Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To investigate the role of CISD1 in gefitinib-resistant non-small cell lung cancer(NSCLC),so as to provide a potential therapeutic target for the treatment of gefitinib-resistant NSCLC.Methods Bioinformatics online platforms TIMER2.0 and HPA were used to analyze the expression level of CISD1 in lung cancer.TIMER2.0 and GEPIA2.0 were used to analyze the correlation between the expression levels of CISD1 and SLC7A11 in lung cancer.The correlation between CISD1 and overall survival rate of lung cancer patients was analyzed using KMPLOT.Human lung carcinoma cell line PC9 and gefitinib-resistant cell line PC9/GR were treated with gefitinib,and cell viability was detected using the CCK8 method.shCISD1 lentivirus infection was used to knockdown CISD1 in PC9/GR cells.Western blotting was employed to detect the protein expression levels of CISD1 and SLC7A11.PC9/GR cells were divided into shNC+DMSO group,shNC+gefitinib group,shCISD1 group,shCISD1+ferrostatin-1 group,and shCISD1+gefitinib group.Plate clone formation assay was used to detect cell proliferation capacity.FerroOrange fluorescent probe and C11-BODIPY fluorescent probe were used to detect intracellular free Fe2+content and intracellular lipid peroxide level,respectively.Results CISD1 was significantly overexpressed in lung carcinoma(P＜0.001).The expression level of CISD1 was negatively correlated with the overall survival rate of lung cancer patients and negatively correlated with the expression level of SLC7A11.Compared with the DMSO control group,gefitinib treatment significantly reduced clone formation and CISD1 protein expression levels in both PC9 and PC9/GR cells(P＜0.05),but the reduction was less pronounced in PC9/GR cells.shCISD1 infection significantly inhibited the protein expression levels of CISD1 and SLC7A11 in PC9/GR cells(P＜0.05)and enhanced the sensitivity of PC9/GR cells to gefitinib.Compared with the shNC+DMSO group,both the shNC+gefitinib group and the shCISD1 group showed significantly reduced clone formation ability(P＜0.05),but increased Fe2+and lipid peroxidation levels(P＜0.05).Compared with the shCISD1 group,the shCISD1+ferrostatin-1 group showed significantly increased clone formation ability(P＜0.05),but decreased Fe2+and lipid peroxidation levels(P＜0.05).Compared with the shNC+gefitinib group,the shCISD1+gefitinib group showed significantly reduced clone formation ability(P＜0.05),but increased Fe2+and lipid peroxidation levels(P＜0.05).Conclusion Knockdown of CISD1 promotes the sensitivity of NSCLC to gefitinib by inducing ferroptosis,which provides a new potential therapeutic target for the treatment of gefitinib-resistant NSCLC.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

Objective To retrospectively analyze the clinical efficacy of the Chaixia Sanjie formula in treating pulmonary nodules.Methods Retrospective collection of 107 patients with pulmonary nodules and liver-qi stagnation syndrome who received the Chaixia Sanjie formula for 3months or more at Dongzhimen Hospital,Beijing University of Chinese Medicine,from January 2021 to June 2024 as the observation group.Another 107 patients with pulmonary nodules and liver-qi stagnation syndrome who did not receive traditional Chi-nese medicine(TCM)intervention during the same period were selected as the control group.Basic information,TCM syndromes,and the diameters of pulmonary nodules on chest HRCT at the first and last visit were collected.Changes in nodule diameter,TCM syndrome scores,and TCM therapeutic efficacy were compared between the two groups.Results Compared with the control group,the nodule di-ameter in the observation group was smaller and the difference was statistically significant(P＜0.05),and the proportion of nodule disap-pearance or reduction was higher in the observation group than in the control group,and the difference was statistically significant(P＜0.05).At the final diagnosis,the observation group showed a decrease in traditional Chinese medicine syndrome scores,including chest fullness,emotional instability,belching and bloating,rib pain,foreign body sensation in the throat,bitter mouth,lack of appetite,irreg-ular bowel movements,and sleep disorders,compared to the initial diagnosis and the control group,with statistical significance(P＜0.05).The effective rate of TCM syndrome improvement in the observation group was 88.8％.Conclusion The Chaixia Sanjie formula can reduce the diameter of pulmonary nodules to some extent and improve TCM syndromes in patients with pulmonary nodules.

Objective To investigate the role of CISD1 in gefitinib-resistant non-small cell lung cancer(NSCLC),so as to provide a potential therapeutic target for the treatment of gefitinib-resistant NSCLC.Methods Bioinformatics online platforms TIMER2.0 and HPA were used to analyze the expression level of CISD1 in lung cancer.TIMER2.0 and GEPIA2.0 were used to analyze the correlation between the expression levels of CISD1 and SLC7A11 in lung cancer.The correlation between CISD1 and overall survival rate of lung cancer patients was analyzed using KMPLOT.Human lung carcinoma cell line PC9 and gefitinib-resistant cell line PC9/GR were treated with gefitinib,and cell viability was detected using the CCK8 method.shCISD1 lentivirus infection was used to knockdown CISD1 in PC9/GR cells.Western blotting was employed to detect the protein expression levels of CISD1 and SLC7A11.PC9/GR cells were divided into shNC+DMSO group,shNC+gefitinib group,shCISD1 group,shCISD1+ferrostatin-1 group,and shCISD1+gefitinib group.Plate clone formation assay was used to detect cell proliferation capacity.FerroOrange fluorescent probe and C11-BODIPY fluorescent probe were used to detect intracellular free Fe2+content and intracellular lipid peroxide level,respectively.Results CISD1 was significantly overexpressed in lung carcinoma(P＜0.001).The expression level of CISD1 was negatively correlated with the overall survival rate of lung cancer patients and negatively correlated with the expression level of SLC7A11.Compared with the DMSO control group,gefitinib treatment significantly reduced clone formation and CISD1 protein expression levels in both PC9 and PC9/GR cells(P＜0.05),but the reduction was less pronounced in PC9/GR cells.shCISD1 infection significantly inhibited the protein expression levels of CISD1 and SLC7A11 in PC9/GR cells(P＜0.05)and enhanced the sensitivity of PC9/GR cells to gefitinib.Compared with the shNC+DMSO group,both the shNC+gefitinib group and the shCISD1 group showed significantly reduced clone formation ability(P＜0.05),but increased Fe2+and lipid peroxidation levels(P＜0.05).Compared with the shCISD1 group,the shCISD1+ferrostatin-1 group showed significantly increased clone formation ability(P＜0.05),but decreased Fe2+and lipid peroxidation levels(P＜0.05).Compared with the shNC+gefitinib group,the shCISD1+gefitinib group showed significantly reduced clone formation ability(P＜0.05),but increased Fe2+and lipid peroxidation levels(P＜0.05).Conclusion Knockdown of CISD1 promotes the sensitivity of NSCLC to gefitinib by inducing ferroptosis,which provides a new potential therapeutic target for the treatment of gefitinib-resistant NSCLC.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.