Objective To investigate the effect of remifentanil pretreatment on lipid peroxidation following acute myocardial ischemia/reperfusion (1/R) in rabbits. MethodsForty healthy adult rabbits of both sexes weighing 1.5-2.5 kg were randomly divided into 5 groups (n = 8 each): group control (group Ⅰ ); group I/R(group Ⅱ ); group morphine pretreatment + I/R (group Ⅲ ); group remifentanil (group Ⅳ ) and group remifentanil pretreatment + I/R (group Ⅴ ). The animals were anesthetized with intraperitoneal 2％ pentobarbital 45 mg/kg and were mechanically ventilated after tracheal intubation. PET CO2 was maintained between 35-45 mm Hg. Myocardial I/R was induced by iv pituitrin 2.5 U/kg in group Ⅱ , Ⅲ and Ⅴ. In group Ⅰ and Ⅳ normal saline 0.3 ml/kg was injected iv instead of pituitrin. In group Ⅲ morphine 3.3 mg/kg was injected iv at 30 min before iv pituitrin. In group Ⅳ and V remifentanil was infused at 3.3 μg· kg-1 ·min-1 for 30 min before iv normal saline and pituitrin.Venous blood samples were taken before (baseline) and at 24 h and 48 h after iv pituitrin for determination of serum cTnI concentration. The myocardial specimens were taken at T3 after blood sampling for microscopic examination and determination of SOD activity and MDA content. ResultsIntravenous pituitrin 2.5 U/kg significantly increased serum cTnI concentration and myocardial MDA content and decreased myocardial SOD activity in group Ⅱas compared with group Ⅰ . Morphine or remifentanil preatment significantly attenuated the myocardial I/R-induced changes mentioned above. Microscopic examination showed that myocardial tissue damages were ameliorated in group V as compared with group Ⅱ . ConclusionRemifentanil pretreament can attenuate acute myocardial ischemic injury by inhibiting lipid peroxidation.

Objective To characterize contemporary electrographic neonatal seizures by video electroencephalogram (VEEG) and to assess the value and the limitations of two-channel (C3-C4/T3-T4) amplitude-integrated electroencephalogram (aEEG) plus original EEG signals used to diagnose neonatal seizure with video EEG as a golden standard.Methods Sixty-six neonates admitted to Children's Hospital of Fudan University from January 2011 to July 2011 with clinical or suspected clinical seizure were investigated and bedside VEEG were recorded for more than 3 hours.VEEG signals were transformed into three kinds of aEEG signals by Galileo NT PMS software:one-channel aEEG (C3-C4),one-channel aEEG (C3-C4) plus original EEG,two-channel aEEG (C3-C4/T3-T4) plus original EEG.Electrical seizure activity on VEEG was signed out with respect to its occurrence,duration and localization of seizure onset; while aEEG seizure was recorded only with its occurrence.The relationship between aEEG and VEEG was analyzed by Spearman analysis.The value and the limitations of aEEG to diagnose neonatal seizure were evaluated by sensitivity,specificity,positive predictive value and negative predictive value.Results A total of 62 traces were suitable for analysis.(1) VEEG showed 39 seizure activities,among which 8 status epilepticus; and the rest 31 neonates had 352 non-status epilepticus electrical seizures,79.3％ (279/352) of which occurred over the centrotemporal region.(2) Eight cases with status epilepticus on VEEG were all diagnosed as status epilepticus on aEEG.For non-status epilepticus electrical seizures,the sensitivity of aEEG for detection of electrical seizures was as followed:49.1％ (173/352) for one-channel aEEG,54.5 ％ (192/352) for one-channel aEEG plus original EEG,81.2％ (286/353) for two-channel aEEG plus original EEG.Results from one-channel aEEG,one-channel aEEG plus original EEG and two-channel aEEG plus original EEG were all related to VEEG (ρ =0.790,0.907 and 0.953,respectively,P＜ 0.01).(3) Sensitivity of seizure detection was 66.7％ (26/39,95％ CI:0.62-0.81) for one-channel aEEG,74.4％(29/39,95％ CI:0.78-0.96) for one-channel aEEG(C3-C4) plus original EEG and 89.7％ (35/39,95％ CI:0.89-1.00) for two-channel aEEG(C3-C4/T3-T4) plus original EEG.Conclusions VEEG might help aEEG in diagnosis of neonatal seizure.two-channel aEEG (C3-C4/T3-T4) plus original EEG could significantly increase the sensitivity of neonatal seizures indentification.

Objective:To analyze the characteristics of spread and genetic evolution of H5 subtype avian influenza virus in Guangzhou from 2014 to 2019.Methods:H5 subtype virus was detected by fluorescence quantitative RT-PCR from the environmental samples in Guangzhou poultry markets. The genes of HA and NA of 48 isolates randomly selected were sequenced, including 46 isolates from environmental samples and 2 isolates from cases. The characteristics of molecular variation and genetic evolution were analyzed by using bioinformatics software.Results:A total of 1 094 strains of H5 subtype avian influenza virus were isolated from 52 284 samples (2.09%). All the strains belonged to Clade 2.3.4.4.C. NA gene belonged to H6N6 of Eurasian lineage. The cleavage sites of all the strains showed the characteristics of highly pathogenicity. Receptor binding sites were avian-derived receptors. However, mutations of S123P, S133A and T156A occurred, which implied that these strains could tend to bind to human receptors. There was an additional glycosylation site at 140 in strains isolated after 2017. The variation of antigen loci mainly occurred in B and E regions.Conclusions:H5 subtype avian influenza virus spread in Guangzhou from 2014 to 2019 with annual increased proportion of positive rate, and the sequencing results indicated that it belonged to Clade 2.3.4.4.C of H5N6 highly pathogenic virus, and genetic evolution and mutation continued, especially the common mutations which could enhance the binding capacity to human receptors. It is necessary to strengthen the surveillance.

Objective:To isolate the influenza A (H3N2) viruses from different sources in Guangzhou in 2019 and analyze these viruses' evolution and variation characteristics.Methods:The hemagglutinin (HA) and neuraminidase (NA) genes of H3N2 isolates from outpatient monitoring, influenza outbreaks, and inpatient severe cases in Guangzhou in 2019 were sequenced. Bioinformatics software analyzed the variations and evolution characteristics of HA and NA genes.Results:The epidemic peaks of influenza A (H3N2) viruses were made up of period Ⅰ (from January to August) and period Ⅱ (from November to December). The positive rate of influenza A (H3N2) in males was 13.46% (703/5 221), which was higher than that in females (11.50%, 510/4 435) ( χ 2=8.43, P=0.00). The group's positive rate of 10-20 years old was the highest (25.18%,665/2 641). The isolates from different sources were highly homologous and closely related to 3C.2a.1 branches, which could be further divided into three small groups of Group 1-3. Gene recombination was observed between different branches. The mutations of HA antigen sites gradually appeared from Group 1 to Group 3, leading to new antigen drift. Variations of HA antigenic sites mainly occurred in the region of A and B. The mutations of receptor binding sites of Group 1 and Group 3 viruses occurred in the anterior and posterior walls. There were two glycosylation sites lacked on region A of HA antigen observed in the isolates of Group 2-3. Conclusions:Genetic variations of H3N2 influenza viruses in Guangzhou included gene mutations and gene recombination. Under the pressure of the vaccine, the evolution of viruses was rapid. Therefore, the monitoring of molecular-related epidemic characteristics of the H3N2 influenza virus was necessary.

To monitor and analyze the molecular variation of the H3N2 influenza virus in Guangzhou during the COVID-19 pandemic, respiratory samples of influenza-like cases from influenza monitoring sentinel hospitals were collected from influenza monitoring sentinel hospitals for virus isolation and whole genome sequencing. The results showed that during COVID-19, there was only one peak of H3N2 influenza in the second quarter of 2022 in Guangzhou (the positive rate was 52.23%), and the epidemic intensity and duration were both higher than those in 2019. The HA gene and NA gene of the epidemic strain in Guangzhou in 2022 belonged to the 3C.2a1b. 2a. 1a. 1 branch, which had a good antigenic site matching with the vaccine strain (A/Cambodia/e0826360/2020) from 2021 to 2022 and had no antigen drift. In 2022 strains, the variation of antigen determinant mainly occurred in the I48T of C region, while no variation occurred in the A, B, D, and E regions. The binding site of the HA protein receptor was consistent with the vaccine strain (A/Cambodia/e0826360/2020). Most of the strains in 2022 carried 13 glycosylation sites on the HA protein, but an outbreak of strains caused a loss of glycosylation sites at 24-NST. In conclusion, the strains that caused the epidemic of H3N2 influenza in Guangzhou in 2022 were not evolved or transmitted from the local strains in 2019 during the COVID-19 pandemic.

To monitor and analyze the molecular variation of the H3N2 influenza virus in Guangzhou during the COVID-19 pandemic, respiratory samples of influenza-like cases from influenza monitoring sentinel hospitals were collected from influenza monitoring sentinel hospitals for virus isolation and whole genome sequencing. The results showed that during COVID-19, there was only one peak of H3N2 influenza in the second quarter of 2022 in Guangzhou (the positive rate was 52.23%), and the epidemic intensity and duration were both higher than those in 2019. The HA gene and NA gene of the epidemic strain in Guangzhou in 2022 belonged to the 3C.2a1b. 2a. 1a. 1 branch, which had a good antigenic site matching with the vaccine strain (A/Cambodia/e0826360/2020) from 2021 to 2022 and had no antigen drift. In 2022 strains, the variation of antigen determinant mainly occurred in the I48T of C region, while no variation occurred in the A, B, D, and E regions. The binding site of the HA protein receptor was consistent with the vaccine strain (A/Cambodia/e0826360/2020). Most of the strains in 2022 carried 13 glycosylation sites on the HA protein, but an outbreak of strains caused a loss of glycosylation sites at 24-NST. In conclusion, the strains that caused the epidemic of H3N2 influenza in Guangzhou in 2022 were not evolved or transmitted from the local strains in 2019 during the COVID-19 pandemic.

Objective:To identify a novel reassortant H3N2 avian influenza virus using nanopore sequencing technology and analyze its genetic characteristics.Methods:The positive samples of the H3N2 avian influenza virus, collected from the external environment in the farmers' market of Guangzhou, were cultured in chicken embryos. The whole genome was sequenced by targeted amplification and nanopore sequencing technology. The genetic characteristics were analyzed using bioinformatics software.Results:The phylogenetic trees showed that each gene fragment of the strain belonged to the Eurasian evolutionary branch, and the host source was of avian origin. The HA gene was closely related to the origin of the H3N6 virus. The NA gene was closely related to the H3N2 avian influenza virus from 2017 to 2020. The PB1 gene was closely related to the H5N6 avian influenza virus in Guangxi Zhuang Autonomous Region and Fujian Province from 2016 to 2022 and was not related to the PB1 gene of the H5N6 avian influenza epidemic strain in Guangzhou. The other internal gene fragments had complex sources with significant genetic diversity. Molecular characteristics indicated that the strain exhibited the molecular characteristics of a typical low pathogenic avian influenza virus and tended to bind to the receptors of avian origin. On important protein sites related to biological characteristics, this strain had mutations of PB2-L89V, PB1-L473V, NP-A184K, M1-N30D/T215A, and NS1-P42S/N205S.Conclusions:This study identified a novel reassortant H3N2 avian influenza virus by nanopore sequencing, with the PB1 gene derived from the H5N6 avian influenza virus. The virus had a low ability to spread across species, but further exploration was needed to determine whether its pathogenicity to the host was affected.

OBJECTIVE: Feature extraction of breast tumors is very important in the breast tumor detection (benign and malignant) in ultrasound image. The traditional quantitative description of breast tumors has some shortcomings, such as inaccuracy. A simple and accurate feature extraction method has been studied. METHODS: In this paper, a new method of boundary feature extraction was proposed. Firstly, the shape histogram of ultrasound breast tumors was constructed. Secondly, the relevant boundary feature factors were calculated from a local point of view, including sum of maximum curvature, sum of maximum curvature and peak, sum of maximum curvature and standard deviation. Based on the boundary features, shape features and texture features, the linear support vector machine classifiers for benign and malignant breast tumor recognition was constructed. RESULTS: The accuracy of boundary features in the benign and malignant breast tumors classification was 82.69%. The accuracy of shape features was 73.08%. The accuracy of texture features was 63.46%. The classification accuracy of the three fusion features was 86.54%. CONCLUSIONS The classification accuracy of boundary features was higher than that of texture features and shape features. The classification method based on multi-features has the highest accuracy and it describes the benign and malignant tumors from different angles. The research results have practical value.
Algorithms ; Breast Neoplasms ; diagnostic imaging ; Humans ; Support Vector Machine ; Ultrasonography

To establish the experts consensus on the management of delirium in critically ill patients.A special committee was set up by 15 experts from the Chinese Critical Hypothermia-Sedation Therapy Study Group.Each statement was assessed based on the GRADE (Grading of Recommendations Assessment,Development,and Evaluation) principle.Then the Delphi method was adopted by 36 experts to reassess all the statements.(1) Delirium is not only a mental change,but also a clinical syndrome with multiple pathophysiological changes.(2) Delirium is a form of disturbance of consciousness and a manifestation of abnormal brain function.(3) Pain is a common cause of delirium in critically ill patients.Analgesia can reduce the occurrence and development of delirium.(4) Anxiety or depression are important factors for delirium in critically ill patients.(5) The correlation between sedative and analgesic drugs and delirium is uncertain.(6) Pay attention to the relationship between delirium and withdrawal reactions.(7) Pay attention to the relationship between delirium and drug dependence/ withdrawal reactions.(8) Sleep disruption can induce delirium.(9) We should be vigilant against potential risk factors for persistent or recurrent delirium.(10) Critically illness related delirium can affect the diagnosis and treatment of primary diseases,and can also be alleviated with the improvement of primary diseases.(11) Acute change of consciousness and attention deficit are necessary for delirium diagnosis.(12) The combined assessment of confusion assessment method for the intensive care unit and intensive care delirium screening checklist can improve the sensitivity of delirium,especially subclinical delirium.(13) Early identification and intervention of subclinical delirium can reduce its risk of clinical delirium.(14) Daily assessment is helpful for early detection of delirium.(15) Hopoactive delirium and mixed delirium are common and should be emphasized.(16) Delirium may be accompanied by changes in electroencephalogram.Bedside electroencephalogram monitoring should be used in the ICU if conditions warrant.(17) Pay attention to differential diagnosis of delirium and dementia/depression.(18) Pay attention to the role of rapid delirium screening method in delirium management.(19) Assessment of the severity of delirium is an essential part of the diagnosis of delirium.(20) The key to the management of delirium is etiological treatment.(21) Improving environmental factors and making patient comfort can help reduce delirium.(22) Early exercise can reduce the incidence of delirium and shorten the duration of delirium.(23) Communication with patients should be emphasized and strengthened.Family members participation can help reduce the incidence of delirium and promote the recovery of delirium.(24) Pay attention to the role of sleep management in the prevention and treatment of delirium.(25) Dexmedetomidine can shorten the duration of hyperactive delirium or prevent delirium.(26) When using antipsychotics to treat delirium,we should be alert to its effect on the heart rhythm.(27) Delirium management should pay attention to brain functional exercise.(28) Compared with non-critically illness related delirium,the relief of critically illness related delirium will not accomplished at one stroke.(29) Multiple management strategies such as ABCDEF,eCASH and ESCAPE are helpful to prevent and treat delirium and improve the prognosis of critically ill patients.(30) Shortening the duration of delirium can reduce the occurrence of long-term cognitive impairment.(31) Multidisciplinary cooperation and continuous quality improvement can improve delirium management.Consensus can promote delirium management in critically ill patients,optimize analgesia and sedation therapy,and even affect prognosis.