Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning.

Background: Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Leveraging the advancements in metagenomic next-generation sequencing (mNGS) technology alongside the emergence of machine learning, it is now viable to compare the attributes of lower respiratory tract microbial communities among patients across diverse age groups, diseases, and infection types. Method: We collected bronchoalveolar lavage fluid samples from 138 patients diagnosed with lower respiratory tract infections and conducted mNGS to characterize the lung microbiota. Employing various machine learning algorithms, we investigated the correlation of key bacteria in patients with concurrent bronchiectasis and developed a predictive model for hospitalization duration based on these identified key bacteria. Result: We observed variations in microbial communities across different age groups, diseases, and infection types. In the elderly group, Pseudomonas aeruginosa exhibited the highest relative abundance, followed by Corynebacterium striatum and Acinetobacter baumannii. Methylobacterium and Prevotella emerged as the dominant genera at the genus level in the younger group, while Mycobacterium tuberculosis and Haemophilus influenzae were prevalent species. Within the bronchiectasis group, dominant bacteria included Pseudomonas aeruginosa, Haemophilus influenzae, and Klebsiella pneumoniae. Significant differences in the presence of Pseudomonas phage JBD93 were noted between the bronchiectasis group and the control group. In the group with concomitant fungal infections, the most abundant genera were Acinetobacter and Pseudomonas, with Acinetobacter baumannii and Pseudomonas aeruginosa as the predominant species. Notable differences were observed in the presence of Human gammaherpesvirus 4, Human betaherpesvirus 5, Candida albicans, Aspergillus oryzae, and Aspergillus fumigatus between the group with concomitant fungal infections and the bacterial group. Machine learning algorithms were utilized to select bacteria and clinical indicators associated with hospitalization duration, confirming the excellent performance of bacteria in predicting hospitalization time. Conclusion: Our study provided a comprehensive description of the microbial characteristics among patients with lower respiratory tract infections, offering insights from various perspectives. Additionally, we investigated the advanced predictive capability of microbial community features in determining the hospitalization duration of these patients.

P-doped spherical hard carbon with high initial coulombic efficiency and enhanced capacity for sodium ion batteries.

Hard carbon (HC) is one of the most promising anode materials for sodium-ion batteries (SIBs) due to its cost-effectiveness and low-voltage plateau capacity. Heteroatom doping is considered as an effective strategy to improve the sodium storage capacity of HC. However, most of the previous heteroatom doping strategies are performed at a relatively low temperature, which could not be utilized to raise the low-voltage plateau capacity. Moreover, extra doping of heteroatoms could create new defects, leading to a low initial coulombic efficiency (ICE). Herein, we propose a repair strategy based on doping a trace amount of P to achieve a high capacity along with a high ICE. By employing the cross-linked interaction between glucose and phytic acid to achieve the in situ P doped spherical hard carbon, the obtained PHC-0.2 possesses a large interlayer space that facilitates Na+ storage and transportation. In addition, doping a suitable amount of P could repair some defects in carbon layers. When used as an anode material for SIBs, the PHC-0.2 exhibits an enhanced reversible capacity of 343 mA h g-1 at 20 mA g-1 with a high ICE of 92%. Full cells consisting of a PHC-0.2 anode and a Na2Fe0.5Mn0.5[Fe(CN)6] cathode exhibited an average potential of 3.1 V with an initial discharge capacity of 255 mA h g-1 and an ICE of 85%. The full cell displays excellent cycling stability with a capacity retention of 80.3% after 170 cycles. This method is simple and low-cost, which can be extended to other energy storage materials.

Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)，and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.

Emodin alleviates intestinal ischemia/reperfusion-induced lung injury by upregulating HO-1 expression via PI3K/AkT pathway.

BACKGROUND: Emodin, a natural anthraquinone derivative found in various Chinese medicinal herbs, has been proved to be an effective therapeutic agent in the treatment of many diseases. However, its effect on lung injury after intestinal ischemia/reperfusion injury remains unknown. This research was designed to investigate whether emodin protects against intestinal ischemia/reperfusion-induced lung injury and to elucidate the underlying molecular mechanisms in vivo and in vitro. METHODS: Intestinal ischemia/reperfusion injury was induced by occluding the superior mesenteric artery in mice, and mouse lung epithelial-12 cells were subjected to oxygen-glucose deprivation and reoxygenation to establish an in vitro model. RESULTS: Our data indicated that emodin treatment reduced intestinal ischemia/reperfusion-induced oxidative stress, inflammation and apoptosis in lung tissues and alleviated lung injury. However, the protective effects of emodin on intestinal ischemia/reperfusion-induced lung injury were reversed by the protein kinase B inhibitor triciribine or the heme oxygenase-1 inhibitor tin protoporphyrin IX. The protein kinase inhibitor triciribine also downregulated the expression of heme oxygenase-1. CONCLUSION: In conclusion, our data suggest that emodin treatment protects against intestinal ischemia/reperfusion-induced lung injury by enhancing heme oxygenase-1 expression via activation of the PI3K/protein kinase pathway. Emodin may act as a potential therapeutic agent for the prevention and treatment of lung injury induced by intestinal ischemia/reperfusion.

A user-friendly visual brain-computer interface based on high-frequency steady-state visual evoked fields recorded by OPM-MEG.

Objective. Magnetoencephalography (MEG) shares a comparable time resolution with electroencephalography. However, MEG excels in spatial resolution, enabling it to capture even the subtlest and weakest brain signals for brain-computer interfaces (BCIs). Leveraging MEG's capabilities, specifically with optically pumped magnetometers (OPM-MEG), proves to be a promising avenue for advancing MEG-BCIs, owing to its exceptional sensitivity and portability. This study harnesses the power of high-frequency steady-state visual evoked fields (SSVEFs) to build an MEG-BCI system that is flickering-imperceptible, user-friendly, and highly accurate.Approach.We have constructed a nine-command BCI that operates on high-frequency SSVEF (58-62 Hz with a 0.5 Hz interval) stimulation. We achieved this by placing the light source inside and outside the magnetic shielding room, ensuring compliance with non-magnetic and visual stimulus presentation requirements. Five participants took part in offline experiments, during which we collected six-channel multi-dimensional MEG signals along both the vertical (Z-axis) and tangential (Y-axis) components. Our approach leveraged the ensemble task-related component analysis algorithm for SSVEF identification and system performance evaluation.Main Results.The offline average accuracy of our proposed system reached an impressive 92.98% when considering multi-dimensional conjoint analysis using data from both theZandYaxes. Our method achieved a theoretical average information transfer rate (ITR) of 58.36 bits min-1with a data length of 0.7 s, and the highest individual ITR reached an impressive 63.75 bits min-1.Significance.This study marks the first exploration of high-frequency SSVEF-BCI based on OPM-MEG. These results underscore the potential and feasibility of MEG in detecting subtle brain signals, offering both theoretical insights and practical value in advancing the development and application of MEG in BCI systems.

Dual-Adaptive Heterojunction Synaptic Transistors for Efficient Machine Vision in Harsh Lighting Conditions.

Photoadaptive synaptic devices enable in-sensor processing of complex illumination scenes, while second-order adaptive synaptic plasticity improves learning efficiency by modifying the learning rate in a given environment. The integration of above adaptations in one phototransistor device will provide opportunities for developing high-efficient machine vision system. Here, a dually adaptable organic heterojunction transistor as a working unit in the system, which facilitates precise contrast enhancement and improves convergence rate under harsh lighting conditions, is reported. The photoadaptive threshold sliding originates from the bidirectional photoconductivity caused by the light intensity-dependent photogating effect. Metaplasticity is successfully implemented owing to the combination of ambipolar behavior and charge trapping effect. By utilizing the transistor array in a machine vision system, the details and edges can be highlighted in the 0.4% low-contrast images, and a high recognition accuracy of 93.8% with a significantly promoted convergence rate by about 5 times are also achieved. These results open a strategy to fully implement metaplasticity in optoelectronic devices and suggest their vision processing applications in complex lighting scenes.

A planar electronic acceptor motif contributing to NIR-II AIEgen with combined imaging and therapeutic applications.

Designing molecules with donor-acceptor-donor (D-A-D) architecture plays an important role in obtaining second near-infrared region (NIR-II, 1000-1700 nm) fluorescent dyes for biomedical applications; however, this always comes with a challenge due to very limited electronic acceptors. On the other hand, to endow NIR-II fluorescent dyes with combined therapeutic applications, trivial molecular design is indispensable. Herein, we propose a pyrazine-based planar electronic acceptor with a strong electron affinity, which can be used to develop NIR-II fluorescent dyes. By structurally attaching two classical triphenylamine electronic donors to it, a basic D-A-D module, namely Py-NIR, can be generated. The planarity of the electronic acceptor is crucial to induce a distinct NIR-II emission peaking at ∼1100 nm. The unique construction of the electronic acceptor can cause a twisted and flexible molecular conformation by the repulsive effect between the donors, which is essential to the aggregation-induced emission (AIE) property. The tuned intramolecular motions and twisted D-A pair brought by the electronic acceptor can lead to a remarkable photothermal conversion with an efficiency of 56.1% and induce a type I photosensitization with a favorable hydroxyl radical (OH˙) formation. Note that no additional measures are adopted in the molecular design, providing an ideal platform to realize NIR-II fluorescent probes with synergetic functions based on such an acceptor. Besides, the nanoparticles of Py-NIR can exhibit excellent NIR-II fluorescence imaging towards orthotopic 4T1 breast tumors in living mice with a high sensitivity and contrast. Combined with photothermal imaging and photoacoustic imaging caused by the thermal effect, the imaging-guided photoablation of tumors can be well performed. Our work has created a new opportunity to develop NIR-II fluorescent probes for accelerating biomedical applications.

The epigenetic regulators EP300/CREBBP represent promising therapeutic targets in MLL-rearranged acute myeloid leukemia.

Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangements (MLL-r) is an aggressive subtype of blood cancer with dismal prognosis, underscoring the urgent need for novel therapeutic strategies. E1A-binding protein (EP300) and CREB-binding protein (CREBBP) function as essential transcriptional coactivators and acetyltransferases, governing leukemogenesis through diverse mechanisms. Targeting EP300/CREBBP holds great promise for treating leukemia with some certain cytogenetic abnormalities. Here, we demonstrated that EP300 and CREBBP are core epigenetic regulators in the pathogenesis of MLL-r AML through assaying the transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Knocking-out EP300/CREBBP and inhibitor (A-485) treatment depressed the MLL-r cells proliferation, while the MLL wild-type cells remained uninfluenced. We found that the CDK4/RB/E2F axis was downregulated specifically in MLL-r AML cell after A-485 treatment by RNA-seq, western blot and cut-tag analyses. EP300/CREBBP inhibitor selectively exerted potent anti-leukemia activity through blocking the MLL-r-BET complex binding to H3K27Ac modification on critical genes loci, distinct from global histone acetylation. Collectively, our study identified EP300/CREBBP as a critical epigenetic driver of MLL-r leukemia and validated their therapeutic potential through targeting inhibition, offering a promising avenue for improving clinical outcomes in this aggressive leukemia.

HO-1 upregulation promotes mitophagy-dependent ferroptosis in PM2.5-exposed hippocampal neurons.

Fine particulate matter (PM2.5) has been extensively implicated in the pathogenesis of neurodevelopmental disorders, but the underlying mechanism remains unclear. Recent studies have revealed that PM2.5 plays a role in regulating iron metabolism and redox homeostasis in the brain, which is closely associated with ferroptosis. In this study, the role and underlying mechanism of ferroptosis in PM2.5-induced neurotoxicity were investigated in mice, primary hippocampal neurons, and HT22 cells. Our findings demonstrated that exposure to PM2.5 could induce abnormal behaviors, neuroinflammation, and neuronal loss in the hippocampus of mice. These effects may be attributed to ferroptosis induced by PM2.5 exposure in hippocampal neurons. RNA-seq analysis revealed that the upregulation of iron metabolism-related protein Heme Oxygenase 1 (HO-1) and the activation of mitophagy might play key roles in PM2.5-induced ferroptosis in HT22 cells. Subsequent in vitro experiments showed that PM2.5 exposure significantly upregulated HO-1 in primary hippocampal neurons and HT22 cells. Moreover, PM2.5 exposure activated mitophagy in HT22 cells, leading to the loss of mitochondrial membrane potential, alterations in the expression of autophagy-related proteins LC3, P62, and mTOR, as well as an increase in mitophagy-related protein PINK1 and PARKIN. As a heme-degradation enzyme, the upregulation of HO-1 promotes the release of excess iron, genetically inhibiting the upregulation of HO-1 in HT22 cells could prevent both PM2.5-induced mitophagy and ferroptosis. Furthermore, pharmacological inhibition of mitophagy in HT22 cells reduced levels of ferrous ions and lipid peroxides, thereby preventing ferroptosis. Collectively, this study demonstrates that HO-1 mediates PM2.5-induced mitophagy-dependent ferroptosis in hippocampal neurons, and inhibiting mitophagy or ferroptosis may be a key therapeutic target to ameliorate neurotoxicity following PM2.5 exposure.

An Artificial Enzyme for Asymmetric Nitrocyclopropanation of α,ß-Unsaturated Aldehydes-Design and Evolution.

The introduction of an abiological catalytic group into the binding pocket of a protein host allows for the expansion of enzyme chemistries. Here, we report the generation of an artificial enzyme by genetic encoding of a non-canonical amino acid that contains a secondary amine side chain. The non-canonical amino acid and the binding pocket function synergistically to catalyze the asymmetric nitrocyclopropanation of α,ß-unsaturated aldehydes by the iminium activation mechanism. The designer enzyme was evolved to an optimal variant that catalyzes the reaction at high conversions with high diastereo- and enantioselectivity. This work demonstrates the application of genetic code expansion in enzyme design and expands the scope of enzyme-catalyzed abiological reactions.

High-Temperature Ash Melting and Fluidity Behavior upon the Cocombustion of Sewage Sludge and Coal.

Wastewater treatment produces a large amount of sludge, where the minimizing of the disposed sludge is essential for environmental protection. The co-combustion of sludge with coal is a preferable method for sewage sludge disposal from the economic and environmental perspective. The co-combustion of sludge has been widely used in the industry with the advantages of large processing capacity. The melting characteristics of ash are an important criterion for the selection of the co-combustion methods and furnace types. In this study, two types of sludge and four types of coal with different ash melting points were selected, where the ash melting behavior upon co-combustion is investigated by experimental and thermodynamical approaches. Especially, the slag fluidity upon co-combustion is explored via a modified inclined plane method. It has been found that the presence of SiO2 and CaO in sludge substantially enhances its fusion temperature owing to the high content of CaO, while SiO2 acts as a solvent, facilitating the co-melting of other oxides and raising the sludge fusion temperature. Fe2O3 exhibits a specific mass fraction within the range of 10-20%. Furthermore, the presence of CaO and SiO2 prohibits the flow ability of the slag at high temperatures, and Fe2O3 promotes the flow ability for sludge at high temperatures. With increasing base/acid ratio, the sludge flow velocity increases remarkably and peaks at 1.6. The interaction between Fe-Ca and Si-AI significantly affects the fluidity significantly. The findings are expected to optimize the condition of co-combustion and desirable furnace design for the incineration of sludge.

Vector magnetocardiography using compact optically-pumped magnetometers.

Optically pumped magnetometers can provide functionality for bio-magnetic field detection and mapping. This has attracted widespread attention from researchers in the biomedical science field. Magnetocardiography has been proven to be an effective method for examining heart disease. Notably, vector magnetocardiography obtains more spatial information than the conventional method by only taking a component that is perpendicular to the chest surface. In this work, a spin-exchange-relaxation-free (SERF) magnetometer with a compact size of 14 mm × 25 mm × 90 mm was developed. The device has a high sensitivity of 25 fT/ Hz. Meanwhile, in the multichannel working mode, synchronous sensor manipulation and data acquisition can be achieved through our control software without additional data acquisition boards. Since a typical SERF magnetometer only responds to dual-axis magnetic fields, two sensors are orthogonally arranged to form a vector detection channel. Our system consists of seven channels and allows 7 × 9 vector MCG mapping by scanning. High-quality heart vector signals are measured, and P peak, QRS peak, and T peak can be distinguished clearly. To better demonstrate the vectorial information, a vector scatter plot form is also provided. Through a basic bio-electric current model, it demonstrates that triaxial MCG measurements capture a richer spatial current information than traditional uniaxial MCG, offering substantial diagnostic potential for heart diseases and shedding more light on the inversion of cardiac issues.

Potassium affects the association between dietary intake of vitamin C and NAFLD among adults in the United States.

INTRODUCTION: Although the association between nonalcoholic fatty liver disease (NAFLD) and vitamin C has been well studied, the effects of dietary potassium intake on this relationship are still unclear. Thus, this study aimed to determine the effects of dietary potassium intake on the association between vitamin C and NAFLD. METHODS: We performed a cross-sectional learn about with 9443 contributors the usage of 2007-2018 NHANES data. Multiple logistic regression evaluation has been utilized to check out the affiliation of dietary vitamin C intake with NAFLD and advanced hepatic fibrosis (AHF). Subsequently, we plotted a smoothed match curve to visualize the association. Especially, the analysis of AHF was conducted among the NAFLD population. In addition, stratified evaluation used to be developed primarily based on demographic variables to verify the steadiness of the results. Effect amendment by way of dietary potassium intake used to be assessed via interplay checks between vitamin C and NAFLD in the multivariable linear regression. RESULTS: In this cross-sectional study, we found that vitamin C was negatively related to NAFLD and AHF. The relationship between vitamin C and NAFLD was different in the low, middle and high potassium intake groups. Furthermore, potassium intake significantly modified the negative relationship between vitamin C and NAFLD in most of the models. CONCLUSION: Our research showed that potassium and vitamin C have an interactive effect in reducing NAFLD, which may have great importance for clinical medication.

Secure ECDSA SRAM-PUF Based on Universal Single/Double Scalar Multiplication Architecture.

Physically unclonable functions (PUFs) are crucial for enhancing cybersecurity by providing unique, intrinsic identifiers for electronic devices, thus ensuring their authenticity and preventing unauthorized cloning. The SRAM-PUF, characterized by its simple structure and ease of implementation in various scenarios, has gained widespread usage. The soft-decision Reed-Muller (RM) code, an error correction code, is commonly employed in these designs. This paper introduces the design of an RM code soft-decision attack algorithm to reveal its potential security risks. To address this problem, we propose a soft-decision SRAM-PUF structure based on the elliptic curve digital signature algorithm (ECDSA). To improve the processing speed of the proposed secure SRAM-PUF, we propose a custom ECDSA scheme. Further, we also propose a universal architecture for the critical operations in ECDSA, elliptic curve scalar multiplication (ECSM), and elliptic curve double scalar multiplication (ECDSM) based on the differential addition chain (DAC). For ECSMs, iterations can be performed directly; for ECDSMs, a two-dimensional DAC is constructed through precomputation, followed by iterations. Moreover, due to the high similarity of ECSM and ECDSM data paths, this universal architecture saves hardware resources. Our design is implemented on a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC) using a Xilinx Virtex-7 and an TSMC 40 nm process. Compared to existing research, our design exhibits a lower bit error rate (2.7×10-10) and better area-time performance (3902 slices, 6.615 µs ECDSM latency).

Resistance and durability of fly ash based geopolymer for heavy metal immobilization: properties and mechanism.

Geopolymer technology is an effective method of fly ash (FA) disposal developed in recent decades. This study provided a novel technology based on geopolymerization for FA resource, which could solve the problem of long-term heavy metal leakage trends. Firstly, Unconfine compressive strength (UCS) of geopolymer and the heavy metals leaching test was taken to discuss the effects of oxidize species. The results indicated that the UCS of geopolymer samples was increased with the increase of CaO, and the largest 28 d UCS was 24.8 MPa when CaO content was 31.5%. When the CaO content was 32%, the leaching concentration of heavy metals was the lowest (Pb2+ was 0.02 mg L-1, Cd2+ was 0.01 mg L-1), and the solidification rate of heavy metal ions were more than 93.6%. Secondly, two methods were used to evaluate the corrosion resistance of FA based geopolymer. The observations suggested that the FA based geopolymer exhibits a high level of resistance to erosion caused by sulfate ions and chloride ions. Thirdly, carbonation tests were taken to discuss the durability of FA based geopolymer. The results shown that UCS exhibited a modest rise following the process of carbonation, and then demonstrated a stable trend after a period of 28 days, and the heavy metal leaching test results that comply with the limitations specified in the national standard at 7, 14, 28, and 56 days. The findings from accelerated carbonization tests at 56 days, determined by empirical equations, suggest that the carbonization age of geopolymers is projected to be 102 years. Finally, XRD, FTIR and SEM were taken to discuss the microstructure characterization of FA based geopolymer, and solidification mechanisms of heavy metal ions by geopolymer materials could be concluded as gelation, physical encapsulation, and chemical reactions.

Aflatoxin B1 inhibited the development of primary myoblasts of grass carp (Ctenopharyngodon idella) by degrading extracellular matrix.

According to the International Agency for Research on Cancer (IARC), aflatoxin B1 (AFB1) has been recognized as a major contaminant in food and animal feed and which is a common mycotoxin with high toxicity. Previous research has found that AFB1 inhibited zebrafish muscle development. However, the potential mechanism of AFB1 on fish muscle development is unknown, so it is necessary to conduct further investigation. In the present research, the primary myoblast of grass carp was used as a model, we treated myoblasts with AFB1 for 24 h. Our results found that 5 µM AFB1 significantly inhibited cell proliferation and migration (P < 0.05), and 10 µM AFB1 promoted lactate dehydrogenase (LDH) release (P < 0.05). Reactive oxygen species (ROS), protein carbonyl (PC) and malondialdehyde (MDA) levels were increased in 15, 5 and 10 µM AFB1 (P < 0.05), respectively. Catalase (CAT), glutathione peroxidase (GPx) and total superoxide dismutase (T-SOD) activities were decreased in 10, 10 and 15 µM AFB1 (P < 0.05), respectively. Furthermore, 15 µM AFB1 induced oxidative damage by Nrf2 pathway, also induced apoptosis in primary myoblast of grass carp. Meanwhile, 15 µM AFB1 decreased MyoD gene and protein expression (P < 0.05). Importantly, 15 µM AFB1 decreased the protein expression of collagen Ⅰ and fibronectin (P < 0.05), and increased the protein levels of urokinase plasminogen activator (uPA), matrix metalloproteinase 9 (MMP-9), matrix metalloproteinase 2 (MMP-2), and p38 mitogen-activated protein kinase (p38MAPK) (P < 0.05). As a result, our findings suggested that AFB1 damaged the cell morphology, induced oxidative damage and apoptosis, degraded ECM components, in turn inhibiting myoblast development by activating the p38MAPK/urokinase-type plasminogen activator (uPA)/matrix metalloproteinase (MMPs)/extracellular matrix (ECM) signaling pathway.

Precise tooth design using deep learning-based templates.

OBJECTIVES: In prosthodontic procedures, traditional computer-aided design (CAD) is often time-consuming and lacks accuracy in shape restoration. In this study, we combined implicit template and deep learning (DL) to construct a precise neural network for personalized tooth defect restoration. METHODS: Ninety models of right maxillary central incisor (80 for training, 10 for validation) were collected. A DL model named ToothDIT was trained to establish an implicit template and a neural network capable of predicting unique identifications. In the validation stage, teeth in validation set were processed into corner, incisive, and medium defects. The defective teeth were inputted into ToothDIT to predict the unique identification, which actuated the deformation of the implicit template to generate the highly customized template (DIT) for the target tooth. Morphological restorations were executed with templates from template shape library (TSL), average tooth template (ATT), and DIT in Exocad (GmbH, Germany). RMSestimate, width, length, aspect ratio, incisal edge curvature, incisive end retraction, and guiding inclination were introduced to assess the restorative accuracy. Statistical analysis was conducted using two-way ANOVA and paired t-test for overall and detailed differences. RESULTS: DIT displayed significantly smaller RMSestimate than TSL and ATT. In 2D detailed analysis, DIT exhibited significantly less deviations from the natural teeth compared to TSL and ATT. CONCLUSION: The proposed DL model successfully reconstructed the morphology of anterior teeth with various degrees of defects and achieved satisfactory accuracy. This approach provides a more reliable reference for prostheses design, resulting in enhanced accuracy in morphological restoration. CLINICAL SIGNIFICANCE: This DL model holds promise in assisting dentists and technicians in obtaining morphology templates that closely resemble the original shape of the defective teeth. These customized templates serve as a foundation for enhancing the efficiency and precision of digital restorative design for defective teeth.