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*

OBJECTIVE: To investigate the relationship between peripheral blood T-cell immunoglobulin mucin-3 (TIM-3) and iron overload in patients with myelodysplastic syndrome (MDS) undergoing red blood cell transfusion. METHODS: 120 MDS patients who received treatment at Wuhan Third Hospital from June 2020 to May 2022 were included and analyzed as research subjects, all of whom met the indications for red blood cell transfusion. Blood routine and biochemical indicators were tested before transfusion, and general clinical data of the patients were statistically analyzed. The iron metabolism status of the patients were evaluated. The clinical characteristics of patients with iron overload and the factors affecting iron overload were analyzed. And a correlation analysis was conducted between TIM-3 and other factors affecting iron overload. RESULTS: Among the 120 MDS patients included in this study, 82 cases (68.33%) were detected to have iron overload after red blood cell transfusion. The occurrence time of iron overload was 20-42 weeks, with an average time of 32.35±5.26 weeks, calculated from the first transfusion of red blood cells. The proportion of patients with high-risk and extremely high-risk according to the revised International Prognostic Scoring System (IPSS-R) and WHO classification-based Prognostic Scoring System (WPSS), the volume of blood transfusions, the proportion of transfusion-dependent patients, and the levels of serum hepcidin (Hepc), erythropoietin (EPO), and TIM-3 in patients with iron overload were higher than those in patients with normal iron metabolism, and the differences were statistically significant (P < 0.05). Logistic regression analysis showed that high-risk and extremely high-risk according to WPSS, blood transfusion volume, transfusion dependence, and upregulation of serum Hepc, EPO, and TIM-3 expression were factors affecting iron overload in MDS patients undergoing red blood cell transfusion (P < 0.05). Pearson correlation analysis showed that serum TIM-3 level in MDS patients were positively correlated with the other factors affecting iron overload (P < 0.05). CONCLUSION Serum TIM-3 is associated with iron overload in MDS patients undergoing red blood cell transfusion, and upregulation of serum TIM-3 expression increases the risk of iron overload after red blood cell transfusion.
Humans ; Myelodysplastic Syndromes/blood* ; Iron Overload/blood* ; Hepatitis A Virus Cellular Receptor 2/blood* ; Erythrocyte Transfusion ; Male ; Female ; Middle Aged ; Aged ; Iron

OBJECTIVE: To evaluate the effect and safety of Chinese medicine (CM) Fuzheng Huazhuo Decoction (FHD) in treating patients with coronavirus disease 2019 (COVID-19) who persistently tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This retrospective cohort study was conducted at Shanghai New International Expo Center shelter hospital in China between April 1 and May 30, 2022. Patients diagnosed as COVID-19 with persistently positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results for ⩾8 days after diagnosis were enrolled. Patients in the control group received conventional Western medicine (WM) treatment, while those in the FHD group received conventional WM plus FHD for at least 3 days. The primary outcome was viral clearance time. Secondary outcomes included negative conversion rate within 14 days, length of hospital stay, cycle threshold (Ct) values of the open reading frame 1ab (ORF1ab) and nucleocapsid protein (N) genes, and incidence of new-onset symptoms during hospitalization. Adverse events (AEs) that occurred during the study period were recorded. RESULTS: A total of 1,765 eligible patients were enrolled in this study (546 in the FHD group and 1,219 in the control group). Compared with the control group, patients receiving FHD treatment showed shorter viral clearance time for nucleic acids [hazard ratio (HR): 1.500, 95% confidence interval (CI): 1.353-1.664, P<0.001] and hospital stays (HR: 1.371, 95% CI: 1.238-1.519, P<0.001), and a higher negative conversion rate within 14 days (96.2% vs. 82.6%, P<0.001). The incidence of new-onset symptoms was 59.5% in the FHD group, similar to 57.8% in the control group (P>0.05). The Ct values of ORF1ab and N genes increased more rapidly over time in the FHD group than those in the control group post-randomization (ORF1ab gene: β =0.436±0.053, P<0.001; N gene: β =0.415 ±0.053, P<0.001). The incidence of AEs in the FHD group was lower than that in the control group (24.2% vs. 35.4%, P<0.001). No serious AEs were observed. CONCLUSION FHD was effective and safe for patients with persistently positive SARS-CoV-2 PCR tests. (Registration No. ChiCTR2200063956).
Humans ; Drugs, Chinese Herbal/adverse effects* ; Retrospective Studies ; Male ; Female ; Middle Aged ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/virology* ; Adult ; Aged ; Treatment Outcome

Obesity, as a chronic recurrent disease, has become a major public health challenge in China. To implement the requirements of the Healthy China Initiative (2019—2030), under domestic guidelines or consensus statements on overweight and obesity, and in alignment with the latest scientific advances globally, the Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition) was developed. This protocol was drafted by the Health Management Center of Shanghai Changzheng Hospital and formulated through multiple rounds of deliberation by experts in China’s health examination quality control field. The protocol establishes unified standards for screening facilities, personnel qualifications, and measurement or testing procedures. It defines specific screening items, outlines a standardized screening pathway, and sets requirements for the final medical review, ensuring the scientific validity, effectiveness, and safety of the screening process. The implementation of this protocol will enhance the consistency of weight management practices for adults across health examination institutions and strengthen the quality control of overweight and obesity screening programs.

Objective To evaluate cognitive function and its influencing factors in psoriasis patients.Methods A total of 129 patients with psoriasis who were admitted to the Psoriasis Diagnosis and Treatment Center of the Dermatology Department of the hospital from August 2022 to August 2023 were selected as the study objects.General data questionnaire and the Montreal Cognitive Assessment-Basic Scale(MoCA-B)were used to investigate cognitive function,and the status quo of cognitive function and influencing factors of psori-asis patients were analyzed.Results The subjects had a total cognitive function score of 12 to 30.There were 90 cases(69.77%)with normal cognitive function and 39 cases(30.23%)with cognitive impairment.Execu-tive function,verbal fluency,computation,abstract thinking,memory,visual perception,naming,attention and MoCA-B scores in patients with cognitive impairment were lower than in patients with normal cognitive func-tion(P＜0.05).Logistic regression analysis showed that age(OR=1.059),years of education(OR=0.855)and pathogenesis(OR=0.185)were the factors affecting the cognitive function of psoriasis patients(P＜0.05).Conclusion Pay attention to the cognitive screening of patients with psoriasis and provide cognitive in-tervention early.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective: To examine the mediating effects of mindfulness level on resilience and symptoms of anxiety and depression among healthcare workers, so as to provide the reference for developing effective psychological intervention. Methods: The clinical doctors, nurses and public health professionals were selected using the stratified random cluster sampling method from hospitals, disease prevention and control centers, and health departments in five cities in Shandong Province, including Qingdao, Jinan, Rizhao, Jining and Liaocheng in January 2023. Basic information, mindfulness level, resilience and symptoms of anxiety and depression among healthcare workers were collected using general demographic questionnaires, the 5-item Mindful Attention Awareness Scale, 10-item Connor-Davidson Resilience Scale, Generalized Anxiety Disorder Scale and Patient Health Questionnaire, respectively. The Process program was used to analyze the mediating effects of mindfulness level on resilience and symptoms of anxiety and depression. Results: A total of 1 836 healthcare workers were investigated, including 472 males (25.71%) and 1 364 females (74.29%), and the median age was 39 (interquartile range, 12) years. There were 629 clinical doctors (34.26%), 963 nurses (52.45%) and 244 public health professionals (13.29%). The median scores of mindfulness level and resilience were 22 (interquartile range, 7) and 20 (interquartile range, 4) points, respectively. The detection rates of anxiety and depression symptoms were 49.78% and 72.28%, respectively. The mediation analysis showed that mindfulness level exerted a partial mediating effect between resilience and anxiety symptoms (β=-0.510, P<0.001), with a direct effect value of -0.130 and a mediating effect value of -0.046, and the mediating effect accounted for 26.14% of the total effect; mindfulness level also exerted a partial mediating effect between resilience and depression symptoms (β=-0.575, P<0.001), with a direct effect value of -0.120 and a mediating effect value of -0.052, and the mediating effect accounted for 30.23% of the total effect. Conclusion Mindfulness level plays a mediating effect between resilience and symptoms of anxiety and depression among healthcare workers.

Objective:To identify the development trajectories of self-neglect behavior in older adults and explore the associated influencing factors.Methods:A fixed cohort was constructed based on the data from three surveys of Chinese longitudinal healthy longevity survey (CLHLS) from 2011 to 2018. A total of eight variables from 4 dimensions including living environment, lifestyle, social interaction, and health care were selected to evaluate self-neglect. Group-based trajectory model was used to identify the development trajectory of self-neglect behavior in the older adults, and polynomial Logistic regression model was used to explore its influencing factors by Stata 16.1.Results:Finally, 2 754 older adults aged 60 and above were included.The development trajectory of self-neglect behavior in older adults, based on the group-based trajectory model, can be classified into stable-low group ( n=268, 9.7%), descending-moderate group ( n=2 224, 80.8%), and decreasing-high group ( n=262, 9.5%). Polynomial Logistic regression showed that, compared with stable-low group, living in rural areas ( B=1.116, OR=3.053, 95% CI= 2.278-4.091) and higher activities of daily living scores( B=0.137, OR=1.147, 95% CI=1.046-1.258) were the risk factors of descending-moderate group. Education levels with 1-6 years( B=-0.398, OR=0.672, 95% CI=0.469-0.963), >6 years( B=-1.072, OR=0.342, 95% CI=0.229-0.513), being married( B=-0.476, OR=0.621, 95% CI=0.444-0.870), self-reported good health( B=-0.808, OR=0.446, 95% CI= 0.213-0.932), improved health status( B=-0.704, OR=0.495, 95% CI=0.320-0.766), self-reported average economic status( B=-1.065, OR=0.345, 95% CI=0.148-0.802), self-reported good economic status( B=-1.634, OR=0.195, 95% CI=0.082-0.467), and a higher cognition score( B=-0.142, OR=0.867, 95% CI=0.798-0.942) served as protective factors of descending-moderate group. In addition to the above factors, being in the age group of 75-89 years( B=0.481, OR=1.617, 95% CI=1.057-2.473) was a risk factor for decreasing-high group compared to stable-low group. Conclusions:Three types of self-neglect behavior trajectories among older adults were identified in this study, suggesting that physical health and economy are the influencing factors of the development trajectory of self-neglect of the elderly.

Objective:To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods:This study was a case-control study. Totally 465 patients with gastric cancer treated in Affiliated People′s Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected. According to postoperative pathology, they were divided into 2 groups, one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors. The cases were divided into a training set (326 cases) and a test set (139 cases) by stratified sampling method at 7∶3. There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set, 46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set. The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest (ROI) at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas. The radiomic features of the ROIs were extracted by Pyradiomics software. The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer. Independent sample t test or χ2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set, and the features with statistical significance were combined to establish a clinical model. Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer. The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer. And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model. Results:There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set ( χ2=10.59, 15.92, P=0.014, 0.001) and the clinical model was established. After screening and dimensionality reduction, the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively. In the training set and the test set, the AUC values of the primary gastric cancer radiomic model were 0.864 (95% CI 0.820-0.908) and 0.836 (95% CI 0.762-0.910), and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782 (95% CI 0.731-0.833) and 0.784 (95% CI 0.702-0.866). The AUC values of the clinical model were 0.761 (95% CI 0.705-0.817) and 0.758 (95% CI 0.671-0.845), and the nomogram were 0.876 (95% CI 0.835-0.917) and 0.851 (95% CI 0.781-0.921). The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set ( χ2=1.70, P=0.989). And the decision curve showed that at the risk threshold 0.01-0.74, a higher clinical net benefit could be obtained by using a nomogram to guide treatment. Conclusions:The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer, and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.