Deep learning for virtual orthodontic bracket removal: tool establishment and application.

OBJECTIVE: We aimed to develop a tool for virtual orthodontic bracket removal based on deep learning algorithms for feature extraction from bonded teeth and to demonstrate its application in a bracket position assessment scenario. MATERIALS AND METHODS: Our segmentation network for virtual bracket removal was trained using dataset A, containing 978 bonded teeth, 20 original teeth, and 20 brackets generated by scanners. The accuracy and segmentation time of the network were tested by dataset B, which included an additional 118 bonded teeth without knowing the original tooth morphology. This tool was then applied for bracket position assessment. The clinical crown center, bracket center, and orientations of separated teeth and brackets were extracted for analyzing the linear distribution and angular deviation of bonded brackets. RESULTS: This tool performed virtual bracket removal in 2.9 ms per tooth with accuracies of 98.93% and 97.42% (P < 0.01) in datasets A and B, respectively. The tooth surface and bracket characteristics were extracted and used to evaluate the results of manually bonded brackets by 49 orthodontists. Personal preferences for bracket angulation and bracket distribution were displayed graphically and tabularly. CONCLUSIONS: The tool's efficiency and precision are satisfactory, and it can be operated without original tooth data. It can be used to display the bonding deviation in the bracket position assessment scenario. CLINICAL SIGNIFICANCE: With the aid of this tool, unnecessary bracket removal can be avoided when evaluating bracket positions and modifying treatment plans. It has the potential to produce retainers and orthodontic devices prior to tooth debonding.

Sarcopenia as a risk factor of progression-free survival in patients with metastases: a systematic review and meta-analysis.

BACKGROUND: Metastasis of cancer causes more than 90% of cancer deaths and is severely damaging to human health. In recent years, several studies have linked sarcopenia to shorter survival in patients with metastatic cancer. Several predictive models exist to predict mortality in patients with metastatic cancer, but have reported limited accuracy. METHODS: We systematically searched Medline, EMBASE, and the Cochrane Library for articles published on or before October 14, 2022. Pooled Hazard Ratio (HR) estimates with 95% confidence intervals (CIs) were calculated using a random effects model. The primary outcome was an increased risk of death or tumor progression in patients with metastatic cancer, which is expressed as progression-free survival (PFS). In addition, we performed subgroup analyses and leave-one-out sensitivity analyses to explore the main sources of heterogeneity and the stability of the results. RESULTS: Sixteen retrospective cohort studies with 1,675 patients were included in the 888 papers screened. The results showed that sarcopenia was associated with lower progression-free survival (HR = 1.56, 95% CI = 1.19-2.03, I2 = 76.3%, P < 0.001). This result was further confirmed by trim-and-fill procedures and leave-one-out sensitivity analysis. CONCLUSIONS: This study suggests that sarcopenia may be a risk factor for reduced progression-free survival in patients with metastatic cancer. Further studies are still needed to explain the reason for this high heterogeneity in outcome. TRIAL REGISTRATION: CRD42022325910.

Neuroprotective Roles of Apelin-13 in Neurological Diseases.

Apelin is a natural ligand for the G protein-coupled receptor APJ, and the apelin/APJ system is widely distributed in vivo. Among the apelin family, apelin-13 is the major apelin isoform in the central nervous system and cardiovascular system, and is involved in the regulation of various physiopathological mechanisms such as apoptosis, neuroinflammation, angiogenesis, and oxidative stress. Apelin is currently being extensively studied in the nervous system, and apelin-13 has been shown to be associated with the onset and progression of a variety of neurological disorders, including stroke, neurodegenerative diseases, epilepsy, spinal cord injury (SCI), and psychiatric diseases. This study summarizes the pathophysiological roles of apelin-13 in the development and progression of neurological related diseases.

Single Molecule Ratcheting Motion of Peptides in a Mycobacterium smegmatis Porin A (MspA) Nanopore.

Diverse functions of proteins, including synthesis, catalysis, and signaling, result from their highly variable amino acid sequences. The technology allowing for direct analysis of protein sequences, however, is still unsatisfactory. Recent developments of nanopore sequencing of DNA or RNA have motivated attempts to realize nanopore sequencing of peptides in a similar manner. The core challenge has been to achieve a controlled ratcheting motion of the target peptide, which is currently restricted to a limited choice of compatible enzymes. By constructing peptide-oligonucleotide conjugates (POCs) and measurements with nanopore-induced phase-shift sequencing (NIPSS), direct observation of the ratcheting motion of peptides has been successfully achieved. The generated events show a clear sequence dependence on the peptide that is being tested. The method is compatible with peptides with either a conjugated N- or C-terminus. The demonstrated results suggest a proof of concept of nanopore sequencing of peptide and can be useful for peptide fingerprinting.

Using deep reinforcement learning to speed up collective cell migration.

BACKGROUND: Collective cell migration is a significant and complex phenomenon that affects many basic biological processes. The coordination between leader cell and follower cell affects the rate of collective cell migration. However, there are still very few papers on the impacts of the stimulus signal released by the leader on the follower. Tracking cell movement using 3D time-lapse microscopy images provides an unprecedented opportunity to systematically study and analyze collective cell migration. RESULTS: Recently, deep reinforcement learning algorithms have become very popular. In our paper, we also use this method to train the number of cells and control signals. By experimenting with single-follower cell and multi-follower cells, it is concluded that the number of stimulation signals is proportional to the rate of collective movement of the cells. Such research provides a more diverse approach and approach to studying biological problems. CONCLUSION: Traditional research methods are always based on real-life scenarios, but as the number of cells grows exponentially, the research process is too time consuming. Agent-based modeling is a robust framework that approximates cells to isotropic, elastic, and sticky objects. In this paper, an agent-based modeling framework is used to establish a simulation platform for simulating collective cell migration. The goal of the platform is to build a biomimetic environment to demonstrate the importance of stimuli between the leading and following cells.

Attention-based recurrent neural network for influenza epidemic prediction.

BACKGROUND: Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat to the society, precise real-time forecasting of influenza outbreaks is of great value to our public. RESULTS: In this paper, we propose a new deep neural network structure that forecasts a real-time influenza-like illness rate (ILI%) in Guangzhou, China. Long short-term memory (LSTM) neural networks is applied to precisely forecast accurateness due to the long-term attribute and diversity of influenza epidemic data. We devise a multi-channel LSTM neural network that can draw multiple information from different types of inputs. We also add attention mechanism to improve forecasting accuracy. By using this structure, we are able to deal with relationships between multiple inputs more appropriately. Our model fully consider the information in the data set, targetedly solving practical problems of the Guangzhou influenza epidemic forecasting. CONCLUSION: We assess the performance of our model by comparing it with different neural network structures and other state-of-the-art methods. The experimental results indicate that our model has strong competitiveness and can provide effective real-time influenza epidemic forecasting.

Nanopore Sequencing Accurately Identifies the Mutagenic DNA Lesion O6 -Carboxymethyl Guanine and Reveals Its Behavior in Replication.

O6 -carboxymethylguanine (O6 -CMG) is a highly mutagenic alkylation product of DNA, triggering transition mutations relevant to gastrointestinal cancer. However, precise localization of a single O6 -CMG with conventional sequencing platforms is challenging. Here nanopore sequencing (NPS), which directly senses single DNA bases according to their physiochemical properties, was employed to detect O6 -CMG. A unique O6 -CMG signal was observed during NPS and a single-event call accuracy of >95 % was achieved. Moreover, O6 -CMG was found to be a replication obstacle for Phi29 DNA polymerase (Phi29 DNAP), suggesting this lesion could cause DNA sequencing biases in next generation sequencing (NGS) approaches.

Polytypic InP nanolaser monolithically integrated on (001) silicon.

On-chip optical interconnects still miss a high-performance laser monolithically integrated on silicon. Here, we demonstrate a silicon-integrated InP nanolaser that operates at room temperature with a low threshold of 1.69 pJ and a large spontaneous emission factor of 0.04. An epitaxial scheme to grow relatively thick InP nanowires on (001) silicon is developed. The zincblende/wurtzite crystal phase polytypism and the formed type II heterostructures are found to promote lasing over a wide wavelength range.

TAK1 in Vascular Signaling: "Friend or Foe"?

The maintenance of normal vascular function and homeostasis is largely dependent on the signaling mechanisms that occur within and between cells of the vasculature. TGF-ß-activated kinase 1 (TAK1), a multifaceted signaling molecule, has been shown to play critical roles in various tissue types. Although the precise function of TAK1 in the vasculature remains largely unknown, emerging evidence suggests its potential involvement in both physiological and pathological processes. A comprehensive search strategy was employed to identify relevant studies, PubMed, Web of Science, and other relevant databases were systematically searched using keywords related to TAK1, TABs and MAP3K7.In this review, we discussed the role of TAK1 in vascular signaling, with a focus on its function, activation, and related signaling pathways. Specifically, we highlight the TA1-TABs complex is a key factor, regulating vascular smooth muscle cells (VSMCs) and endothelial cells (ECs) involved in the processes of inflammation, vascular proliferation and angiogenesis. This mini review aims to elucidate the evidence supporting TAK1 signaling in the vasculature, in order to better comprehend its beneficial and potential harmful effects upon TAK1 activation in vascular tissue.

A review of lactate-lactylation in malignancy: its potential in immunotherapy.

Lactic acid was formerly regarded as a byproduct of metabolism. However, extensive investigations into the intricacies of cancer development have revealed its significant contributions to tumor growth, migration, and invasion. Post-translational modifications involving lactate have been widely observed in histone and non-histone proteins, and these modifications play a crucial role in regulating gene expression by covalently attaching lactoyl groups to lysine residues in proteins. This discovery has greatly enhanced our comprehension of lactic acid's involvement in disease pathogenesis. In this article, we provide a comprehensive review of the intricate relationship between lactate and tumor immunity, the occurrence of lactylation in malignant tumors, and the exploitation of targeted lactate-lactylation in tumor immunotherapy. Additionally, we discuss future research directions, aiming to offer novel insights that could inform the investigation, diagnosis, and treatment of related diseases.

Automatic Lenke classification of adolescent idiopathic scoliosis with deep learning.

Purpose: The Lenke classification system is widely utilized as the preoperative evaluation protocol for adolescent idiopathic scoliosis (AIS). However, manual measurement is susceptible to observer-induced variability, which consequently impacts the evaluation of progression. The goal of this investigation was to develop an automated Lenke classification system utilizing innovative deep learning algorithms. Methods: Using the database from the First Affiliated Hospital of Sun Yat-sen University, the whole spinal x-rays images were retrospectively collected. Specifically, images collection was divided into AIS and control group. The control group consisted of individuals who underwent routine health checks and did not have scoliosis. Afterwards, relative features of all images were annotated. Deep learning was implemented through the utilization of the key-point based detection method to realize the vertebral detection, and Cobb angle measurement and scoliosis classification were performed based on relevant standards. Besides, the segmentation method was employed to achieve the recognition of lumbar vertebral pedicle to determine the type of lumbar spine modifier. Finally, the model performance was further quantitatively analyzed. Results: In the study, a total of 2082 spinal x-ray images were collected from 407 AIS patients and 227 individuals in the control group. The model for vertebral detection achieved an F1-score of 0.809 for curve type evaluation and an F1-score of 0.901 for thoracic sagittal profile. The intraclass correlation efficient (ICC) of the Cobb angle measurement was 0.925. In the analysis of performance for vertebra pedicle segmentation model, the F1-score of lumbar modification profile was 0.942, the intersection over union (IOU) of the target pixels was 0.827, and the Hausdorff distance (HD) was 6.565 ± 2.583 mm. Specifically, the F1-score for ultimate Lenke type classifier was 0.885. Conclusions: This study has constructed an automated Lenke classification system by employing the deep learning networks to achieve the recognition pattern and feature extraction. Our models require further validation in additional cases in the future.

Mechanisms and translational applications of regeneration in limbs: From renewable animals to humans.

BACKGROUND: The regenerative capacity of organisms declines throughout evolution, and mammals lack the ability to regenerate limbs after injury. Past approaches to achieving successful restoration through pharmacological intervention, tissue engineering, and cell therapies have faced significant challenges. OBJECTIVES: This review aims to provide an overview of the current understanding of the mechanisms behind animal limb regeneration and the successful translation of these mechanisms for human tissue regeneration. RESULTS: Particular attention was paid to the Mexican axolotl (Ambystoma mexicanum), the only adult tetrapod capable of limb regeneration. We will explore fundamental questions surrounding limb regeneration, such as how amputation initiates regeneration, how the limb knows when to stop and which parts to regenerate, and how these findings can apply to mammalian systems. CONCLUSIONS: Given the urgent need for regenerative therapies to treat conditions like diabetic foot ulcers and trauma survivors, this review provides valuable insights and ideas for researchers, clinicians, and biomedical engineers seeking to facilitate the regeneration process or elicit full regeneration from partial regeneration events.

Superconductivity in the High-Entropy Ceramics Ti0.2 Zr0.2 Nb0.2 Mo0.2 Ta0.2 Cx with Possible Nontrivial Band Topology.

Topological superconductors have drawn significant interest from the scientific community due to the accompanying Majorana fermions. Here, the discovery of electronic structure and superconductivity (SC) in high-entropy ceramics Ti0.2 Zr0.2 Nb0.2 Mo0.2 Ta0.2 Cx (x = 1 and 0.8) combined with experiments and first-principles calculations is reported. The Ti0.2 Zr0.2 Nb0.2 Mo0.2 Ta0.2 Cx high-entropy ceramics show bulk type-II SC with Tc ≈ 4.00 K (x = 1) and 2.65 K (x = 0.8), respectively. The specific heat jump (∆C/γTc ) is equal to 1.45 (x = 1) and 1.52 (x = 0.8), close to the expected value of 1.43 for the BCS superconductor in the weak coupling limit. The high-pressure resistance measurements show a robust SC against high physical pressure in Ti0.2 Zr0.2 Nb0.2 Mo0.2 Ta0.2 C, with a slight Tc variation of 0.3 K within 82.5 GPa. Furthermore, the first-principles calculations indicate that the Dirac-like point exists in the electronic band structures of Ti0.2 Zr0.2 Nb0.2 Mo0.2 Ta0.2 C, which is potentially a topological superconductor. The Dirac-like point is mainly contributed by the d orbitals of transition metals M and the p orbitals of C. The high-entropy ceramics provide an excellent platform for the fabrication of novel quantum devices, and the study may spark significant future physics investigations in this intriguing material.

Manganese Enhances the Osteogenic Effect of Silicon-Hydroxyapatite Nanowires by Targeting T Lymphocyte Polarization.

Biomaterials encounter considerable challenges in extensive bone defect regeneration. The amelioration of outcomes may be attainable through the orchestrated modulation of both innate and adaptive immunity. Silicon-hydroxyapatite, for instance, which solely focuses on regulating innate immunity, is inadequate for long-term bone regeneration. Herein, extra manganese (Mn)-doping is utilized for enhancing the osteogenic ability by mediating adaptive immunity. Intriguingly, Mn-doping engenders heightened recruitment of CD4+ T cells to the bone defect site, concurrently manifesting escalated T helper (Th) 2 polarization and an abatement in Th1 cell polarization. This consequential immune milieu yields a collaborative elevation of interleukin 4, secreted by Th2 cells, coupled with attenuated interferon gamma, secreted by Th1 cells. This orchestrated interplay distinctly fosters the osteogenesis of bone marrow stromal cells and effectuates consequential regeneration of the mandibular bone defect. The modulatory mechanism of Th1/Th2 balance lies primarily in the indispensable role of manganese superoxide dismutase (MnSOD) and the phosphorylation of adenosine 5'-monophosphate-activated protein kinase (AMPK). In conclusion, this study highlights the transformative potential of Mn-doping in amplifying the osteogenic efficacy of silicon-hydroxyapatite nanowires by regulating T cell-mediated adaptive immunity via the MnSOD/AMPK pathway, thereby creating an anti-inflammatory milieu favorable for bone regeneration.

Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma.

Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database to provide help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. Based on the DEGs of each cluster acquired from single-cell data, immune cell marker genes, and ligand-receptor gene data, we constructed a multilayer network. Then, the genes in the network and the genes in TCGA were used to construct the WGCNA network, which screened out prognosis-associated genes for subsequent analysis. Finally, a prognostic risk scoring model was obtained, and CPTAC data showed that the effectiveness of this model was good. A nomogram based on the predictive model for predicting the overall survival was established, and internal validation was performed well. Our findings suggest that the predictive model built and based on the immune cell scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice.

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer.

Immunotherapy has become a revolutionary treatment for cancer and brought new vitality to tumor immunity. Bone metastases are the most prevalent metastatic site for advanced prostate cancer (PCa). Therefore, finding new immunotherapy targets in PCa patients with bone metastasis is urgently needed. We conducted an elaborative bioinformatics study of immune-related genes (IRGs) and tumor-infiltrating immune cells (TIICs) in PCa bone metastases. Databases were integrated to obtain RNA-sequencing data and clinical prognostic information. Univariate and multivariate Cox regression analyses were conducted to construct an overall survival (OS) prediction model. GSE32269 was analyzed to acquire differentially expressed IRGs. The OS prediction model was established by employing six IRGs (MAVS, HSP90AA1, FCGR3A, CTSB, FCER1G, and CD4). The CIBERSORT algorithm was adopted to assess the proportion of TIICs in each group. Furthermore, Transwell, MTT, and wound healing assays were employed to determine the effect of MAVS on PCa cells. High-risk patients had worse OS compared to the low-risk patients in the training and validation cohorts. Meanwhile, clinically practical nomograms were generated using these identified IRGs to predict the 3- and 5-year survival rates of patients. The infiltration percentages of some TIICs were closely linked to the risk score of the OS prediction model. Some tumor-infiltrating immune cells were related to the OS. FCGR3A was closely correlated with some TIICs. In vitro experiments verified that up-regulation of MAVS suppressed the proliferation and metastatic abilities of PCa cells. Our work presented a thorough interpretation of TIICs and IRGs for illustrating and discovering new potential immune checkpoints in bone metastases of PCa.

[Study on promoting bone formation in osteoporotic zebrafish by lithium-doped hydroxyapatite nanowires].

PURPOSE: To observe the regulatory effect of lithium-doped hydroxyapatite nanowires on bone metabolism in osteoporotic zebrafish induced by dexamethasone. METHODS: Pure hydroxyapatite nanowires(nHA) and hydroxyapatite nanowires doped with 10% lithium ions (Li-nHA) were prepared by using hydrothermal method, and then material characterization was performed. The juvenile zebrafish cultured for 3 days(3dpf) were selected and co-cultured with nHA and Li-nHA extracts up to 7dpf. A negative(0.1% DMSO) control group was set up and transgenic zebrafish Tg(ola.sp7:nlsGFP) was used to select the best concentration for promoting bone formation. The osteoporotic zebrafish were induced by dexamethasone and incubated with nHA and Li-nHA extracts. The wild-type zebrafish was stained with alizarin red and the osteogenic differentiation was observed in transgenic zebrafish. Real-time quantitative PCR was adopted to detect osteogenic maker genes, such as zinc finger transcription factor (SP7), alkaline phosphatase (ALP), osteoprotegerin (OPG), Runt related transcription factor 2(Runx2) and osteocalcin (OCN). Statistical analysis was performed with GraphPad Prism 9.3 software. RESULTS: nHA and Li-nHA promoted bone formation and up-regulated expression levels of ALP, OCN, Runx2, SP7 and OPG of osteoporotic zebrafish. Compared with nHA, Li-nHA significantly increased the mineralization specific staining area and cumulative optical density of zebrafish bone, and the expression of osteogenic maker genes was also significantly increased. CONCLUSIONS: Doping lithium ions in nano hydroxyapatite can enhance its osteoinductive properties, and Li-nHA can effectively improve bone formation of osteoporotic zebrafish.

Risk factors for cardiovascular adverse events from immune checkpoint inhibitors.

Immune-related adverse events (irAEs), including skin injury, liver and kidney injury, colitis, as well as cardiovascular adverse events, are a series of complications arising during the treatment of immune checkpoint inhibitors (ICIs). Cardiovascular events are the most urgent and the most critical, as they can end life in a short period of time. With the widespread use of ICIs, the number of immune-related cardiovascular adverse events (irACEs) induced by ICIs has increased. More attention has been paid to irACEs, especially regarding cardiotoxicity, the pathogenic mechanism, diagnosis and treatment. This review aims to assess the risk factors for irACEs, to raise awareness and help with the risk assessment of irACEs at an early stage.

Dynamic network biomarker identifies cdkn1a-mediated bone mineralization in the triggering phase of osteoporosis.

The identification of predictive markers to determine the triggering phase prior to the onset of osteoporosis is essential to mitigate further irrevocable deterioration. To determine the early warning signs before osteoporosis, we used the dynamic network biomarker (DNB) approach to analyze time-series gene expression data in a zebrafish osteoporosis model, which revealed that cyclin-dependent kinase inhibitor 1 A (cdkn1a) is a core DNB. We found that cdkn1a negatively regulates osteogenesis, as evidenced by loss-of-function and gain-of-function studies. Specifically, CRISPR/Cas9-mediated cdkn1a knockout in zebrafish significantly altered skeletal development and increased bone mineralization, whereas inducible cdkn1a expression significantly contributed to osteoclast differentiation. We also found several mechanistic clues that cdkn1a participates in osteoclast differentiation by regulating its upstream signaling cascades. To summarize, in this study, we provided new insights into the dynamic nature of osteoporosis and identified cdkn1a as an early-warning signal of osteoporosis onset.

Senolytic Treatment Improve Small Intestine Regeneration in Aging.

Aging induces a series of alterations, specifically a decline in the stature and number of villi and crypts in the small intestine, thus compromising the absorbent capability of the villi. This investigation employed a senolytic combination of dasatinib and quercetin (D+Q) to examine its impact on the intestinal tract of elderly mice. Our findings demonstrate that D+Q treatment leads to a decrease in the expression of p21, p16, and Ki67, while concurrently triggering removal of apoptotic cells within the villi. Additionally, D+Q treatment exhibits the ability to promote growth in both the height and quantity of villi and crypts, along with stimulating nitric oxide (NO) production in aged mice. The study presented a model to assess strategies to alleviate age-related senescence in the intestinal tract of elderly mice. Importantly, D+Q showcases promising potential in enhancing intestinal functionality within the aging.