After the wooden shipwreck was recovered from the marine underwater environment,the wooden components undergo varying degrees of degradation,therefore,accurately determining the extent of degradation is a fundamental scientific issue for implementing effective preservation strategies.In this work,the wooden remains of Pinus massoniana excavated from the"Nanhai No.1"shipwreck(Southern Song Dynasty)were investigated and compared with the modern wood to discriminate the degradation levels of archaeological wood using attenuated total reflection Fourier transform infrared(ATR-FTIR)spectroscopy.The residual sugar content within wood cell walls was determined using a non-invasive automated microscale ATR-FTIR method to extract chemical information from the wood tangential section.Microstructural characterization of wood samples was conducted by super depth of field microscopy and scanning electron microscopy.FTIR spectral analysis was performed to evaluate the degradation state and elucidate changes in cellulose crystallinity.Finally,the combination of FTIR spectroscopy with the sparse partial least squares discriminant analysis(sPLS-DA)model facilitated the rapid discrimination of degradation levels in shipwreck archaeological wood,and the performance of the model was evaluated using receiver operating characteristic(ROC)curves and area under the curve(AUC).The results showed that the higher the degree of wood degradation,the lower the residual sugar content in the wood cell wall,and the residual glucose content of highly degraded wood was only 4.7％.Significant differences were observed in both the tangential section microstructure and FTIR characteristic absorption patterns across degradation levels,and as the degradation advanced,progressive cell wall loosening occurred alongside selective removal of polysaccharide components,and the relative lignin content was increased,resulting in an elevated A1509/A1370 ratio in FTIR spectra.The sPLS-DA model achieved excellent discrimination performance with AUC values exceeding 0.9,confirming that the combination of FTIR spectroscopy with sPLS-DA enabled accurate assessment of degradation levels in shipwreck archaeological wood.This study developed a rapid and accurate methodology for assessing degradation levels in shipwreck archaeological wood based on microscale ATR-FTIR spectroscopy,which would help to promote the accurate assessment of the preservation state of waterlogged wooden artifacts.

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.

Intraoperative neural monitoring (IONM) combines electrophysiology with anatomy to monitor nerve function during thyroid surgery,and has become an important auxiliary technology for neuroprotection. After more than ten years of development,the technology has been widely applied and popularized in China,promoting the development of a number of new technologies in the industry. Combined with the questionnaire survey data of the Chinese Neural Monitoring Study Group,this paper aims to summarize the clinical effect of IONM technology, the application status and existing problems at home and abroad, and propose the possible future development direction.

Intraoperative neural monitoring (IONM) combines electrophysiology with anatomy to monitor nerve function during thyroid surgery,and has become an important auxiliary technology for neuroprotection. After more than ten years of development,the technology has been widely applied and popularized in China,promoting the development of a number of new technologies in the industry. Combined with the questionnaire survey data of the Chinese Neural Monitoring Study Group,this paper aims to summarize the clinical effect of IONM technology, the application status and existing problems at home and abroad, and propose the possible future development direction.

The abuse and irrational use of antibiotics in human veterinary medicine has seriously endangered the ecological environment and human health.In this study,a fully automatic solid-phase disk extraction-stable isotope dilution-ultra-high performance liquid chromatography-mass spectrometry method for determination of 17 kinds of sulfonamides antibiotics(SAs)in water was established,which was then applied to determination of SAs in real samples including tap water,river water and seawater,respectively.Meanwhile,the residual characteristics were discussed and the ecological risks were assessed.With this method,1.0 L water sample with 0.5 g/L Na2EDTA(pH=3)was extracted and enriched by 3M SDB-XC disk,and eluted by 10 mL of mixture of methanol and acetone(1:1,V/V),and the pretreatment time of the sample was about 60 min per six samples.Under the optimized conditions,the linearity of the method for detection of 17 kinds of SAs ranged from 0.05 to 100 μg/L,with correlation coefficients(R2)>0.999.In addition,the detection limits(S/N=3)were as low as 0.012-0.052 ng/L,and the recoveries were in the range of 76%-110%,with relative standard deviations of 0.5%-9.6%(n=5).The results showed that no SAs was detected in tap water,while 3 and 9 kinds of SAs were detected in river water of Zhoushan,and seawater of Wenzhou Sea area in Zhejiang province,respectively.The total concentrations of the detected SAs were 0.875-21.826 ng/L and 1.024-20.768 ng/L in river water and seawater,respectively,and among which,sulfamethoxazole(SMX)was the predominant compound in river water and seawater,accounting for 81%and 74%of the total SAs,respectively.The ecological risk assessment showed that the risk quotients of the detected SAs in the river water and seawater in the study area for the three kinds of trophic organisms(algae,Daphnia and fish)were far less than 0.01,meaning that the ecological risk was low.

Further evidence is needed to explore the impact of high-altitude environments on the neurologic function of neonates.Non-invasive techniques such as cerebral near-infrared spectroscopy and amplitude-integrated electroencephalography can provide data on cerebral oxygenation and brain electrical activity.This study will conduct multiple cerebral near-infrared spectroscopy and amplitude-integrated electroencephalography monitoring sessions at various time points within the first 3 days postpartum for healthy full-term neonates at different altitudes.The obtained data on cerebral oxygenation and brain electrical activity will be compared between different altitudes,and corresponding reference ranges will be established.The study involves 6 participating centers in the Chinese High Altitude Neonatal Medicine Alliance,with altitude gradients divided into 4 categories:800 m,1 900 m,2 400 m,and 3 500 m,with an anticipated sample size of 170 neonates per altitude gradient.This multicenter prospective cohort study aims to provide evidence supporting the impact of high-altitude environments on early brain function and metabolism in neonates.[Chinese Journal of Contemporary Pediatrics,2024,26(4):403-409]

Anesthesia machines are important auxiliary equipment for clinical anesthesia. Doctors and engineers should actively grasp the key technical progress in anesthesia equipment and deal with the problems and risks associated with its use. To summarize and analyze the clinical progress and application trends of key anesthesia technologies,such as automatic detection of anesthesia equipment,low flow,target control,depth prediction,lung protection and the combination of static and inhalation anesthesia,and to discuss thinking of fault analysis,formulation of maintenance strategy,and troubleshooting methods by combining hardware and software based on common faults of anesthesia equipment and maintenance examples. The aim is to provide thinking for reducing the workload and improve the quality of medical care of medical institutions,and to provide partial guidance for doctors and engineers working in medical institutions.

Anesthesia machines are important auxiliary equipment for clinical anesthesia. Doctors and engineers should actively grasp the key technical progress in anesthesia equipment and deal with the problems and risks associated with its use. To summarize and analyze the clinical progress and application trends of key anesthesia technologies,such as automatic detection of anesthesia equipment,low flow,target control,depth prediction,lung protection and the combination of static and inhalation anesthesia,and to discuss thinking of fault analysis,formulation of maintenance strategy,and troubleshooting methods by combining hardware and software based on common faults of anesthesia equipment and maintenance examples. The aim is to provide thinking for reducing the workload and improve the quality of medical care of medical institutions,and to provide partial guidance for doctors and engineers working in medical institutions.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Aim To explore the effect of four stilbenes including rhaponticin, desoxyrhaponticin, rhapontigenin and resveratrol on glucose and lipid metabolism in insulin-resistant HepG2 cells induced by high glucose and high fat. Methods The model of insulin resistance was established by incubating HepG2 cells with a complex of glucose and oleic acid. MTT assay was used to detect cell viability. The intracellular triglyceride (TG) and glucose levels were measured by the kit method. The lipid production was observed by oil red O staining, and the cell morphology and uptake of 2-NBDG were observed by confocal microscope. The PPAR signaling pathway and PI3K/Akt insulin signaling pathway related proteins were determined by Western blot to evaluate the effect of stilbenes on glycolipid metabolism in IR-HepG2 cells. Results The complex containing 50 mmol • L