Objective To analyze the predictive value of serum levels of procalcitonin(PCT)and cytokines on the prognosis of patients with COVID-19 at admission.Methods From November 2022 to February 2023,patients diagnosed with COVID-19 who were admitted to Beijing Chest Hospital were enrolled.Chemiluminescence was used to detect serum PCT levels,and flow microsphere array was used to detect serum cytokines IL-1β,IL-2,IL-4,IL-5,IL-6,IL-8,IL-10,IL-12p70,IL-17A,IL-17F,IL-22,TNF-α,TNF-β,IFN-γ level.ICU admission,mechanical ventilation and in-hospital death were defined as poor prognosis.After excluding patients with bacterial infection,the relationship between serum PCT and cytokine levels at admission and the prognosis of COVID-19 patients was analyzed.After excluding patients with bacterial infection,the relationship between serum PCT and cytokine levels at admission and the prognosis of COVID-19 patients was analyzed.Results A total of 176 patients with complete data were included,including 134 in the PCT-normal group and 42 in the PCT-elevated group,with a median age of 71.50 years and 71.59%males.Patients in the PCT elevated-group had significantly higher rates of ICU admission(38.41%vs.13.11%,P<0.05),mechanical ventilation(76.92%vs.24.59%,P<0.001)and in-hospital mortality(38.46%vs.6.56%,P<0.001)were significantly higher than those in the PCT-normal group.Serum levels of cytokines IL-6(7.40 pg/mL vs.4.78 pg/mL,P = 0.033 4)and IL-8(10.97 pg/mL vs.5.92 pg/mL,P<0.001)were significantly higher in patients with poor prognosis than in those with good prognosis.The area under the curve for PCT,IL-6,and IL-8 to predict poor prognosis in COVID-19 patients was 0.687,0.660,and 0.746,respectively;sensitivity was 52.78%,55.17%,and 72.41%,respectively;and specificity was 81.58%,74.19%,and 74.19%,respectively,as calculated from the ROC curve.When PCT,IL-6 and IL-8 jointly predict the prognosis of COVID-19 patients,the area under the curve is 0.764,the sensitivity is 70.00%,and the specificity is 80.00%.Conclusion Serum PCT and cytokines IL-6 and IL-8 could be used as predictive markers for poor prognosis in patients with COVID-19.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Aim To explore the improvement effect of Bazi Bushen capsule on thymic degeneration in SAMP6 mice and the possible mechanism.Methods Twenty 12 week old male SAMP6 mice were randomly divided into the model group(SAMP6)and the Bazi Busheng capsule treatment group(SAMP6+BZBS).Ten SAMR1 mice were assigned to a homologous control group(SAMR1).The SAMP6+BZBS group was oral-ly administered Bazi Bushen capsule suspension(2.8 g·kg-1)daily,while the other two groups were orally administered an equal amount of distilled water.After nine weeks of administration,the morphology of the thymus in each group was observed and the thymus in-dex was calculated;HE staining was used to observe the structural changes of thymus tissue;SA-β-gal stai-ning was used to detect thymic aging;flow cytometry was used to detect the proportion of thymic CD3+T cells in each group;Western blot was used to detect the levels of p16,Bax,Bcl-2,and cleaved caspase-3 proteins in thymus;immunofluorescence was applied to detect the proportion of cortical thymic epithelial cells in each group;ELISA was employed to detect IL-7 lev-els in thymus.Results Compared with the SAMP6 group,the thymic index of the SAMP6+BZBS group significantly increased(P＜0.05);the disordered thy-mic structure was significantly improved;the positive proportion of SA-β-gal staining significantly decreased(P＜0.01);the proportion of CD3+T cells apparently increased(P＜0.05);the level of p16 protein signifi-cantly decreased(P＜0.05);the level of Bcl-2 pro-tein significantly increased(P＜0.05),while the lev-el of cleaved caspase-3 protein markedly decreased(P＜0.05);the proportion of cortical thymic epithelial cells evidently increased;the level of IL-7 significantly increased(P＜0.01).Conclusions Bazi Bushen capsule can delay thymic degeneration,inhibit cell ap-optosis in thymus and promote thymic cell development in SAMP6 mice,which may be related to increasing the proportion of cortical thymic epithelial cells and promoting IL-7 secretion.

OBJECTIVE: To examine the anti-inflammatory effects and potential mechanisms of polypeptide from Moschus (PPM) in lipopolysaccharide (LPS)-induced THP-1 macrophages and BALB/c mice. METHODS: The polypeptide was extracted from Moschus and analyzed by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Subsequently, LPS was used to induce inflammation in THP-1 macrophages and BALB/c mice. In LPS-treated or untreated THP-1 macrophages, cell viability was observed by cell counting kit 8 and lactate dehydrogenase release assays; the proinflammatory cytokines and reactive oxygen species (ROS) were measured by enzyme-linked immunosorbent assay and flow cytometry, respectively; and protein and mRNA levels were measured by Western blot and real-time quantitative polymerase chain reaction (qRT-PCR), respectively. In LPS-induced BALB/c mice, the proinflammatory cytokines were measured, and lung histology and cytokines were observed by hematoxylin and eosin (HE) and immunohistochemical (IHC) staining, respectively. RESULTS: The SDS-PAGE results suggested that the molecular weight of purified PPM was in the range of 10-26 kD. In vitro, PPM reduced the production of interleukin 1β (IL-1β), IL-18, tumor necrosis factor α (TNF-α), IL-6 and ROS in LPS-induced THP-1 macrophages (P<0.01). Western blot analysis demonstrated that PPM inhibited LPS-induced nuclear factor κB (NF-κB) pathway and thioredoxin interacting protein (TXNIP)/nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 (NLRP3) inflammasome pathway by reducing protein expression of phospho-NF-κB p65, phospho-inhibitors of NF-κB (Iκ Bs) kinase α/β (IKKα/β), TXNIP, NLRP3, apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), and pro-caspase-1 (P<0.05 or P<0.01). In addition, qRT-PCR revealed the inhibitory effects of PPM on the mRNA levels of TXNIP, NLRP3, ASC, and caspase-1 (P<0.05 or P<0.01). Furthermore, in LPS-induced BALB/c mice, PPM reduced TNF-α and IL-6 levels in serum (P<0.05 or P<0.01), decreased IL-1β and IL-18 levels in the lungs (P<0.01) and alleviated pathological injury to the lungs. CONCLUSION PPM could attenuate LPS-induced inflammation by inhibiting the NF-κB-ROS/NLRP3 pathway, and may be a novel potential candidate drug for treating inflammation and inflammation-related diseases.

Humans ; Ulcer/pathology* ; Herpesvirus 4, Human ; Epstein-Barr Virus Infections ; Skin Diseases

In recent years, the types and quantities of fentanyl analogs have increased rapidly. It has become a hotspot in the illicit drug control field of how to quickly identify novel fentanyl analogs and to shorten the blank regulatory period. At present, the identification methods of fentanyl analogs that have been developed mostly rely on reference materials to target fentanyl analogs or their metabolites with known chemical structures, but these methods face challenges when analyzing new compounds with unknown structures. In recent years, emerging machine learning technology can quickly and automatically extract valuable features from massive data, which provides inspiration for the non-targeted screening of fentanyl analogs. For example, the wide application of instruments like Raman spectroscopy, nuclear magnetic resonance spectroscopy, high resolution mass spectrometry, and other instruments can maximize the mining of the characteristic data related to fentanyl analogs in samples. Combining this data with an appropriate machine learning model, researchers may create a variety of high-performance non-targeted fentanyl identification methods. This paper reviews the recent research on the application of machine learning assisted non-targeted screening strategy for the identification of fentanyl analogs, and looks forward to the future development trend in this field.
Fentanyl ; Substance Abuse Detection/methods* ; Mass Spectrometry/methods* ; Illicit Drugs/analysis*

【Objective】 To analyze the impact of sporadic cases of COVID-19 on the work of Transfusion Department, so as to explore the countermeasures. 【Methods】 The admission of inpatient departments, the reception of outpatient(including emergency) departments, the workload of transfusion department(including blood typing, unexpected antibody screening and cross matching), and the consumption of blood components in the Xijing Hospital between October and November in 2021, during COVID-19 outbreak, were collected. All the above data was statistically compared to the data in same period in 2018, before the COVID-19 outbreak. 【Results】 Due to the COVID-19 epidemic, there was a significant decrease in number of inpatients(280±157.1 vs 340.4±110.2), outpatient(including emergency)(8 359±3 615 vs 10 151±3 225), the workload of blood typing(272.0±132.4 vs 341.6±110.4), unexpected antibody screening(78.26±42.22 vs 98.51±43.53) and crossmatch(237.2±99 vs 475.7±155.6), as well as the consumption(U) of all blood components(457.9±50.32 vs 579.4±62.51) in the Xijing Hospital(P<0.05). In detail, the epidemic had the most direct impact on the number of inpatients and outpatients, which shrank continuously on the 2^nd day after official announcement of the new COVID-1 cases. While the workload of blood typing, unexpected antibody screening and crossmatch decreased slightly, with a lag, usually on the 2^nd, 3^rd and 5^th day after official announcement. The decrease of the usage of red blood cells and plasma began from the 7^th day after the new epidemic to the 6^th day after the end of the epidemic. However, the usage platelets and cryoprecipitate coagulation factors decreased from the 8^th and 10^th day after the new epidemic to the 2^nd and 6^th day after the end of the epidemic, respectively. 【Conclusion】 The daily work of Blood Transfusion Department has been seriously affected by sporadic COVID-19 epidemic. The working mode, staff structure and inventory ratio of blood components should be adjusted and optimized instantly to maintain the normal conduct of medical treatments in hospitals and ensure the safety of patients.