ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Objective To investigate the application value of quantitative relaxation parameters based on synthetic MRI technology in the differential diagnosis of parotid gland tumors.Methods Conventional MRI and synthetic MRI data of 59 patients with patho-logically confirmed parotid gland tumors were analyzed retrospectively.T1,T2,and proton density(PD)values of the tumor were extracted from T1,T2 and PD mapping.The differences in quantitative relaxation parameters of pleomorphic adenomas,Warthin tumors,and malignant tumors were further compared.Diagnostic performance of each quantitative relaxation parameter was assessed and com-pared via receiver operating characteristic(ROC)curve and DeLong test.Results T2 value was significantly higher in pleomorphic adenomas than that in malignant tumors(P<0.05).The T1,T2,and PD values of pleomorphic adenomas and malignant tumors were significantly higher than those of Warthin tumors(P<0.05).The area under the curve(AUC)of the T2 value in differentia-ting pleomorphic adenomas from malignant tumors was 0.794.The AUC for T1 value(0.939)in differentiating Warthin tumors from malignant tumors was significantly higher than that of T2(0.873,P=0.341)and PD(0.927,P=0.891)values,without sta-tistically significant difference.The AUC for T2 value(0.968)in differentiating pleomorphic adenomas from Warthin tumors was significantly higher than that of T1(0.931,P=0.360)and PD(0.876,P=0.120)values,without statistically significant difference.Conclusion Quantitative relaxation parameters based on synthetic MRI technology may contribute to differentiating pleomorphic adenomas,Warthin tumors,and malignant tumors of the parotid gland.

Objective To compare the diagnostic value of ultrasonography and CT in acute appendicitis.Methods A retrospective analysis was conducted on 279 patients who were diagnosed with acute appendicitis and followed emergency surgery.Patients were divided into different subgroups based on postoperative pathological results and body mass index(BMI),and the pathological results were used as the gold standard to analyze whether there were differences in the diagnostic accuracy of ultrasonography and CT examination for acute appendicitis.Results A total of 279 patients with confirmed acute appendicitis,with 64 cases of simple appendicitis,127 cases of suppurative appendicitis,and 88 cases of gangrenous appendicitis according to pathological classification.The diagnostic accuracy of ultrasonography was 68.75%(44/64),73.22%(93/127),and 81.81%(72/88),respectively.The diagnostic accuracy of CT was 71.87%(46/64),82.67%(105/127),and 90.90%(80/88),respectively.There was no statistically significant difference in diagnostic accuracy between the two examinations(P>0.05).Subgroup analysis based on patient BMI showed that there was no difference in diagnostic accuracy of the two examinations for patients with normal BMI(P>0.05),while for overweight and obese patients,the diagnostic accuracy of CT was better than that of ultrasonography,with a statistical difference(P<0.05).Conclusion There is no difference in the diagnostic accuracy of ultrasonography and CT examinations for acute appendicitis of different pathological types.But for overweight and obese acute appendicitis patients,the diagnostic accuracy of CT examination is superior to ultrasonography.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Circular RNAs (circRNAs) are a kind of non-coding RNA (ncRNA) with covalent closed-loop structure. They have attracted more and more attention because of their high stability, evolutionary conservatism, and tissue expression specificity. It has shown that circRNAs are involved in the development of a variety of diseases including malignant tumors recently. Nasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the nasopharynx and has a unique ethnic and geographical distribution in South China and Southeast Asia. Epstein-Barr virus (EBV) infection is closely related to the development of NPC. Radiotherapy and chemotherapy are the mainstays of treatment for NPC. But tumor recurrence or distant metastasis is the leading cause of death in patients with NPC. Several studies have shown that circRNAs, as gene expression regulators, play an important role in NPC and affect the progression of NPC. This review mainly summarized the research status of abnormally expressed circRNAs in NPC and EBV-encoded circRNAs. We also discussed the possibility of circRNAs as a therapeutic target, diagnostic and prognostic marker for NPC.

Objective To investigate the efficacy of flupentixol combined with ondansetron in preventing postoperative nausea and vomiting(PONV)in patients receiving sufentanil and dezocine patient-controlled intravenous analgesia(PCIA).Methods Surgical patients receiving sufentanil and dezocine PCIA were randomly divided into treatment and control groups using a random number table.The control group received sufentanil 150 μg,dezocine 20 mg,and ondansetron 8 mg for PCIA,while the treatment group received sufentanil 150 μg,dezocine 20 mg,flupentixol 5 mg,and ondansetron 8 mg for PCIA.The incidence of PONV,severity of PONV,heart rate(HR),mean arterial pressure(MAP),blood oxygen saturation(SPO2)levels at different time points after surgery,surgery-related indicators,visual analogue scale(VAS)scores,Ramsay scores,PCIA pressing times,and incidence of adverse drug reactions were compared between the two groups.Results The incidence of PONV in the treatment group and the control group at 2,12,24,36 and 48 hours after surgery were 1.64％,4.84％,6.56％,3.28％,0 and 14.75％,18.03％,19.67％,16.39％,9.84％,respectively.The HR at 24 hours after surgery in the treatment group and the control group were(91.42±8.75)and(98.13±9.62)beat·min-1,respectively;the MAP were(91.98±4.56)and(99.05±4.17)mmHg;SPO2 were(98.13±1.65)％and(98.95±1.82)％;VAS scores were 2.68±0.49 and 2.97±0.63;Ramsay scores were 2.27±0.65 and 2.05±0.32;PCIA pressing times were(2.14±0.37)and(4.36±0.78)times,respectively.The differences in the above indicators between the treatment group and the control group were statistically significant(all P＜0.05).The incidence of total adverse drug reactions after surgery in the treatment group and the control group were 13.12％and 8.20％,respectively,with no statistically significant difference(P＞0.05).Conclusion Flupentixol combined with ondansetron can reduce the risk of PONV caused by sufentanil combined with dezocine PCIA after surgery,ensuring good analgesic effects and safety.

Objective To observe the application effect and safety of continuous adductor canal block(ACB)with different doses of dexmedetomidine(DEX)combined with ropivacaine in postoperative analgesia of total knee arthroplasty(TKA).Methods Patients with TKA were enrolled as the research subjects and were divided into low-dose group,middle-dose group and high-dose group by the random number table method.At 10 min before induction of general anesthesia,all the groups were given 20 mL of 0.5％ropivacaine loading dose for ACB,placed nerve block indwelling catheter,and started ACB analgesia pump after the end of surgery.Low-dose group,middle-dose group and high-dose group were given 0.5,1.0 and 1.5 μg·kg-1 DEX+0.25％ropivacaine for a total of 100 mL,with a background dose of 4 mL·h-1and a control dose of 4 mL,and they locked for 30 min and continuously treated for 48 h.The surgical parameters and postoperative recovery quality of the two groups were compared.Visual analogue scale(VAS)was used to evaluate the pain status in resting state and motion state at 2,6,12,24 and 48 h after surgery.The number of effective compressions of self-controlled analgesia pump and the dosage of remedial analgesics at 48 h after surgery were counted and the safety evaluation was performed.Results No cases dropped out during treatment,and finally 30 cases were included in low-dose,middle-dose and high-dose groups,respectively.The first ambulation times in low-dose,middle-dose and high-dose groups were(54.22±8.37),(47.68±7.65)and(52.79±8.74)h;the time of active knee flexion 90° were(8.90±3.10),(7.20±2.70)and(8.60±2.40)d;the motion VAS scores were(3.86±0.59),(3.57±0.51)and(3.48±0.52)points at 48 h after surgery;the times of first analgesia pump compression within 48 h after surgery were(10.57±3.87),(12.45±3.63)and(13.36±3.56)h;the number of effective compressions of self-controlled analgesia pump were(6.11±2.18),(3.76±1.14)and(3.24±1.07)times;the remedial analgesia rates were 13.33％,0 and 0;at 6 h after surgery,quadriceps muscle strength scores were(4.81±0.21),(4.75±0.23)and(4.61±0.26)points,and the incidence rates of adverse drug reactions were 20.00％,6.67％and 6.67％,respectively.There were statistically significant differences in the above indicators between low-dose group and middle-dose group except for the incidence of adverse drug reactions(all P＜0.05).There were statistical differences between low-dose group and high-dose group except for the incidence of adverse drug reactions(all P＜0.05),but there were no statistical differences between middle-dose group and high-dose group(all P＞0.05).Conclusion The use of 1.0 μg·kg-1DEX combined with ropivacaine for ACB in TKA patients can achieve good postoperative analgesia effect and it has small impact on muscle strength and has good safety,thus this dose can be used as a clinical recommended dose.

Objective To explore the effect of rifampicin on the pharmacokinetics of linezolid in mice and provide pharmacokinetic evidence for the formulation of safe drugs for clinical use of pulmonary tuberculosis.Methods Fifty male KM mice were randomly divided into 2 groups:Control group,rifampicin group;the control group was given 15 mg·kg-1 linezolid;the rifampicin group was given 100 mg·mL-1 rifampicin,continuous administration for 7 days,followed by gavage,administration of 15 mg·kg-1 linezolid;blood and lung tissue were collected from mouse at different time points after administration.High performance liquid mass spectrometry(LC-MS/MS)was used to determine plasma concentration of linezolid and compared the pharmacokinetics between groups.Pharmacokinetic parameters were calculated using DAS 2.0 software.Results Main pharmacokinetic parameters of plasma linezolid in control group,rifampicin group were as follows:AUC0_t were(23.88±1.16)and(19.06±2.56)pg·mL-1·h,respectively;t1/2 were((1.15±0.11)and(1.11±0.10)h,respectively;Cmax were(9.93±0.46)and(7.74±1.17)μg·mL-1,respectively.The main pharmacokinetic parameters of the lungs in the control group and the rifampicin group were as follows:AUC0_t were(18.76±4.29)and(14.90±1.52)μg·mL-1·h,respectively;t1/2 were(1.94±0.50)and(1.44±0.07)h,respectively;Cmax were(8.28±2.67)and(6.82±1.57)μg·mL-1,respectively.AUC0_t and Cmax in plasma and AUC0_t in lung tissue of control group were significantly different from those of rifampicin group(all P＜0.05).Conclusion After the combination of rifampicin,linezolid plasma and lung tissue exposure decreased significantly,and attention should be paid to monitoring linezolid trough concentration when the two drugs were combined to avoid treatment failure caused by low effective concentration.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Objective:To explore the prognostic value of baseline 18F-FDG PET/CT metabolic parameters in locally advanced cervical cancer (LACC) after concurrent chemoradiotherapy (CCRT). Methods:From September 2015 to October 2021, the clinical data of 180 LACC patients (age: 22-76 years) who underwent 18F-FDG PET/CT before CCRT at Affiliated Cancer Hospital of Shandong First Medical University were analyzed retrospectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV max, and SUV mean were computed by using the margin threshold of 42%SUV max. The optimal threshold for predicting progression-free survival (PFS) was obtained by ROC curve analysis. The Kaplan-Meier method was applied for survival analysis, and the log-rank test was applied to compare the survival rate between groups. Multivariate Cox proportional hazard regression was used to analyze progression for PFS. Results:The median follow-up was 19.1 months, and 54 patients (30.0%, 54/180) suffered from disease progression. ROC curve analysis showed that the optimal cut-off value of MTV was 31.145 ml, with the AUC of 0.641. Para-aortic lymph node (PALN) metastasis had the highest AUC value (0.589) among the clinical factors, followed by International Federation of Gynecology and Obstetrics (FIGO) stage (0.581). The 1-year PFS rates of patients with MTV<31.145 ml ( n=88) and MTV≥31.145 ml ( n=92) were 80.68% and 59.78%, respectively ( χ2=13.72, P<0.001). Multivariate Cox analysis demonstrated that pathological type (hazard ratio ( HR)=3.075, 95% CI: 1.370-6.901, P=0.006), FIGO stage ( HR=1.955, 95% CI: 1.031-3.707, P=0.040), PALN metastasis ( HR=2.136, 95% CI: 1.202-3.796, P=0.010) and MTV ( HR=2.449, 95% CI: 1.341-4.471, P=0.004) were the significant predictors for PFS. Conclusions:Pathological type, FIGO stage, PALN metastasis and MTV are independent prognostic risk factors for PFS. MTV as the baseline 18F-FDG PET/CT metabolic parameter, can realize prognostic stratification analysis.