Cytokeratin 8 ( CK8 ) belongs to the keratin family of intermediate filament cytoskeletal proteins. A lot of researches have demonstrated that abnormal expression or post-translational modifications of CK8 may affect its activity and consequently affect the development and progression of tumors. Therefore, investigating the role of CK8 in tumorigenesis may contribute to the prevention and treatment of tumors.

BACKGROUND:Early detection and accurate staging diagnosis of heart failure are the basis of good clinical therapy efficacy. Due to lack of simple and effective staging model for the diagnosis of heart failure, it is difficult to diagnose heart failure in clinics, leading to poor control of heart failure. OBJECTIVE:To establish the disease staging model based on Adaboost and SVM for heart failure, and improve the accuracy of diagnosis and staging of heart failure. METHODS:A total of 194 cases were roled into this study, including heart failure patients and healthy physical examination persons. According to the stage standards formulated by American Colege of Cardiology and American Heart Association, specific clinical feature parameters closely related to heart failure were colected and selected. Based on clinical diagnosis results and using Adaboost model and SVM model, we trained the models for heart failure diagnosis and staging, thus obtaining diagnosis model. RESULTS AND CONCLUSION: The parameters included stroke volume, cardiac output, left ventricular ejection fraction, left atrial diameter, left ventricular internal diameter at end-systole, N-terminal pro-brain natriuretic peptide and heart rate variability. As for the Adaboost model, its sensitivity and specificity was 100% and 94.4%, respectively. At the same time the SVM model had good sensitivity and specificity, 86.5% and 89.4% respectively. Adaboost classification model can be accurate in the diagnosis of heart failure symptoms, the accuracy reached 89.36%. On the basis of the diagnosis of heart failure, the SVM classification model is effective in staging the severity of heart failure, staging accuracy for staging B and C was 86.49% and 81.48%, respectively. The findings indicate that, combining Adaboost and SVM machine learning models could provide an accurate diagnosis and staging model for heart failure.

Objective:By analyzing the norm data results of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-Ⅳ) in China,to prove the validity of the procedure and methods during the norming development.Methods:The whole process of the revision of WAIS-Ⅳ,the development of computer-assisted system and norm sampling plan,were introduced in more detail,and the distribution of actual norm data of 1757 cases was analyzed.Results:For area distribution,compared with planned sampling number,the number from North and Northeast China was statistically significant different (x2 =78.02,P ＜0.01).For age stages distribution,most of cases conformed to the requirements of sampling,except that some cases including high-level educational cases aged 16-17 years and above 65 years,and low-level educational cases aged 30-34 years were less than the planned sampling number.For gender distribution,male subjects were more,but there was no statistically significant difference between male and female subjects (x2 =228,P =0.131).For educational degree distribution,the sampling conformed to the requirements of sampling plan (x2 =2.74,P =0.603).For occupation,resident years and registered permanent residence,and the sample was basically representative.Conclusion:The process of the revision of the Chinese version of WAIS-Ⅳ is appropriate,and actual norm sampling basically conforms to planned sample distribution,providing the sufficient representativeness and reliability for national norm data of WAIS-Ⅳ.

Adolescent ; Adult ; Endoscopy ; Ethmoid Sinus ; surgery ; Eyelids ; surgery ; Female ; Humans ; Male ; Middle Aged ; Orbital Fractures ; surgery ; Otorhinolaryngologic Surgical Procedures ; methods ; Young Adult

Objective To explore the relationship of intelligence among memory, sustained attention and executive function of schizophrenic patients. Methods 120 schizophrenic inpatients and 60 healthy subjects matched in age, gender and years of education with the patients were assessed with Wechsler Adult Intelligence Scale-fourth edition (WAIS-IV) and Wechsler Memory Scale-fourth edition (WMS-IV), Continuous Performance Test (CPT), Wisconsin Card Sorting Test (WCST). Results The intelligence quotient (IQ), memory quotient (MQ), scores of CPT and WCST were poor in the patients (P<0.05). IQ was correlated with MQ (r=0.837, P<0.01), the scores of CPT (r=0.613, P<0.01) and WCST (r=0.466, P<0.01). The scores of CPT and MQ were the independent factors related with IQ (P<0.001).Conclusion There is intelligence impairment in schizophrenics, which may related with the impairment of memory and sustained attention.

Objective To investigate the intellectual characteristics and related factors for patients with mental retardation. Methods 118 patients with mental retardation and 118 normal subjects were assessed with Wechsler Adult Intelligence Scale-fourth edition of Chinese (WAIS-Ⅳ). Results The full intelligence quotient (FIQ), index and scores of subtests were significantly lower in the patients than in the controls (P<0.01), especially for those of working memory and processing speed index. The difference in percentage of significance between verbal comprehension and working memory was higher (P<0.05). The FIQ and some index of patients positively correlated with age, education level and their parents' education level (P<0.01). Conclusion The patients with mental retardation present an overall decline in intelligence,especially in the working memory and processing speed. The mental development is unbalanced in some patients, that the verbal comprehension is relatively better than working memory. The intelligence of patients with mental retardation may be related with their age, education level and their parents' education level.

Objective To investigate the memory characteristics and related factors of patients with mental retardation. Methods 73 patients with mental retardation (patient group) and 73 normal subjects (control group) matched with the patient group were respectively tested with Wechsler Memory Scale-Fourth Edition of Chinese Version (WMS-IV). Results The scores of each subtest and composite scores of WMS-IV were significantly lower in the patient group than in the control group (P<0.01). All the composite scores positively correlated with each other in the patient group (r=0.38-0.90, P<0.01) and in the control group (r=0.31-0.94, P<0.01). Age and education level positively correlated with all the composite scores (except the Visual Working Memory Index) in the patient group (P<0.05). Conclusion The patients with mental retardation present an overall decline in memory, especially in the immediate memory. The memory function in patients is related with their ages and education levels.

Hepatic encephalopathy is a clinical syndrome of central nervous system dysfunction caused by liver insufficiency.It severely affects the quality of life of patients and may lead to death.Accurate prediction of the risk of developing hepatic encephalopathy is crucial for early intervention and treatment.In order to identify the risk of hepatic encephalopathy in patients in advance,many studies have been devoted to efforts to develop tools and methods to identify the risk of hepatic encephalopathy as early as possible,so as to develop preventive and early management strategies.Most conventional hepatic encephalopathy risk prediction models currently assess the prob-ability of a patient developing hepatic encephalopathy by analysing factors such as clinical data and biochemical indicators,however,their accuracy,sensitivity and positive predictive value are not high.The application of artificial intelligence to clinical predictive modelling is a very hot and promising area,which can use large amounts of data and complex algorithms to improve the accuracy and efficiency of diagnosis and prognosis.To date,there have been few studies using AI techniques to predict hepatic encephalopathy.Therefore,this paper reviews the research progress of hepatic encephalopathy risk prediction models,and also discusses the prospect of AI application in hepatic encephalopathy risk prediction models.It also points out the challenges and future research directions of AI in HE risk prediction model research in order to promote the development and clinical application of hepatic encephalopathy risk prediction models.

OBJECTIVE: To assess the value of chromosomal microarray analysis (CMA) to verify a fetus with partial 18p deletion signaled by non-invasive prenatal testing. METHODS: G-banding chromosomal karyotyping analysis was carried out on amniotic fluid sample of the fetus and peripheral blood samples from the parents. Amniotic DNA was also subjected to CMA analysis. The fetus was also subjected to systematic ultrasound scan. RESULTS: The fetus was found to have a karyotype of 46,XX,18p+. CMA has revealed a 5 Mb deletion at 18p11.32-p11.31, a 2.9 Mb duplication at 18p11.31-p11.23, and a 2.5 Mb duplication at 18p11.23-p11.22. No chromosomal aberration or microdeletion/microduplication was detected in either parent. CONCLUSION Non-invasive prenatal testing and CMA are both sensitive for the detection of chromosomal microdeletions and microduplications. CMA can help with clarification of genotype-phenotype correlation and facilitate prenatal diagnosis and genetic counseling for the family.
Chromosome Deletion ; Chromosomes ; Female ; Fetus ; Humans ; Karyotyping ; Pregnancy ; Prenatal Diagnosis

Abiraterone is commonly used as a targeted drug for the treatment of prostate cancer， which commonly causes adverse drug reactions （ADR）， including abnormal liver function， fatigue， nausea and edema， etc. This study reports a 78-year-old man with a history of hepatitis B and liver cirrhosis after prostate cancer resection who was admitted to the First Affiliated Hospital of Henan University of Chinese Medicine. The patient received abiraterone treatment 1 month before admission and developed gastrointestinal symptoms 3 weeks after the treatment and worsened at 4th week with yellowing of the skin， sclera and urine. Unfortunately， the patient died after 5 weeks of abiraterone treatment （1 week after admission）. Based on test and examination results， the patient was diagnosed with acute-on-chronic liver failure （ACLF）. This paper analyzes the patient’s medical history and the relevant treatment in detail. It is evaluated that ACLF and abiraterone are “probably” related based on Naranjo ADR Probability Scale， suggesting abiraterone may induce severe ADR of liver failure in patients with chronic liver diseases such as cirrhosis. These patients should be monitored dynamically for changes in liver function and treated prophylactically with liver-protective drugs if necessary.