ObjectiveBased on the conjoint analysis of transcriptome and metabolome， the key genes in the phenylpropanoid biosynthesis pathway of Lonicera macranthoides were explored， which provided a basis for further exploring the synthesis and regulation mechanism of phenylpropanoid compounds in "Xianglei" L. macranthoides. MethodsThe stem， leaves， and three flowering flowers of "Xianglei" L. macranthoides were selected as experimental materials to construct transcriptome and metabolome. The transcriptome and metabolomics were conjointly analyzed by the Kyoto Encyclopedia of Genes and Genomes （KEGG） database and weighted correlation network analysis （WGCNA）， and the key genes in the phenylpropanoid biosynthesis pathway of L. macranthoides were explored. ResultsIn this study， 77 differential phenylpropanoids and 315 differential genes were found. Through the joint analysis of transcription and metabolism， nine key differential metabolites and four key genes related to them were finally discovered. Among them， cinnamic acid， 5-O-caffeoylshikimic acid，sinapyl alcohol， and chlorogenic acid were higher in flowers， and the content of the iconic effective component， namely chlorogenic acid，decreased sharply during the withering period. Caffeic acid，ferulic acid， 5-hydroxyconiferaldehyde，p-coumaryl alcohol， and syringin were higher in leaves. These four key genes belong to the cinnamic alcohol dehydrogenase （CAD） family， 4-coumaric acid： Coenzyme A （4CL） family， hydroxycinnamyl transferase （HCT） family， and L-phenylalanine ammonlyase （PAL） family genes. ConclusionAmong the four key genes excavated from L. macranthoides， TRINITY_DN42767_c0_g6 is related to the synthesis of p-coumaryl alcohol and sinapyl alcohol. TRINITY_DN43525_c4_g1 uses caffeic acid，ferulic acid，and cinnamic acid as substrates to catalyze the next reaction. TRINITY_DN47958_c3_g4 correlates with the synthesis of 3-p-coumaroyl quinic acid and caffeoyl-CoA， and TRINITY_DN52595_c1_g2 correlates with cinnamic acid synthesis. These findings provide a basis for further exploring the synthesis and regulation mechanism of phenylpropanoids in "Xianglei" L. macranthoides.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome

Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery. However, variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials. This heterogeneity in protocols may cause confusion among dental practitioners; therefore, guidelines and considerations for ITR should be explicated. This expert consensus discusses the biological foundation of ITR, the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration, and the main complications of this treatment, aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies; the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
Humans ; Tooth Replantation/methods* ; Consensus ; Periapical Periodontitis/surgery*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Biosynthesized selenium nanoparticles (SeNPs) have attracted much attention because of their unique physical, chemical, and biological properties. The microbial reduction of selenium salts to SeNPs has great potential, while there is a lack of elite strains. In this study, we explored the reduction of Na₂SeO₃ by Streptomyces avermitilis into SeNPs. The colonies and hyphae of the strain and the synthesized SeNPs were characterized by optical microscopy, scanning electron microscopy (SEM), transmission electron microscope (TEM), energy dispersive spectrometry (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). At the same time, the inhibitory activity of SeNPs on Fusarium oxysporum, the main pathogen causing root rot of Lycium barbarum, was studied. The results showed that S. avermitilis converted Na₂SeO₃ into SeNPs and tolerated 300 mmol/L Na₂SeO₃, demonstrating strong tolerance. S. avermitilis synthesized spherical SeNPs in the cytoplasm, and most of SeNPs had a diameter of about 100 nm and were released by hyphal fracture. The SeNPs synthesized by S. avermitilis were amorphous, and their surfaces were dominated by C and Se, with the existence of O, N and other elements. SeNPs had functional groups such as -OH, C=O, C-N, and C-H, which were closely related to the stability and biological activity of SeNPs. The SeNPs synthesized by S. avermitilis showcased significant inhibitory activity on F. oxysporum, and 25.0 μmol/mL SeNPs showcased the inhibition rate of 77.61% and EC₅₀ of 0.556 μmol/mL. In conclusion, S. avermitilis can tolerate high Na₂SeO₃ stress and mediate the synthesis of SeNPs. The synthesized SeNPs have good stability and strong inhibitory activity, demonstrating the potential application value in the preparation of SeNPs and the control of L. barbarum root rot.
Streptomyces/metabolism* ; Fusarium/drug effects* ; Lycium/microbiology* ; Selenium/metabolism* ; Nanoparticles/chemistry* ; Plant Diseases/microbiology* ; Metal Nanoparticles/chemistry* ; Antifungal Agents/pharmacology*

Brain age prediction is of great significance to the in-depth understanding of individual neurodevelopment,early diagnosis of neuropsychiatric disorders,and formulation of personalized treatment plans. With the continuous advancement of deep learning,more and more researches focus on using such algorithms to predict brain age. Compared with traditional regression algorithms,deep learning which has the advantages of complex pattern learning,end-to-end learning and high adaptability can more accurately reveal the neuropathological mechanisms of neuropsychiatric disorders,and provide more precise tools for clinical assessment,assisted diagnosis and prognosis prediction. Herein the study reviews the recent advances in the application of deep learning algorithms in brain age prediction,introduces the achievements in deep learning model optimization,multimodal data inputs and interpretability studies for brain age prediction,discusses the methods for the establishment of integrated deep learning architectures and the future challenges of developing unified benchmarking,and provides an outlook on the application of deep learning in brain age prediction.

Objective:To investigate expression and clinical significance of T cell activation related membrane molecules in infertility patients with polycystic ovary syndrome(PCOS).Methods:A total of 80 PCOS infertility patients who visited Second Affiliated Hospital of Hainan Medical College from January 2020 to June 2021 were selected as observation group,and 80 cases of women who underwent physical examination at same time were selected as control group.Expressions of membrane molecules related to T cell acti-vation in peripheral blood of patients between two groups were compared.Patients with PCOS infertility were divided into pregnant group[66(82.5％)]and non pregnant group[14(17.5％)]according to different prognosis.General clinical data,peripheral blood inflammatory factors and T cell activation related membrane molecules expressions were compared between two groups,focusing on correlation between T cell activation related membrane molecules expressions and prognosis of PCOS infertility patients,ROC curve and decision-making curve of T cell activation related membrane molecule expressions were drawn to predict prognosis of PCOS infer-tility patients,whose prediction efficiency and net profitability were further analyzed.Pearson correlation analysis was used to explore correlation between T cell activation related membrane molecules expressions and clinical characteristics of PCOS infertility patients.Results:CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients in observation group were significantly higher than control group(P<0.05).Total testosterone(T),TNF-α,IFN-γ,CD4+CD45+T and CD4+CD63+T cells expressions of patients in non pregnancy group were significantly higher than pregnancy group(P<0.05).Multivariate Logistic regression analysis showed that CD4+CD45+T and CD4+CD63+T cells were independent predictors of prognosis of PCOS infertility patients(P<0.05),ROC analysis showed that AUC of CD4+CD45+T cells predicting prognosis of PCOS infertility patients was 0.756(0.721～0.826),and the best diag-nostic cut-off point was 48.1％,AUC of CD4+CD63+T cells was 0.746(0.711～0.834),and the best cut-off point for diagnosis was 31.2％,while AUC of CD4+CD45+T and CD4+CD63+T cells combination was 0.948(0.897～0.986).Decision curve analysis showed that combined prediction of CD4+CD45+T and CD4+CD63+T cells was higher than a single indicator.Correlation analysis showed that CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients with PCOS infertility was related to T,TNF-α,insulin resistance index(HOMA-IR),IFN-γ,IL-2 and IL-10(P<0.05).Conclusion:The higher the CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood,the worse the prognosis of patients with PCOS infertility.

Objective:To investigate expression and clinical significance of T cell activation related membrane molecules in infertility patients with polycystic ovary syndrome(PCOS).Methods:A total of 80 PCOS infertility patients who visited Second Affiliated Hospital of Hainan Medical College from January 2020 to June 2021 were selected as observation group,and 80 cases of women who underwent physical examination at same time were selected as control group.Expressions of membrane molecules related to T cell acti-vation in peripheral blood of patients between two groups were compared.Patients with PCOS infertility were divided into pregnant group[66(82.5％)]and non pregnant group[14(17.5％)]according to different prognosis.General clinical data,peripheral blood inflammatory factors and T cell activation related membrane molecules expressions were compared between two groups,focusing on correlation between T cell activation related membrane molecules expressions and prognosis of PCOS infertility patients,ROC curve and decision-making curve of T cell activation related membrane molecule expressions were drawn to predict prognosis of PCOS infer-tility patients,whose prediction efficiency and net profitability were further analyzed.Pearson correlation analysis was used to explore correlation between T cell activation related membrane molecules expressions and clinical characteristics of PCOS infertility patients.Results:CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients in observation group were significantly higher than control group(P<0.05).Total testosterone(T),TNF-α,IFN-γ,CD4+CD45+T and CD4+CD63+T cells expressions of patients in non pregnancy group were significantly higher than pregnancy group(P<0.05).Multivariate Logistic regression analysis showed that CD4+CD45+T and CD4+CD63+T cells were independent predictors of prognosis of PCOS infertility patients(P<0.05),ROC analysis showed that AUC of CD4+CD45+T cells predicting prognosis of PCOS infertility patients was 0.756(0.721～0.826),and the best diag-nostic cut-off point was 48.1％,AUC of CD4+CD63+T cells was 0.746(0.711～0.834),and the best cut-off point for diagnosis was 31.2％,while AUC of CD4+CD45+T and CD4+CD63+T cells combination was 0.948(0.897～0.986).Decision curve analysis showed that combined prediction of CD4+CD45+T and CD4+CD63+T cells was higher than a single indicator.Correlation analysis showed that CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood of patients with PCOS infertility was related to T,TNF-α,insulin resistance index(HOMA-IR),IFN-γ,IL-2 and IL-10(P<0.05).Conclusion:The higher the CD4+CD45+T and CD4+CD63+T cells expressions in peripheral blood,the worse the prognosis of patients with PCOS infertility.

Brain age prediction is of great significance to the in-depth understanding of individual neurodevelopment,early diagnosis of neuropsychiatric disorders,and formulation of personalized treatment plans. With the continuous advancement of deep learning,more and more researches focus on using such algorithms to predict brain age. Compared with traditional regression algorithms,deep learning which has the advantages of complex pattern learning,end-to-end learning and high adaptability can more accurately reveal the neuropathological mechanisms of neuropsychiatric disorders,and provide more precise tools for clinical assessment,assisted diagnosis and prognosis prediction. Herein the study reviews the recent advances in the application of deep learning algorithms in brain age prediction,introduces the achievements in deep learning model optimization,multimodal data inputs and interpretability studies for brain age prediction,discusses the methods for the establishment of integrated deep learning architectures and the future challenges of developing unified benchmarking,and provides an outlook on the application of deep learning in brain age prediction.