical treatment decisions. METHODS: Data from patients aged 45-74 years, who were diagnosed with T1-2N0M0 stage PCa from the SEER database (2010-2015), were used. Multivariate statistical methods, including propensity score matching (PSM), competing risk regression, COX regression analysis, and Fine-Gray testing, were applied to assess the impact of RP and EBRT on CSM risk. RESULTS: Among 146,082 T1-2 stage PCa patients, cardiac disease emerged as the primary cause of death, surpassing PCa itself. Multifactorial COX regression and competing risk regression analyses indicated that local treatments do not increase CSM risk. Further analysis revealed a significant increase in CSM risk for patients undergoing only EBRT compared with those undergoing only RP (hazard ratio [HR] = 2.71, 95% confidence interval [CI] 1.96-3.74, P < 0.001), with subsequent PSM adjustment, further confirming a significantly reduced risk in the RP treatment group (HR 0.23, 95% CI 0.13-0.40, P < 0.001). CONCLUSIONS: T1-2 stage PCa patients face a significant risk of CSM, with RP offering a potential advantage over EBRT in reducing this risk. These findings encourage clinicians to comprehensively consider the potential impact on cardiac health when formulating treatment plans, providing crucial guidance for optimizing treatment strategies.

Simultaneous detection of enrofloxacin and florfenicol in animal-derived foods based on fluorescence quenching BELISA and a nanozyme catalytic strategy.

Enrofloxacin (ENRO) and florfenicol (FF) are animal-specific drugs, but they present great harm to human health. Therefore, it is essential to rapidly and accurately detect ENRO and FF in animal-derived foods simultaneously. Herein, dual-template molecular imprinted polymers (MIPs) with specific recognition of ENRO and FF were prepared, meanwhile, the molar ratios of templates to monomer and cross-linker were optimized and then applied as a bionic antibody to experiment. Based on the principle that the fluorescence of QDs could be efficiently quenched by the enzymatic fabrication of Prussian blue nanoparticles (PBNPs), a novel and sensitive fluorescence quenching biomimetic enzyme-linked immunosorbent assay (BELISA) was established for simultaneous detection of ENRO and FF by the conversion of the absorption signal into fluorescent signals. Under optimal conditions, the detection limit (IC15) was 4.64 ng L-1 for ENRO and 1.33 ng L-1 for FF. Besides, matrix interference of chicken, eggs, milk and shrimp samples, was investigated in our study, and the result indicates that all of the sample matrices had a profound impact on the fluorescence of QDs, especially for milk samples (with Im of 94.10 %). After performing the matrix-elimination experiments, chicken, eggs, milk and shrimp samples spiked with ENRO and FF were extracted and detected by this proposed method, with recoveries ranging from 82.70 to 113.48 %. The results correlated well with those obtained using HPLC. In conclusion, the developed method could be an alternative and sensitive method for the simultaneous detection of ENRO and FF in animal-derived foods.

Inhibiting the Otub1/phosphorylated STAT3 axis for the treatment of non-small cell lung cancer.

The transcription factor STAT3 is a promising target for the treatment of non-small cell lung cancer (NSCLC). STAT3 activity is mainly dependent on phosphorylation at tyrosine 705 (pSTAT3-Y705), but the modulation on pSTAT3-Y705 is elusive. By screening a library of deubiquitinases (Dubs), we found that the Otub1 increases STAT3 transcriptional activity. As a Dub, Otub1 binds to pSTAT3-Y705 and specifically abolishes its K48-linked ubiquitination, therefore preventing its degradation and promoting NSCLC cell survival. The Otub1/pSTAT3-Y705 axis could be a potential target for the treatment of NSCLC. To explore this concept, we screen libraries of FDA-approved drugs and natural products based on STAT3-recognition element-driven luciferase assay, from which crizotinib is found to block pSTAT3-Y705 deubiquitination and promotes its degradation. Different from its known action to induce ALK positive NSCLC cell apoptosis, crizotinib suppresses ALK-intact NSCLC cell proliferation and colony formation but not apoptosis. Furthermore, crizotinib also suppresses NSCLC xenograft growth in mice. Taken together, these findings identify Otub1 as the first deubiquitinase of pSTAT3-Y705 and provide that the Otub1/pSTAT3-Y705 axis is a promising target for the treatment of NSCLC.

Adapting nanopore sequencing basecalling models for modification detection via incremental learning and anomaly detection.

We leverage machine learning approaches to adapt nanopore sequencing basecallers for nucleotide modification detection. We first apply the incremental learning (IL) technique to improve the basecalling of modification-rich sequences, which are usually of high biological interest. With sequence backbones resolved, we further run anomaly detection (AD) on individual nucleotides to determine their modification status. By this means, our pipeline promises the single-molecule, single-nucleotide, and sequence context-free detection of modifications. We benchmark the pipeline using control oligos, further apply it in the basecalling of densely-modified yeast tRNAs and E.coli genomic DNAs, the cross-species detection of N6-methyladenosine (m6A) in mammalian mRNAs, and the simultaneous detection of N1-methyladenosine (m1A) and m6A in human mRNAs. Our IL-AD workflow is available at: https://github.com/wangziyuan66/IL-AD .

Inhibition of ACE2-S Protein Interaction by a Short Functional Peptide with a Boomerang Structure.

Considering the high evolutionary rate and great harmfulness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is imperative to develop new pharmacological antagonists. Human angiotensin-converting enzyme-2 (ACE2) functions as a primary receptor for the spike protein (S protein) of SARS-CoV-2. Thus, a novel functional peptide, KYPAY (K5), with a boomerang structure, was developed to inhibit the interaction between ACE2 and the S protein by attaching to the ACE2 ligand-binding domain (LBD). The inhibition property of K5 was evaluated via molecular simulations, cell experiments, and adsorption kinetics analysis. The molecular simulations showed that K5 had a high affinity for ACE2 but a low affinity for the cell membrane. The umbrella sampling (US) simulations revealed a significant enhancement in the binding potential of this functional peptide to ACE2. The fluorescence microscopy and cytotoxicity experiments showed that K5 effectively prevented the interaction between ACE2 and the S protein without causing any noticeable harm to cells. Further flow cytometry research indicated that K5 successfully hindered the interaction between ACE2 and the S protein, resulting in 78% inhibition at a concentration of 100 µM. This work offers an innovative perspective on the development of functional peptides for the prevention and therapy of SARS-CoV-2.

ZIF-8-based Nanoparticles for Inflammation Treatment and Oxidative Stress Reduction in Periodontitis.

Periodontitis, an inflammatory bone resorption disease associated with dental plaque, poses significant challenges for effective treatment. In this study, we developed Mino@ZIF-8 nanoparticles inspired by the periodontal microenvironment and the unique properties of zeolitic imidazolate framework 8, aiming to address the complex pathogenesis of periodontitis. Transcriptome analysis revealed the active engagement of Mino@ZIF-8 nanoparticles in innate and adaptive inflammatory host defense and cellular metabolic remodeling. Through sustained release of the anti-inflammatory and antibacterial agent minocycline hydrochloride (Mino) and the generation of Zn2+ with pro-antioxidant effects during degradation, Mino@ZIF-8 nanoparticles synergistically alleviate inflammation and oxidative damage. Notably, our study focuses on the pivotal role of zinc ions in mitochondrial oxidation protection. Under lipopolysaccharide (LPS) stimulation, periodontal ligament cells undergo a metabolic shift from oxidative phosphorylation (OXPHOS) to glycolysis, leading to reduced ATP production and increased reactive oxygen species levels. However, Zn2+ effectively rebalances the glycolysis-OXPHOS imbalance, restoring cellular bioenergetics, mitigating oxidative damage, rescuing impaired mitochondria, and suppressing inflammatory cytokine production through modulation of the AKT/GSK3ß/NRF2 pathway. This research not only presents a promising approach for periodontitis treatment but also offers novel therapeutic opportunities for zinc-containing materials, providing valuable insights into the design of biomaterials targeting cellular energy metabolism regulation.

Interplay among manures, vegetable types, and tetracycline resistance genes in rhizosphere microbiome.

The rapid global emergence of antibiotic resistance genes (ARGs) is a substantial public health concern. Livestock manure serves as a key reservoir for tetracycline resistance genes (TRGs), serving as a means of their transmission to soil and vegetables upon utilization as a fertilizer, consequently posing a risk to human health. The dynamics and transfer of TRGs among microorganisms in vegetables and fauna are being investigated. However, the impact of different vegetable species on acquisition of TRGs from various manure sources remains unclear. This study investigated the rhizospheres of three vegetables (carrots, tomatoes, and cucumbers) grown with chicken, sheep, and pig manure to assess TRGs and bacterial community compositions via qPCR and high-throughput sequencing techniques. Our findings revealed that tomatoes exhibited the highest accumulation of TRGs, followed by cucumbers and carrots. Pig manure resulted in the highest TRG levels, compared to chicken and sheep manure, in that order. Bacterial community analyses revealed distinct effects of manure sources and the selective behavior of individual vegetable species in shaping bacterial communities, explaining 12.2% of TRG variation. Firmicutes had a positive correlation with most TRGs and the intl1 gene among the dominant phyla. Notably, both the types of vegetables and manures significantly influenced the abundance of the intl1 gene and soil properties, exhibiting strong correlations with TRGs and elucidating 30% and 17.7% of TRG variance, respectively. Our study delineated vegetables accumulating TRGs from manure-amended soils, resulting in significant risk to human health. Moreover, we elucidated the pivotal roles of bacterial communities, soil characteristics, and the intl1 gene in TRG fate and dissemination. These insights emphasize the need for integrated strategies to reduce selection pressure and disrupt TRG transmission routes, ultimately curbing the transmission of tetracycline resistance genes to vegetables.

An Unfitted Finite Element Poisson-Boltzmann Solver with Automatic Resolving of Curved Molecular Surface.

So far, the existing Poisson-Boltzmann (PB) solvers that accurately take into account the interface jump conditions need a pregenerated body-fitted mesh (molecular surface mesh). However, qualified biomolecular surface meshing and its implementation into numerical methods remains a challenging and laborious issue, which practically hinders the progress of further developments and applications of a bunch of numerical methods in this field. In addition, even with a molecular surface mesh, it is only a low-order approximation of the original curved surface. In this article, an interface-penalty finite element method (IPFEM), which is a typical unfitted finite element method, is proposed to solve the Poisson-Boltzmann equation (PBE) without requiring the user to generate a molecular surface mesh. The Gaussian molecular surface is used to represent the molecular surface and can be automatically resolved with a high-order approximation within our method. Theoretical convergence rates of the IPFEM for the linear PB equation have been provided and are well validated on a benchmark problem with an analytical solution (we also noticed from numerical examples that the IPFEM has similar convergence rates for the nonlinear PBE). Numerical results on a set of different-sized biomolecules demonstrate that the IPFEM is numerically stable and accurate in the calculation of biomolecular electrostatic solvation energy.

A risk score for predicting in-stent restenosis in patients with premature acute myocardial infarction undergoing percutaneous coronary intervention with drug-eluting stent.

Background: This study aimed at developing and validating a risk score to predict in-stent restenosis (ISR) in patients with premature acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI) with drug-eluting stent (DES). Methods: This was a two-center retrospective study. A total of 2185 patients firstly diagnosed with premature AMI (age ≥18 years and <55 years in men, <65 years in women) from Xinjiang cohort were retrospectively analyzed. After filtering by exclusion criteria, patients were randomly divided into training cohort (n = 434) and internal validation cohort (n = 186) at a 7:3 ratio. Several candidate variables associated with ISR in the training cohort were assessed by the least absolute shrinkage and selection operator and logistic regression analysis. The ISR risk nomogram score based on the superior predictors was finally developed, and then validated in the internal validation cohort and in an independent Chengdu external validation cohort (n = 192). The higher total nomogram score, the greater the ISR risk. Results: The eight variables in the final risk nomogram score, cardiovascular-kidney-metabolic (CKM) score included age, diabetes mellitus (DM), body mass index (BMI), systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDLC), estimated glomerular filtration rate (eGFR), stent in left anterior descending coronary artery, minimum stent diameter <3 mm. The areas under the curve (AUC) and C-statistics [training cohort: 0.834 (95%CI: 0.787 to 0.882); internal validation cohort: 0.852 (95%CI: 0.784 to 0.921); Chengdu external validation cohort: 0.787 (95%CI: 0.692 to 0.882), respectively)] demonstrated the good discrimination of the CKM score. The Hosmer-Lemeshow test (χ2 = 7.86, P = 0.448; χ2 = 5.17, P = 0.740; χ2 = 6.35, P = 0.608, respectively) and the calibration curve confirmed the good calibration of the CKM score. Decision curve analysis (DCA) testified the clinical net benefit of the CKM score in the training and validation cohort. Conclusion: This study provided a well-developed and validated risk nomogram score, the CKM score to predict ISR in patients with premature AMI undergoing PCI with DES. Given that these variables are readily available and practical, the CKM score should be widely adopted for individualized assessment and management of premature AMI.

Global Research Trends and Focuses on Pierre Robin Sequence From 1992 to 2023: A Bibliometric Analysis of the Past 3 Decades.

There is currently a lack of scientific bibliometric analyses in the field of Pierre Robin sequence (PRS). Pierre Robin sequence is known for its clinical triad of micrognathia, glossoptosis, airway obstruction, and possible secondary cleft palate. These defects can lead to upper airway obstruction, sleep apnea, feeding difficulties, affect an individual's growth and development, education level, and in severe cases can be life-threatening. Through analysis of literature retrieved from the Web of Science Core Collection (WoSCC) database using Results Analysis and Citation Report and Citespace software, 933 original articles and reviews were included after manual screening. The overall trend for the number of annual publications and citations was increasing. On the basis of the analysis, airway evaluation and treatment, mandibular distraction osteogenesis (MDO), as well as descriptions of PRS characteristics have been the focus of research in this field. In addition, with advances in new technologies such as gene sequencing and expanding understanding of diseases among researchers, research on genetics and etiology related to PRS has become a growing trend.

Chronic Wound Image Augmentation and Assessment Using Semi-Supervised Progressive Multi-Granularity EfficientNet.

Goal: Augment a small, imbalanced, wound dataset by using semi-supervised learning with a secondary dataset. Then utilize the augmented wound dataset for deep learning-based wound assessment. Methods: The clinically-validated Photographic Wound Assessment Tool (PWAT) scores eight wound attributes: Size, Depth, Necrotic Tissue Type, Necrotic Tissue Amount, Granulation Tissue type, Granulation Tissue Amount, Edges, Periulcer Skin Viability to comprehensively assess chronic wound images. A small corpus of 1639 wound images labeled with ground truth PWAT scores was used as reference. A Semi-Supervised learning and Progressive Multi-Granularity training mechanism were used to leverage a secondary corpus of 9870 unlabeled wound images. Wound scoring utilized the EfficientNet Convolutional Neural Network on the augmented wound corpus. Results: Our proposed Semi-Supervised PMG EfficientNet (SS-PMG-EfficientNet) approach estimated all 8 PWAT sub-scores with classification accuracies and F1 scores of about 90% on average, and outperformed a comprehensive list of baseline models and had a 7% improvement over the prior state-of-the-art (without data augmentation). We also demonstrate that synthetic wound image generation using Generative Adversarial Networks (GANs) did not improve wound assessment. Conclusions: Semi-supervised learning on unlabeled wound images in a secondary dataset achieved impressive performance for deep learning-based wound grading.

High Strength and Shape Memory Spinal Fusion Device for Minimally Invasive Interbody Fusions.

Introduction: Lumbar interbody fusion is widely employed for both acute and chronic spinal diseases interventions. However, large incision created during interbody cage implantation may adversely impair spinal tissue and influence postoperative recovery. The aim of this study was to design a shape memory interbody fusion device suitable for small incision implantation. Methods: In this study, we designed and fabricated an intervertebral fusion cage that utilizes near-infrared (NIR) light-responsive shape memory characteristics. This cage was composed of bisphenol A diglycidyl ether, polyether amine D-230, decylamine and iron oxide nanoparticles. A self-hardening calcium phosphate-starch cement (CSC) was injected internally through the injection channel of the cage for healing outcome improvement. Results: The size of the interbody cage is reduced from 22 mm to 8.8 mm to minimize the incision size. Subsequent NIR light irradiation prompted a swift recovery of the cage shape within 5 min at the lesion site. The biocompatibility of the shape memory composite was validated through in vitro MC3T3-E1 cell (osteoblast-like cells) adhesion and proliferation assays and subcutaneous implantation experiments in rats. CSC was injected into the cage, and the relevant results revealed that CSC is uniformly dispersed within the internal space, along with the cage compressive strength increasing from 12 to 20 MPa. Conclusion: The results from this study thus demonstrated that this integrated approach of using a minimally invasive NIR shape memory spinal fusion cage with CSC has potential for lumbar interbody fusion.

Focuses, Developments, and Publication Trends in Facial Bone Aging and Related Fields: A Systematic Bibliometric Analysis (1990-2023).

There is a current lack of bibliometric analysis in facial bone aging and relevant fields. By providing clear and intuitive references, predictions, and guidance for future research, this study aims to fill the gap in the current field, summarize the related research, and guide the researchers' future work. Literature data were retrieved from the Web of Science Core Collection database. Results Analysis and Citation Report of Web of Science, and CiteSpace software were used to optimize the visualization results, including publication characteristics, disciplines, journals, literature, countries/regions, institutions, authors, research focuses, etc. A total of 277 publications were included after manual screening, and the overall trend of annual publications and citations was increasing. On the basis of the analysis, the characteristics of facial bone aging, aging of facial soft tissue, and facial rejuvenation have been the focuses of research in this field. As stem cell research advances and researchers, deepen their comprehension of facial bone aging, basic scientific research on facial bones has witnessed a growing trend.

Genetic variants in UNC93B1 predispose to childhood-onset systemic lupus erythematosus.

Rare genetic variants in toll-like receptor 7 (TLR7) are known to cause lupus in humans and mice. UNC93B1 is a transmembrane protein that regulates TLR7 localization into endosomes. In the present study, we identify two new variants in UNC93B1 (T314A, located proximally to the TLR7 transmembrane domain, and V117L) in a cohort of east Asian patients with childhood-onset systemic lupus erythematosus. The V117L variant was associated with increased expression of type I interferons and NF-κB-dependent cytokines in patient plasma and immortalized B cells. THP-1 cells expressing the variant UNC93B1 alleles exhibited exaggerated responses to stimulation of TLR7/-8, but not TLR3 or TLR9, which could be inhibited by targeting the downstream signaling molecules, IRAK1/-4. Heterozygous mice expressing the orthologous Unc93b1V117L variant developed a spontaneous lupus-like disease that was more severe in homozygotes and again hyperresponsive to TLR7 stimulation. Together, this work formally identifies genetic variants in UNC93B1 that can predispose to childhood-onset systemic lupus erythematosus.