Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

OBJECTIVES: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device. METHODS: A small toothbrush-like device consisting of a 400 nm UV light-emitting lamp with a 470 nm filter was manufactured for intraoral imaging. A total of 133 cases with 9,478 QLF images of teeth were included for caries lesion evaluation using a CNN model. The database was divided into development, validation, and testing cohorts at a 7:2:1 ratio. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for model performance. RESULTS: The overall caries prevalence was 19.59%. The CNN model achieved an AUC of 0.88, an accuracy of 0.88, a specificity of 0.94, and a sensitivity of 0.64 in the validation cohort. They achieved an overall accuracy of 0.92, a sensitivity of 0.95 and a specificity of 0.55 in the testing cohort. The model can distinguish different stages of caries well, with the best performance in detecting deep caries followed by intermediate and superficial lesions. CONCLUSIONS: Caries lesions have typical characteristics in QLF images and can be detected by CNNs. A QLF-based device with CNNs can assist in caries screening in the clinic or at home. TRIAL REGISTRATION: The clinical trial was registered in the Chinese Clinical Trial Registry (No. ChiCTR2300073487, Date: 12/07/2023).

Construction of a mitochondria-targeted probe to monitor cysteine levels in cancer cells and zebrafish.

Cysteine (Cys) plays an indispensable role as an antioxidant in the maintenance of bioredox homeostasis. We have constructed an efficient fluorescent probe Mito-Cys based on the binding of indole and naphthol. The acrylic ester group serves as a recognition switch for specific detection of Cys, which undergoes Michael addition and intramolecular cyclization reactions, thereby ensuring the chemical kinetics priority of Cys compared to other biothiols. The probe has good water solubility, large Stokes shift (137 nm), with a detection limit of 21.81 nM. In addition, cell imaging experiments have shown that the probe has excellent mitochondrial targeting ability (R = 0.902). The probe can distinguish between Cys, homocysteine (Hcy) and glutathione (GSH), and can detect Cys specifically and quickly (100 s) to ensure accurate quantitative analysis of Cys changes in cells. More importantly, the probe confirms that ferroptosis inducing factors trigger thiol starvation in mitochondria, which helps to gain a deeper understanding of the physiological and pathological functions related to Cys and ferroptosis.

Structural and biochemical characterization of active sites mutant in human inorganic pyrophosphatase.

Inorganic pyrophosphatases (PPases) are enzymes that catalyze the conversion of inorganic pyrophosphate (PPi) into phosphate (Pi). Human inorganic pyrophosphatase 1 (Hu-PPase) exhibits high expression levels in a variety of tumors and plays roles in cell proliferation, apoptosis, invasion and metastasis, making it a promising prognostic biomarker and a target for cancer therapy. Despite its widespread presence, the catalytic mechanism of Hu-PPase in humans remains inadequately understood. The signature motif amino acid sequence (DXDPXD) within the active sites of PPases is preserved across different species. In this research, an enzymatic activity assay revealed that mutations led to a notable reduction in enzymatic function, although the impact of the four amino acids on the activity of the pocket varied. To investigate the influence of these residues on the substrate binding and enzymatic function of PPase, the crystal structure of the Hu-PPase-ED quadruple mutant (D116A/D118A/P119A/D121A) was determined at 1.69 Å resolution. The resulting structure maintained a barrel-like shape similar to that of the wild-type, albeit lacking Mg2+ ions. Molecular docking analysis demonstrated a decreased ability of Hu-PPase-ED to bind to PPi. Further, molecular dynamics simulation analysis indicated that the mutation rendered the loop of Mg2+ ion-binding residues less stable. Therefore, the effect on enzyme activity did not result from a change in the gross protein structure but rather from a mutation that abolished the Mg2+-coordinating groups, thereby eliminating Mg2+ binding and leading to the loss of enzyme activity.

Predicting rice diseases using advanced technologies at different scales: present status and future perspectives.

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present the state-of-the-art in contemporary optical sensing applications of pathogen-plant interaction phenotypes. This review serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice crops through ML and DL models.

Cognitive reappraisal and empathy chain-mediate the association between relative deprivation and prosocial behavior in adolescents.

Background: Relative deprivation is one of the factors that influences the development of personality and behavior. However, it is still unclear whether and how relative deprivation decreases the prosocial behavior in adolescents. This study aimed to examine the association between relative deprivation and adolescent prosocial behavior and the role of emotion regulation strategies and empathy in modifying this association. Methods: The present study included 609 secondary school students (M = 15.42 years, SD = 0.653) in Fujian Province, China. All participants completed the Relative Deprivation Questionnaire, Emotion Regulation Scale, the Basic Empathy Scale, and Prosocial Behavior Scale. The collected data were analyzed using SPSS 25.0 and Mplus 7.4. Results: Relative deprivation was negatively correlated with cognitive reappraisal, but positively correlated with expressive suppression. Cognitive reappraisal was positively correlated with empathy and prosocial behavior, but expressive suppression was not. Empathy was positively correlated with prosocial behavior. Relative deprivation decreased prosocial behavior through (a) cognitive reappraisal, (b) empathy, and (c) chain mediation of cognitive reappraisal and empathy. No significant mediating effect of expressive suppression was found. Conclusion: The results indicate that relative deprivation decreases adolescent prosocial behavior, and that cognitive reappraisal and empathy are the potential psychological mechanisms that affect the association between relative deprivation and adolescent prosocial behavior.

Machine-learning-facilitated prediction of heavy metal contamination in distiller's dried grains with solubles.

Excessive heavy metal contamination often occurs in feed due to natural or anthropogenic activity, leading to poisoning and other health problems in animals. In this study, a visible/near-infrared hyperspectral imaging system (Vis/NIR HIS) was used to reveal the different characteristics of spectral reflectance of Distillers Dried Grains with Solubles (DDGS) doped with various heavy metals and to effectively predict metal concentrations. Two types of sample treatment were used, namely tablet and bulk. Three quantitative analysis models were constructed based on the full wavelength, and through comparison the support vector regression (SVR) model was found to show the best performance. As typical heavy metal contaminants, copper (Cu) and zinc (Zn) were used for modeling and prediction. The prediction set accuracy of the tablet samples doped with Cu and Zn was 94.9% and 86.2%, respectively. In addition, a novel characteristic wavelength selection model based on SVR (SVR-CWS) was proposed to filter characteristic wavelengths, which improved the detection performance. The regression accuracy of the SVR model on the prediction set of tableted samples with different Cu and Zn concentrations was 94.7% and 85.9%, respectively. The accuracy of bulk samples with different Cu and Zn concentrations was 81.3% and 80.3%, respectively, which indicated that the detection method can reduce the pretreatment steps and verify its practicability. The overall results suggested the potential of Vis/NIR-HIS in the detection of feed safety and quality.

Early detection of cotton verticillium wilt based on root magnetic resonance images.

Verticillium wilt (VW) is often referred to as the cancer of cotton and it has a detrimental effect on cotton yield and quality. Since the root system is the first to be infested, it is feasible to detect VW by root analysis in the early stages of the disease. In recent years, with the update of computing equipment and the emergence of large-scale high-quality data sets, deep learning has achieved remarkable results in computer vision tasks. However, in some specific areas, such as cotton root MRI image task processing, it will bring some challenges. For example, the data imbalance problem (there is a serious imbalance between the cotton root and the background in the segmentation task) makes it difficult for existing algorithms to segment the target. In this paper, we proposed two new methods to solve these problems. The effectiveness of the algorithms was verified by experimental results. The results showed that the new segmentation model improved the Dice and mIoU by 46% and 44% compared with the original model. And this model could segment MRI images of rapeseed root cross-sections well with good robustness and scalability. The new classification model improved the accuracy by 34.9% over the original model. The recall score and F1 score increased by 59% and 42%, respectively. The results of this paper indicate that MRI and deep learning have the potential for non-destructive early detection of VW diseases in cotton.

Biomechanical perspectives on dentine cracks and fractures: Implications in their clinical management.

OBJECTIVES: The present review discussed the biomechanical properties of cracks and fractures in crown and root dentine and attempted to explain why cracked teeth and vertical root fractures are so frequent despite the existence of multiple crack toughening mechanisms in dentine. The implications of this knowledge were used to justify how these defects are managed clinically. DATA, SOURCES AND STUDY SELECTION: Literature search was conducted on PubMed, Web of Science, and Scopus for a narrative review on fracture mechanics of crown and root dentine as well as the clinical management of cracked teeth and teeth with vertical root fracture. CONCLUSIONS: Although dentine is tougher and less brittle than enamel, it's facture toughness is considerably lower than most ductile metals. Because the initiation toughness of dentine is very low, cracks initiate from incipient damage under low stress While crack toughening mechanisms exist that enable dentine to resist crack extension, these mechanisms are often inadequate for protecting dentine from crack propagation that ultimately leads to catastrophic failure. Additional factors such as ageing also reduces the resistance of dentine to crack growth. Because dentine cracks are eventually filled with bacteria biofilms upon exposure to oral fluids, they enable rapid bacteria ingress into the dental pulp via open dentinal tubules. To date, treatment options for cracked teeth are limited. While most teeth with vertical root fracture are recommended for extraction, new strategies have been reported that appeared to achieve short-term success in preserving these teeth. CLINICAL SIGNIFICANCE: Current strategies for the management for dentine cracks and fractures are limited and their long-term effectiveness remain uncertain. Understanding the characteristics, toughening mechanism and weakening factors of tooth cracks is helpful in designing better treatment.

Single-port laparoscopy versus conventional laparoscopy of benign adnexal masses during pregnancy: a retrospective case-control study.

OBJECTIVE: To compare operative outcomes between single-port laparoscopy (SPL) and conventional laparoscopy (CL) to remove adnexal masses during pregnancy. METHODS: This retrospective case-control study included all patients who had undergone laparoscopic removal of benign adnexal masses during pregnancy between October 2010 and January 2020. Multiple clinical characteristics and operative outcomes were retrospectively analysed and compared between patients who had undergone SPL versus CL, including cosmetic satisfaction with the scar, measured on a 10-point scale (10 indicating very satisfied). RESULTS: A total of 64 patients were included (SPL, n = 22; and CL, n = 42). Overall scar satisfaction scores significantly favoured SPL versus CL (9.1 ± 1.7 versus 8.1 ± 1.3, respectively), however, surgery duration was significantly longer for SPL than CL (69.2 ± 21.0 min versus 54.7 ± 20.7 min). No incisional hernia was detected in the study. Operative blood loss, decrease in estimated haemoglobin level, length of hospital stay, and hospitalization expenses were comparable between the two groups. Pregnancy and fetal outcomes were not remarkably different. CONCLUSION: For removal of benign adnexal masses during pregnancy, SPL may offer superior cosmetic satisfaction versus CL, and was not associated with additional perioperative danger, economic burden, or adverse pregnancy and neonatal outcomes.

Changes of Endothelin-1 and Calcitonin Gene-Related Peptide Concentrations in Patients with Cervical Radiculopathy after Wrist-Ankle Acupuncture-Moxibustion and Hot Compression with Chinese Herbal Medicine.

Objective: This study aimed at investigating the effects of wrist-ankle acupuncture-moxibustion and hot compression with Chinese herbal medicine on pain symptoms, endothelin-1 (ET-1), and calcitonin gene-related peptide (CGRP) concentrations of patients with cervical radiculopathy (CR). Methods: A total of 82 patients with CR were randomly divided into the study group and control group, with 41 cases in each group. The control group was treated with standard treatment. In addition to standard treatment, the study group was additionally treated with wrist-ankle acupuncture-moxibustion and hot compression with Chinese herbal medicine. The ET-1 and CGRP concentrations in the plasma were measured by the radioimmunoassay method. Results: The total response rate in the study group and the control group was 97.55% and 82.93%, respectively. The study group showed lower scores of the visual analogue scale (VAS), Northwick Park Neck Pain Questionnaire (NPQ), McGill Pain Questionnaire (MPQ), numbness intensity assessment, and neck disability index (NDI) but higher scores of the Short Form-36 (SF-36) health survey questionnaire than the control group after treatment. Besides, the study group exhibited reduced ET-1 and substance P (SP) concentrations concomitant with increased CGRP and ß-endorphin (ß-EP) concentrations compared with the control group. Conclusion: Wrist-ankle acupuncture-moxibustion and hot compression with Chinese herbal medicine could effectively alleviate the pain of CR patients, affect ET-1 and CGRP concentrations, promote the recovery of cervical function, and improve the quality of life.