OBJECTIVE: To explore clinical efficacy of membrane-induced technique combined with gastrocnemius muscle flap transposition in treating traumatic osteomyelitis of the upper tibia. METHODS: A retrospective analysis was conducted on 7 patients with traumatic osteomyelitis of the upper tibia who were treated with membrane-induced technique combined with gastrocnemius muscle flap transposition from January 2022 to December 2023. Among them, there were 4 males and 3 females; aged from 29 to 57 years old; 4 patients were treated after open fracture, 2 patients were treated after closed fracture, and 1 patient was treated after scalding; the courses of disease ranges from 2 weeks to 8 years; sinus tracts were present in all patients, and the lesion range of the tibia ranged from 5 to 9 cm. The results of deep tissue bacterial culture showed that 2 patients were negative, 3 patients were staphylococcus aureus, 1 patient was methicillin-resistant staphylococcus aureus, and 1 patient was pseudomonas aeruginosa and 1 patient was klebsiella pneumoniae. After debridement, the range of bone defect ranged from 8 to 12 cm, and the cortical defect accounted for approximately 30% of the circumference. The area of soft tissue defect ranged from 8.0 cm×2.0 cm to 10.0 cm×6.0 cm. At the first stage, vancomycin-loaded/meropenem/gentamicin-loaded bone cement was implanted. The gastrocnemius muscle flap was repositioned to cover the wound surface and free skin grafting was performed. After an interval of 7 to 10 weeks, the stageⅡsurgery was performed to remove bone cement. Autologous iliac bone mixed with vancomycin/gentamicin and calcium sulfate artificial bone was transplanted, and the wound was sutured. One patient retained the original internal plants, one patient removed the internal plants and replaced them with steel plate external fixation, one patient replaced the internal plants and added steel plate external fixation, and three patients were simply fixed with steel plate external fixation. One year after operation, the recovery of knee joint and ankle joint functions was evaluated by using Hospital for Special Surgery (HSS) knee joint score and Kofoed ankle joint function score respectively. RESULTS: All patients had their wounds closed simultaneously with bone cement implantation and healed well. All patients were followed up for 12 to 17 months after operation, and satisfactory bone healing was achieved at 6 months after stageⅡsurgery. Twelve months after operation, all patients had good bone healing without obvious limping was observed when walking. At 12 months after operation HSS knee joint score ranged from 93 to 100 points, and Kofoed ankle function score ranged from 96 to 100 points. CONCLUSION For traumatic osteomyelitis of the upper tibia, a staged treatment plan combining membrane-induced technique and gastrocnemius flap transposition on the basis of thorough debridement could safely cover the wound surface, effectively control bone infection and achieve satisfactory bone healing, without adverse effects on limb function.
Humans ; Male ; Female ; Middle Aged ; Osteomyelitis/surgery* ; Adult ; Surgical Flaps ; Retrospective Studies ; Tibia/injuries* ; Muscle, Skeletal/surgery*

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

Adolescent idiopathic scoliosis(AIS)is a complex three-dimensional deformity involving coronal,sagittal,and axial planes,with a prevalence that should not be overlooked.With advancements in technology and in-depth research,an increasing number of hospitals and physicians are exploring standardized diagnostic and treatment approaches for AIS.Comprehensive and in-depth understanding is required for AIS,including its etiology,screening and diagnosis,classification,assessment and examination,treatment options,exploration of current focus,and evaluation of quality of life.Such understanding ensures that the diagnostic and treatment are scientific,standardized,and timely.Based on the principles of evidence-based medicine,a consensus on the diagnosis and treatment of AIS is reached after multiple discussions among spinal surgery experts,aiming to provide reference and guidance for clinical practice.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

ObjectiveTo investigate the noise level and influencing factors in metro platforms and station halls， thereby providing the scientific basis for the establishment of hygienic standards. MethodsDuring the morning peak（7：00‒9：30）and off-peak （9：30‒17：00） on weekdays， the noise levels were measured with noise meters at 39 monitoring points of 13 station platforms and 31 monitoring points of 6 station halls. The monitoring points arrangement and detection methods referred to the Examination methods for public places—Part 1： physical parameters（GB/T 18204.1‒2013）. ResultsThe measured noise level in the station ranged from 69.25 to 86.17 dB（A）， accounting for 44.74% below 75 dB（A）， 89.47% below 80 dB（A） and 97.37% below 85 dB（A）.The noise level of the platform ［（76.38±4.19） dB（A）］ was higher than that of the station hall ［（74.24±4.50） dB（A）］（P<0.01）. The noise level of the elevated platforms ［（80.01±2.25） dB（A）］ was higher than that of the underground platforms ［（75.73±4.13） dB（A）］（P<0.01）， and the noise level of the platforms without platform screen doors（PSD） ［（80.21±5.08） dB（A）］ was higher than that of platforms with PSD［（74.73±3.16） dB（A）］ （P<0.01）. No statistical significant differences were observed among the different areas of the platforms， monitoring periods， platform depth， exit mode and operation years （P>0.05）. ConclusionThe noise level in metro stations in the city does not fully meet the requirements of current relevant standards. It is suggested to take noise reduction measures to reduce the noise of metro stations.

Objective:To investigate the effects of low-frequency and high frequency repetitive transcranial magnetic stimulation (rTMS) combined with levodopa and benserazide hydrochloride on mild cognitive impairment in patients with Parkinson disease (PD).Methods:Totally 90 PD patients with mild cognitive impairment who visited from January 2020 to June 2022 were included , and they were divided into a simple drug group ( n=30), drug+ low-frequency group ( n=30), and drug+ high-frequency group ( n=30) according to the order of admission.The patients in the simple drug group were treated with oral levodopa and benserazide hydrochloride, while the patients in drug+ low-frequency and drug+ high-frequency groups were treated with low-frequency or high-frequency rTMS on the basis of oral levodopa and benserazide hydrochloride.Montreal cognitive assessment(MoCA), digital span (DS), Chinese auditory learning test (CALT), the judgment of line orientation test (JLOT) and verbal fluency test (VFT) were used to evaluate the cognitive function of patients before and after 4 weeks of treatment.SPSS 26.0 was used for statistical analysis.The paired t-test was used for intra-group comparison before and after treatment, while one-way ANOVA was used for inter-group comparison. Results:There were no significant differences in MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT, and VFT scores among patients in the simple drug group before and after 4 weeks of treatment( t=-1.157, -0.648, -0.215, -0.290, -0.154, -0.782, -0.960, all P>0.05). After 4 weeks of treatment, MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT scores in drug+ low-frequency group and drug+ high-frequency group were higher than before treatment (drug+ low frequency group: t=-16.357, -11.379, -7.999, -11.805, -16.624, -15.996, -17.241, all P<0.05; drug+ high-frequency group: t=-25.198, -13.971, -13.904, -25.831, -26.382, -20.108, -15.643, all P<0.05). There were no statistically significant differences in the scores of MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT among the three groups before treatment (all P>0.05). After treatment, there were statistically significant differences in the scores of MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT among the three groups (simple drug group : (20.37±1.96), (4.37±1.19), (2.80±0.55), (6.93±1.70), (5.17±1.09), (15.50±2.69), (10.73±1.55); drug+ low-frequency group: (23.83±2.32), (5.87±0.94), (3.87±0.73), (9.17±1.74), (8.13±1.50), (20.77±2.19), (13.30±1.73); drug+ high-frequency group: (27.17±1.64), (6.73±1.01), (4.80±0.81), (11.20±2.06), (10.03±1.54), (25.17±3.14), (15.87±2.05)) (all P<0.05). Further analysis showed that both the drug+ low-frequency and drug+ high-frequency groups had higher scores than the simple drug group, and the drug+ high-frequency group had higher scores than the drug+ low-frequency group(all P<0.05). Conclusion:The combination of drug+ low-frequency or drug+ high-frequency rTMS and drug therapy can help improve cognitive function in patients with PD, and the efficacy of drug+ high-frequency rTMS may be more significant, which provides a new therapeutic idea for clinical treatment of patients with PD.

ObjectiveTo establish a UHPLC-MS/MS quantitative method for the determination of glucuronic acid， tartaric acid， glycolic acid， malic acid， lactic acid， citric acid， DL-2-hydroxybutyric acid sodium， mandelic acid， benzilic acid， hydroxycaprylic acid， lactobionic acid， gluconic acid and N-acetylneuraminic acid in cosmetics. MethodsSamples were prepared by ultrasonic extraction， cleansed by precipitating reagent and followed by high-speed centrifugation of the extraction solution. The supernatant was filtered by 0.22 μm Millipore filter. The continued filtrate was taken for analysis. A reversed phase column， Poroshell 120 EC-C₁₈ （2.7 μm， 4.6 mm×1 000 mm） was used with 0.1% formic acid buffer and acetonitrile as the mobile phase under the condition of gradient elution. The analytes were detected with electrospray ionization source in negative ion mode （ESI^-） and multiple reactions monitoring （MRM）， and quantified by external standard curve. ResultsThe method showed a good linearity of glucuronic acid， tartaric acid， malic acid， DL-2-hydroxybutyric acid sodium， benzilic acid， hydroxycaprylic acid and N-acetylneuraminic acid within the concentration range of 50.0‒2 000.0 μg·L^-1 （r>0.995）. The method showed a good linearity of glycolic acid， lactic acid， citric acid and mandelic acid within the concentration range of 100.0‒5 000.0 μg·L^-1 （r>0.995）. The method showed a good linearity of lactobionic acid and gluconic acid within the concentration range of 50.0‒5 000.0 μg·L^-1 （r>0.995）. The recoveries were in the range of 92.3%‒114.1%； the relative standard deviations （RSD） were in the range of 0.9%‒6.0% （n=3）. The detection limits of glucuronic acid， tartaric acid， malic acid， citric acid， DL-2-hydroxybutyric acid sodium， mandelic acid， benzilic acid， hydroxycaprylic acid， lactobionic acid， gluconic acid and N-acetylneuraminic acid were 0.003% while the detection limits of glycolic acid， lactic acid and mandelic acid were 0.006%. In 10 batches of commercially available cosmetics， eight batches showed positive result. ConclusionThe UHPLC-MS/MS method is efficient， sensitive and accurate and is applicable to the determination of 13 α-hydroxy acidic components in cosmetics.

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.

During the progression of heart failure(HF),abnormal transduction of the transforming growth factor-β(TGF-β)/Smads signaling pathway is important mechanism of myocardial fibrosis(MF)in HF.TGF-β,a key factor in MF,is in an overexpression state in the process of MF in HF,and Smads is a major effector downstream of TGF-β.The TGF-β/Smads pathway induces abnormal proliferation of myofibroblasts,aggravates myocardial extracellular matrix deposition,and reduces the ability of the cardiac tissues to resist fibrosis,which plays a complex role in the pathogenesis of MF in HF.Traditional Chinese medicine(TCM)has the efficacy of unequivocal inhibiting myocardial collagen deposition,anti-MF,protecting the myocardium and improving cardiac function in the prevention and treatment of MF in HF and so on,and the TGF-β/Smads pathway is one of the key pathways through which TCM monomers,TCM combinations,and proprietary medicines can exert their cardioprotective effects on the HF.This paper reviews the existing experimental research results of TCM intervening in the TGF-β/Smads pathway for the treatment of MF in HF over the past 10 years,with a view to providing theoretical basis for the prevention and treatment of HF MF well as the development and of new drugs.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.