[Objective] To analyze the serological characteristics and molecular biology results for a P^k phenotype. [Methods] One patient with P^k phenotype upon unexpected antibodies at Jining Blood Center in July 2022 was selected as the study subject. The blood groups and unexpected antibodies of the proband and his second son were identified using serological methods. The sequences of 3-β-N-acetylgalactosaminyltransferase gene (B3GALNT1) and the coding region of α-1,4-galactosyltransferase gene (A4GALT) were amplified and analyzed by PCR direct sequencing, and haploid sequence analysis was carried out on the variant sites of the B3GALNT1 gene. PROVEAN, SIFT, PolyPhen2 and Mutation Taster were used to analyze the effect of mutations on the protein. [Results] Serological test results suggested that the proband was a P2^k type, including anti-P antibody in his serum, and his son was the P2 phenotype. Sequencing analysis revealed that the proband had a compound heterozygous variants of the B3GALNT1 in c. 239T>A (p. Leu80Gln) and c. 433C>T (p. Arg145Ter). Further haploid analysis showed that the c. 239T>A had occurred in one haploid while c. 433C>T was present in the other haploid, and his son carried a heterozygous variant of c. 433C>T (p. Arg145Ter); the proband and his son all have homozygous mutation variants of the A4GALT in c. 903C>G. Bioinformatic analysis also predicted that the mutations were harmful to the protein function. [Conclusion] The compound heterozygous variants c. 239T>A (p. Leu80Gln) and c. 433C>T (p. Arg145Ter) in the B3GALNT1 gene may contribute to the P^k phenotype, of which the c. 239T>A variant has not been reported.

OBJECTIVES: To propose a hypothesis that aloe-emodin may inhibit scar tissue fibrosis through thrombospondin-1(THBS1)-PI3K-Akt pathway. METHODS: By cultivating fibroblasts derived from scar tissue after cleft palate surgery in humans, aloe emodin of different concentrations (10, 20, 30, 40 and 50 μmol/L) was added to the cells which activity was detected. At the same time, transcriptome sequencing was performed on scar tissue and cells, and bioinformatics methods were used to explore potential targets and signaling pathways of scar tissue fibrosis. RESULTS: Aloe-emodin had a concentration dependent inhibitory effect on fibroblast proliferation,with the 40 μmol/L concentration group showing the most significant effect. The results of tissue and cell sequencing indicated that differentially expressed genes were significantly enriched in extracellular matrix-receptor interaction pathway, and shared a common differential gene which was THBS1. The ORA analysis results indicated that differentially expressed genes, including THBS1, were significantly enriched in the PI3K-Akt signaling pathway. CONCLUSIONS Aloe emodin may inhibit the PI3K-Akt pathway by downregulating THBS1, thereby reducing the proliferation activity of fibroblasts derived from postoperative palatal scar tissue.
Thrombospondin 1/genetics* ; Humans ; Signal Transduction/drug effects* ; Fibroblasts/cytology* ; Proto-Oncogene Proteins c-akt/metabolism* ; Fibrosis ; Phosphatidylinositol 3-Kinases/metabolism* ; Cicatrix/metabolism* ; Cell Proliferation/drug effects* ; Anthraquinones/pharmacology* ; Cells, Cultured

Objective To evaluate the forensic application value of used dental floss as a source of bio-logical evidence for individual identification by analyzing the effects of dental floss sample collection methods,DNA extraction methods,preservation conditions,and sampling sites on the success rate of STR typing.Methods Dental floss samples were collected using three techniques:direct cutting,cotton swab wiping,and flocked swab wiping,respectively.DNA was extracted respectively by the Chelex,spin column-based and magnetic bead-based methods.DNA quantification and STR typing were per-formed using the Qubit kit and FGI HumDNA Typing kit(Platinum),respectively.Storage environ-ments(temperature and humidity,ultraviolet radiation)and sampling locations(the floss part,the handle part)on DNA quantity and STR typing were evaluated.Results Through conducting a statisti-cal analysis of three key indicators of average DNA mass concentration,STR locus detection rate,and typing accuracy rate,the direct cutting method demonstrated the highest efficacy,followed by cotton swab wiping mothed,and the flocked swab wiping method had the lowest efficacy.Direct cutting yielded an average DNA mass concentration greater than(4.94±1.87)ng/μL,with STR locus detection and accuracy rates of 100%.Bead-based DNA extraction method produced superior DNA concentration and quality compared to spin column-based and Chelex methods,regardless of whether the sampling technique used.Preservation conditions had a significant impact on the DNA analysis of samples.Par-ticularly,the STR typing accuracy of samples preserved at 55℃/50%RH for 35 days dropped to(81.82±12.31)%,and that of samples exposed to ultraviolet radiation for 12 h dropped to(55.46±34.31)%.DNA concentration from the handle part of dental floss was extremely low,with an STR typing accuracy of only(30.91±27.35)%.Conclusion Using cotton swabs to wipe or directly cutting the thread of dental floss samples,and combining this approach with the magnetic bead method for DNA extraction,can best guarantee the concentration and quality of DNA.In addition,samples should be stored in low-temperature,low-humidity environment,protected from light and ultraviolet radiation.

Objective To analyzes the influence of Artificial Intelligence(AI)technology on physician workload based on the panel data of 31 provinces in China from 2012 to 2021.Methods Using MATLAB R2022b software to estimate the kernel density of physician workload and analyze the changes of physician workload in the past 10 years.Select fixed effects model and perform panel regression analysis between AI techniques and physician workload based on Stata MP 17.0 software.Results At present,there is a serious regional multi-level differentiation in physician workload.AI-assisted diagnosis,AI-assisted treatment and AI-assisted management have significantly reduced the physician workload.However,there is regional difference in the negative influence of AI technology on physician workload,with the most significant influence in eastern China and less significant in western China.Both aging and personal health investment negatively moderate the relationship between AI-assisted diagnosis technology and physician workload.Conclusion Great attention should be paid to AI,especially AI-assisted diagnosis technology,because it plays an important role in reducing the physician workload and alleviating the pressure caused by insufficient medical resources and uneven distribution in the context of aging.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.