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 evaluate the diagnostic value of hematological parameters for PCa with prostate-specific antigen(PSA)of 4-10 μg/L and construct a risk-stratification model with these parameters.Methods:We retrospectively analyzed the da-ta on the males undergoing the initial prostatic biopsy in the Affiliated Hospital of Xuzhou Medical University with PSA of 4-10 μg/L from March 2010 to April 2021.According to the results of biopsy,we classified the patients into a PCa and a non-PCa group,and compared the hematological parameters between the two groups.We performed univariate and multivariate logistic regression analyses,identified the independent risk factors for PCa,constructed a risk-stratification model for the prediction of PCa and evaluated its effi-ciency.Results:A total of 415 cases were included in this study,107(25.8％)in the PCa and 308(74.2％)in the non-PCa group.Compared with the non-PCa males,the PCa patients showed a significantly older age,higher ratios of neutrophil to lymphocyte and platelet to lymphocyte,systemic immune-inflammation index(SII),red blood cell distribution width and cystatin C(CysC)level(all P＜0.05),but lower red blood cell count and hemoglobin and free/total PSA(f/tPSA)levels(all P＜0.05).Multivariate logis-tic regression analysis indicated that age,f/tPSA,SII and CysC were independent risk factors for the prediction of PCa(all P＜0.05).Five prediction models were constructed based on the above risk factors,and the area under the ROC curve(AUC)of the four-parameter(age+f/tPSA+SII+CysC)model was 0.745(95％CI:0.694-0.796),significantly higher than those of the other mod-els(P＜0.05).A risk-stratification model(low-,intermediate-,and high-risk)was also constructed based on the total nomogram scores,which showed a comparable performance to that of the Prostate Imaging Reporting and Data System(PI-RADS)for the predic-tion of PCa(AUC:0.727[95％CI:0.650-0.804]vs 0.734[95％CI:0.658-0.811]).However,the prediction rate by the risk-stratification model was evidently higher in the low-risk males than in those with low PI-RADS scores(1-2)(39.4％vs 22.2％).Conclusion:SII and CysC are independent risk factors for the prediction of PCa in patients with gray-zone PSA levels.The risk-stratification model based on age,SII,CysC and f/tPSA is comparable to PI-RADS in the diagnostic efficiency of PCa,with an even higher prediction rate in low-risk patients than in those with low PI-RADS scores,and contributive to precision screening and reduction of excessive biopsies in the diagnosis of PCa with gray-zone PSA.

To address the key challenges in multivariate statistical modeling,a higher-order derivative approach combined with vector space angle multiplicative error correction was proposed for establishing an acid value prediction ordinary least squares(OLS)regression model based on attenuated total reflectance-Fourier transform infrared(ATR-FTIR)spectroscopy.By using acid values measured by potentiometric titration as reference,ATR-FTIR spectroscopy was utilized for direct calibration and prediction of acid values on 96 kinds of lubricating oil samples from a wind turbine.Firstly,the simulated hyperbolic(SH)method was employed to obtain accurate fourth derivative spectrum,resolving overlapping bands and enhancing spectral selectivity.Then,from the calibration set(48 samples),informative spectral regions were identified based on correlation coefficients.Next,the sample with the highest acid value was selected as the reference and1/(1+tan(θ/2))was used as the metric relation of the spectrum to suppress the multiplicity error caused by factors such as the change of effective optical path in ATR-FTIR spectroscopy.After pretreatment of the spectrum by the method of fourth-order derivative combined with angular quantity,the number of variables decreased from 1737 to 8,and the matrix condition number decreased from 1.85×1015 to 56.34,which effectively eliminated the collinearity issue for OLS regression.Direct OLS modeling on spectral preprocessed data achieved a determination coefficient of 0.981 for 47 validation samples,with a relative error range of-8.38%-8.22%,outperforming the commonly used partial least squares(PLS)method(Determination coefficient of 0.865,relative error of-27.82%-22.38%).It was proved that effective data preprocessing significantly improved the prediction accuracy of the model.Furthermore,when the number of calibration set was compressed to 25 and the number of validation set was expanded to 70,the model retained 8 variables with a condition number of 42.60,the determination coefficient of validation set was 0.972,and the relative error ranged from-10.80%to 12.31%.Comparing with the PLS method(Determination coefficient of 0.724,relative error of-34.26%-53.84%),the improvement was more obvious,which showed that the method could still have high prediction accuracy even with fewer modeling samples as well as robustness against multiplicative error interference.

This study systematically reviewed the randomized controlled trial(RCT) of traditional Chinese medicine(TCM) treatment of coronary heart disease patients with angina pectoris after percutaneous coronary intervention(PCI). The basic elements of these RCTs, including sample size and estimation method, randomizing scheme, allocation concealment, blind method implementation, data integrity, statistical method, TCM syndrome, intervention measures, treatment course, follow-up time, and outcome indicators, were analyzed to provide reference for the design of future RCT and the clinical application of TCM in treating angina pectoris after PCI. CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, Web of Science, ClinicalTrials.gov, and Chinese Clinical Trial Registry were searched for the RCT about TCM treatment of coronary heart disease patients with angina pectoris after PCI according to pre-defined criteria, with the time interval from inception to January 31, 2024. A total of 188 RCTs were included, of which 184 were clinical research articles and 4 were clinical trial registration schemes. These RCTs involved a total of 15 521 patients, with an average sample size of 83 patients and a maximum sample size of 248 patients. Among them, 126 RCTs reported TCM syndromes, the top three of which were Qi deficiency and blood stasis(38.89%), phlegm combined with stasis(17.46%), and Qi stagnation and blood stasis(9.52%). The control group received guideline-directed medical therapy(GDMT) or GDMT combined with placebo, and the treatment group received GDMT combined with TCM. The treatment mainly lasted for 4-8 weeks, most of the RCTs did not set the follow-up period or the follow-up period was unknown. A total of 160 outcome indicators were used, with the total frequency of 1 348. According to functional attributes, the outcome indicators can be categorized into 6 groups: symptoms/signs(403, 29.90%), TCM syndromes/symptoms(182, 13.50%), physical and chemical examination(468, 34.72%), quality of life(89, 6.60%), long-term prognosis(5, 0.37%), and safety evaluation(201, 14.91%). The clinical trial design of TCM intervention in angina pectoris after PCI of coronary heart disease is becoming more and more rigorous, while it remains to be improved. It is expected that more clinical trial schemes with rigorous design and taking into account the TCM advantages can be adopted in the future to provide a basis for the TCM treatment of angina pectoris after PCI of coronary heart disease.
Humans ; Randomized Controlled Trials as Topic ; Angina Pectoris/drug therapy* ; Coronary Disease/drug therapy* ; Percutaneous Coronary Intervention ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Treatment Outcome ; Female

This umbrella review aimed to summarize and provide a general evaluation of the effectiveness of current treatments for male infertility and assess the quality of evidence and possible biases. An umbrella review of systematic reviews and meta-analyses available in PubMed, Web of Science, and Scopus, covering studies published up to October 2023, was conducted. Sperm concentration, morphology, and motility were used as endpoints to evaluate the effectiveness of the treatments. Of 2998 studies, 18 published meta-analyses were extracted, yielding 90 summary effects on sperm concentration ( n = 36), sperm morphology ( n = 26), and sperm motility ( n = 28) on 28 interventions. None of the meta-analyses were classified as having low methodological quality, whereas 12 (66.7%) and 6 (33.3%) had high and moderate quality, respectively. Of the 90 summary effects, none were rated high-evidence quality, whereas 53.3% ( n = 48), 25.6% ( n = 23), and 21.1% ( n = 19) were rated moderate, low, and very low, respectively. Significant improvements in sperm concentration, morphology, and motility were observed with pharmacological interventions (N-acetyl-cysteine, antioxidant therapy, aromatase inhibitors, selective estrogen receptor modulators, hormones, supplements, and alpha-lipoic acid) and nonpharmacological interventions (varicocele repair and redo varicocelectomy). In addition, vitamin supplementation had no significant positive effects on sperm concentration, motility, or morphology. Treatments for male infertility are increasingly diverse; however, the current evidence is poor because of the limited number of patients. Further well-designed studies on single treatment and high-quality meta-analysis of intertreatment comparisons are recommended.
Humans ; Male ; Antioxidants/therapeutic use* ; Infertility, Male/therapy* ; Meta-Analysis as Topic ; Sperm Count ; Sperm Motility ; Systematic Reviews as Topic

Microwave biosensors are extensively applied in detection of food safety,environmental pollution and biomedical health.Compared to traditional optical and electrochemical sensing solutions,traditional optical and electrochemical sensor detection schemes,microwave sensing shows the advantages of high precision,strong penetration and non-contact detection.Polydimethylsiloxane(PDMS)exhibits numerous favorable characteristics in terms of integration,biocompatibility and processability.The integration of microwave biosensors with PDMS microfluidic chips allows for the full exploitation of the aforementioned advantages,thereby facilitating the provision of rapid,precise,and cost-effective detection solutions.These solutions are of considerable practical significance within the domain of biomedicine.This paper provides an overview of the fundamental characteristics and operational principles of microwave biosensors.It also offers a comprehensive account of the diverse types of microwave biosensors integrated with PDMS microfluidic chips,highlighting their respective advantages and disadvantages.Furthermore,it anticipates the challenges and potential solutions in the development of a novel generation of biosensor chip integration.This is with a view to providing a viable research and development concept for the advancement of medium and large-scale integrated-chip functional microfluidic chips in China.

Objective: To retrospectively analyze the risk factors of anastomotic leakage in the neck after esophageal cancer and establish a nomogram prediction model that can accurately predict the occurrence of anastomotic leakage in the neck of the patient. Methods: The study retrospectively analyzed 702 patients who underwent radical esophageal cancer surgery between January 2010 and May 2015 at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. A multivariate logistic regression model was used to determine the risk factors for neck anastomotic leak, and a nomogram model was constructed, internal validation methods were used to evaluate and verify the predictive effectiveness of the nomogram. Results: There were 702 patients in the whole group, 492 in the training group and 210 in the validation group. The incidence of postoperative cervical anastomotic leak was 16.1% (79/492) in 492 patients with esophageal cancer in the training group. Multifactorial analysis revealed calcification of the descending aorta (OR=2.12, 95% CI: 1.14, 3.94, P=0.018), calcification of the celiac artery (OR=2.29, 95% CI: 1.13, 4.64, P=0.022), peripheral vascular disease (OR=5.50, 95% CI: 1.64, 18.40, P=0.006), postoperative ventilator-assisted breathing (OR=5.33, 95% CI: 1.83, 15.56, P=0.002), pleural effusion or septic chest (OR=3.08, 95% CI: 1.11, 8.55, P=0.031), incisional fat liquefaction and infection (OR=3.49, 95% CI: 1.68, 7.27, P=0.001) were independent risk factors for the development of cervical anastomotic leak after esophageal cancer surgery. The results of the nomogram prediction model showed that the consistency indices of the training and external validation groups were 0.73 and 0.74, respectively (P<0.001), suggesting that the prediction model has good predictive efficacy. Conclusion: The nomogram prediction model can intuitively predict the incidence of postoperative cervical anastomotic leakage in patients with high prediction accuracy, which can help provide a clinical basis for preventing cervical anastomotic leak and individualized treatment of patients.
Humans ; Anastomotic Leak/etiology* ; Nomograms ; Retrospective Studies ; Esophageal Neoplasms/surgery* ; Esophagectomy/methods* ; Risk Factors ; Anastomosis, Surgical/adverse effects*

Objective: To retrospectively analyze the risk factors of anastomotic leakage in the neck after esophageal cancer and establish a nomogram prediction model that can accurately predict the occurrence of anastomotic leakage in the neck of the patient. Methods: The study retrospectively analyzed 702 patients who underwent radical esophageal cancer surgery between January 2010 and May 2015 at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. A multivariate logistic regression model was used to determine the risk factors for neck anastomotic leak, and a nomogram model was constructed, internal validation methods were used to evaluate and verify the predictive effectiveness of the nomogram. Results: There were 702 patients in the whole group, 492 in the training group and 210 in the validation group. The incidence of postoperative cervical anastomotic leak was 16.1% (79/492) in 492 patients with esophageal cancer in the training group. Multifactorial analysis revealed calcification of the descending aorta (OR=2.12, 95% CI: 1.14, 3.94, P=0.018), calcification of the celiac artery (OR=2.29, 95% CI: 1.13, 4.64, P=0.022), peripheral vascular disease (OR=5.50, 95% CI: 1.64, 18.40, P=0.006), postoperative ventilator-assisted breathing (OR=5.33, 95% CI: 1.83, 15.56, P=0.002), pleural effusion or septic chest (OR=3.08, 95% CI: 1.11, 8.55, P=0.031), incisional fat liquefaction and infection (OR=3.49, 95% CI: 1.68, 7.27, P=0.001) were independent risk factors for the development of cervical anastomotic leak after esophageal cancer surgery. The results of the nomogram prediction model showed that the consistency indices of the training and external validation groups were 0.73 and 0.74, respectively (P<0.001), suggesting that the prediction model has good predictive efficacy. Conclusion: The nomogram prediction model can intuitively predict the incidence of postoperative cervical anastomotic leakage in patients with high prediction accuracy, which can help provide a clinical basis for preventing cervical anastomotic leak and individualized treatment of patients.
Humans ; Anastomotic Leak/etiology* ; Nomograms ; Retrospective Studies ; Esophageal Neoplasms/surgery* ; Esophagectomy/methods* ; Risk Factors ; Anastomosis, Surgical/adverse effects*

Humans ; Tricuspid Valve/surgery* ; Heart Valve Prosthesis Implantation ; Surgical Instruments ; Treatment Outcome ; Cardiac Catheterization ; Tricuspid Valve Insufficiency/surgery*

OBJECTIVE: To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes. METHODS: The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score. RESULTS: A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect. CONCLUSION Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.
Humans ; Cell Cycle ; Multiple Myeloma/genetics* ; Prognosis ; Risk Factors