Objective:To investigate the clinical phenotype and gene mutation in a child with developmental disorders caused by CTNNB1 gene mutation. Methods:Clinical data of a child with CTNNB1 gene mutation who was admitted to Xiamen Hospital of Fudan University Affiliated Pediatric Hospital in May 2017 were collected, whole exome sequencing technology was applied to verify the family lineage of the child, and the pathogenicity of mutation site was analyzed. Results:The patient was a 6 years and 1 month old male, with a clinical phenotype including mental retardation, motor developmental disorders, speech disorders, visual disorders (internal strabismus), microcephaly, and behavioral problems (social withdrawal, overdependence, etc.), as well as panic syndrome (i.e., sudden shrieking in response to auditory and visual stimuli, extensional rigidity of the body, etc., followed by short periods of general extensional rigidity). The whole exome sequencing results showed the presence of a de novo mutation c.283(exon4)C>T in the CTNNB1 gene, and the c.283(exon4)C>T mutation was interpreted as pathogenic (PVS1+PS2+PS1+PM2+PM) according to the American College of Medical Genetics and Genomics variant classification criteria and guidelines. No relevant genetic variants were found in the parental family verification. Conclusion:CTNNB1 gene mutation c.283(exon4)C>T can cause neurodevelopmental disorders, including mental retardation, motor developmental disorders, speech disorders, visual disorders, microcephaly and behavioral abnormalities.

Thioredoxin-interacting protein (TXNIP), which mainly regulates glucose homeostasis in pancreatic β cells, is a novel target in the treatment of diabetes.In this study, 4-hydroxybenzopyrimidine was used as the raw material, four nitrogen-containing rings (imidazole, methylpiperazine, pyrazole, morpholine) were introduced, benzopyrimidine skeleton with nitrogen-containing rings derivatives targeting TXNIP was designed and synthesized, and the protective effect of compounds on palmitic acid-stimulated islet β cells was investigated.A total of 20 benzopyrimidine derivatives were designed and synthesized, and the structures were confirmed by 1H NMR and ESI-MS.Pharmacological studies showed that most of the compounds exhibited protective effects on islet β cells, with better axtivity for compounds C-1, C-2, C-4 and D-2 (cell survival rate > 70%) compared with PA model group (38.3%), Among the four compounds, D-2 had the highest activity of 87.2%, so it could become a potential new anti-diabetic chemical entity.

The fingerprint of Boenninghausenia albiflora var. albiflora was established by ultra performance liquid chromatography(UPLC), and the content of 12 active components including chlorogenic acid was determined. Multivariate statistical analysis was used to explore the indicator components of B. albiflora var. albiflora and a comprehensive evaluation system was created for the quality of B. albiflora var. albiflora. In this study, 33 batches of B. albiflora var. albiflora with different sources were collected and studied, and the UPLC fingerprint of B. albiflora var. albiflora was developed. There were 37 common peaks, of which 12 components were identified, and the content of these 12 components was measured. In combination of the common peaks and the content of chemical components, multivariate statistical analysis was performed, and the results showed that 6 components [daphnoretin, isoimperatorin, astragalin, imperatorin, neochlorogenic acid, and isoquercitrin(weight coefficient>0.1)] were selected as chemical markers for the quality of B. albiflora var. albiflora. Technique for order of preference by similarity to ideal solution(TOPSIS) analysis and chemometrics revealed that the quality of S32, S28 and S29 were superior, while that of S12, S7 and S16 were inferior. The quality evaluation method of B. albiflora var. albiflora constructed in this study was accurate and reliable, with simpleness and easiness to operate. It is suggested that the 6 above-mentioned active components could be used as indicator components for quality control of B. albiflora var. al-biflora. The samples were harvested during the flowering and fruiting period, which is from the beginning of July to the end of August.
Chromatography, High Pressure Liquid/methods* ; Chromatography, Liquid ; Drugs, Chinese Herbal/chemistry* ; Multivariate Analysis ; Quality Control

With the enhancement of computing power and the continuous development of machine learning and deep learning algorithms, artificial intelligence (AI) has gradually become an important tool for human activities and has also given new vitality to the fields of life science and medicine. For laboratory medicine, it is both an opportunity and a challenge. The combination of inspection big data and AI algorithms has promoted the improvement of morphological inspection capabilities, the optimization of inspection processes, the discovery of new knowledge, and the development of disease diagnosis models. It has become a convenient and intelligent assistant for disease prevention, diagnosis and prognosis prediction.

Ferulic acid (FA), a natural product of phenylpropanoids containing phenolic hydroxyl groups, has a wide range of pharmacological activities and some therapeutic effect on Alzheimer's disease (AD).Using FA as the raw material, the ferulic acid carbamate aniline derivatives were first synthesized by 4-step esterification reaction, splicing carbamate active functional groups, hydrolysis reaction and amide condensation.These FA derivatives were evaluated for in vitro cholinesterase inhibition activity by the Ellman method.A total of 15 novel FA derivatives were designed and synthesized, and their structures were confirmed by 1H NMR, 13C NMR and ESI-MS.Cholinesterase activity tests showed that compounds 5c, 5f, 5j, 5g, 5m possessed good acetylcholinesterase inhibition activity.Except for 5l, 5m, almost all compounds have inhibition activity on butyrylcholinesterase, which is much higher than that on acetylcholinesterase.In conclusion, compounds 5c, 5f, 5j and 5g can be used as potential anti-AD inhibitors targeting cholinesterase..

Fever is a sign of infection and inflammatory diseases in the body. Persistent high fever will lead to cell degeneration, causing multiple organ dysfunction, and seriously affecting brain nerve and tissue function. Although the fever process is common and ordinary, its pathological mechanism involves multiple signaling pathways, such as nuclear transcription factor κB signaling pathway, Toll-like receptor 4 signaling pathway. A large number of studies have shown that traditional Chinese medicine compound and its active components can reduce serum inflammatory factors (TNF-α, IL-1β and IL-6) and hypothalamic thermoregulatory mediators (PGE

Using syringaldehyde as raw material, the phosphine ylide intermediate was efficiently synthesized through acetylated hydroxyl protection, aldehyde group reduction, chlorination and reaction with triphenylphosphine. On this basis, moscatilin (MST) and its 12 analogs (MST-1-MST-12) were synthesized by wittig reaction, deacetylation and double bond reduction. All the structures were confirmed by 1H NMR, 13C NMR and ESI-MS. Bacterial lipopolysaccharide-induced mouse macrophage RAW264.7 inflammation model was used to conduct preliminary anti-inflammatory activity tests in vitro for the target compounds. Results showed that all compounds could inhibit the production of inflammatory factor NO, and that MST-5 exhibited the strongest anti-inflammatory activity (IC50= 0.428 μmol/L).Further exploration is expected for the study of the anti-inflammatory mechanism of MST-5.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultation and improves the accuracy of congenital heart disease diagnosis. At the present stage, the AI based cardiac auscultation technique mainly focuses on the research of AI algorithms, and the researchers have designed and summarized a variety of effective algorithms based on the characteristics of cardiac audio data, among which the mel-frequency cepstral coefficients (MFCC) is the most effective one, and widely used in the cardiac auscultation. However, the current cardiac sound analysis techniques are based on specific data sets, and have not been validated in clinic, so the performance of algorithms need to be further verified. The lack of heart sound data, especially the high-quality, standardized, publicly available heart sound database with disease labeling, further restricts the development of heart sound diagnostic analysis and its application in screening. Therefore, expert consensus is necessary in establishing an authoritative heart sound database and standardizing the heart sound auscultation screening process for congenital heart disease. This paper provides an overview of the research and application status of auscultation algorithm and hardware equipment based on AI in auscultation screening of congenital heart disease, and puts forward the problems to be solved in clinical application of AI auscultation screening technology.
Algorithms ; Artificial Intelligence ; Heart Auscultation/trends* ; Heart Defects, Congenital/diagnosis* ; Humans ; Mass Screening/methods*

Objective:To investigate the diagnosis and treatment of abdominal cocoon (AC).Methods:The clinical manifestations, findings during surgery, treatments, and follow-up results of 26 cases of AC were retrospectively studied from Jan 2001 to Jan 2019.Results:All of 26 cases were diagnosed as AC definitely by laparotomy, and were categorized into 2 types: type Ⅰ is of absence of second enterocoelia (18 cases, 69%) while type Ⅱ shows second enterocoelia (8cases, 31%). Twenty cases (12 type Ⅰ, 8 type Ⅱ) underwent membrane excision and careful enterodialysis to release the small intestine entirely or partially, while the other 6 cases (all were type Ⅰ) did not. All the patients recovered smoothly.Conclusions:AC can be categorized into two types, Surgery is recommended for type Ⅱ and part of type Ⅰ with severe complications.