Objective:To investigate the molecular markers involved in death related to acute myocardial infarction (AMI) and provide new targets for early intervention.Methods:Consecutive patients who hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from January 2017 to December 2021 and diagnosed with AMI were enrolled. The clinical factors and markers associated with in-hospital death after AMI were analyzed. In addition, patients diagnosed with AMI hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from September 2022 to April 2023 were enrolled. We prospectively analyzed the plasma protein of death related to AMI via Olink Precision Proteomics based on proximity extension assay (PEA) technology.Results:In the retrospective study, 2 325 patients with AMI were analyzed, including 75 patients in the in-hospital death group and 2 250 subjects in the survival group. The overall mortality rate during hospitalization was 3.23% (75/2325). The patients in the death group were older: 72 (64, 80) years vs. 63 (55, 71) years. And Interleukin-6 (IL-6), hypersensitive C-reactive protein (Hs-CRP), leukocyte counts and neutrophil counts were markedly higher in the death group than those in the survival group: 69.0 (26.7, 136.6) ng/L vs. 18.2 (9.4, 36.5) ng/L, 45.7 (28.7, 50.5) mg/L vs. 5.5 (2.0, 17.2) mg/L, 12.0 (9.8, 14.1) ×10 9/L vs. 8.9 (7.2, 11.2) × 10 9/L, 9.8 (7.8, 12.1) ×10 9/L vs. 6.5(4.7, 8.8) ×10 9/L ( P<0.01). In this prospective study, 86 patients with AMI were analyzed. 61 proteins including Insulin-like growth factor-binding protein 1, 2 (IGFBP-1, IGFBP-2), Chitotriosidase-1 (CHIT1), Complement component C1q receptor (CD93) were independently associated with in-hospital death related to AMI ( P<0.05). The differential proteins were mainly enriched in inflammatory response, cell adhesion, cytokine signaling pathway and apoptosis. Moreover, 22 proteins including Urokinase plasminogen activator surface receptor (U-PAR), Trefoil factor 3 (TFF3), Perlecan (PLC), Growth differentiation factor 15 (GDF-15), Junctional adhesion molecule A (JAM-A) were plotted according to a logistic regression model, and the area under the curve (AUC) was more than 0.9, showing the high accuracy in predicting in-hospital death after AMI. Conclusions:Molecular markers of the inflammatory response, cell adhesion, cell growth and apoptosis might be involved in death related to AMI, which provides new targets for early intervention.

Endometriosis (EMS) is a chronic systemic disease prevalent in women of reproductive age. The signs and symptoms of this disease are not specific, and the severity of the disease varies, leading to clinical heterogeneity, which increases the difficulty of diagnosis. It seriously affects the quality of life of patients and also occupies a large amount of social health resources. Artificial intelligence (AI) refers to the ability of a computer technology to enable machines to simulate human intelligence, including perception, learning, reasoning, decision making and language understanding. AI serves as a powerful data-mining tool capable of processing large amounts of medical data and diagnosing, managing, and treating patients according to their specific conditions. Especially in the diagnostic process of EMS, the use of AI can improve the detection rate and shorten the diagnostic time while increasing the diagnostic sensitivity and specificity. In this paper, we provide an overview of the application of medical big data and AI to the diagnosis and treatment of EMS in order to provide new aids to further improve diagnostic efficiency and therapeutic efficacy.

Objective To assess the effectiveness of the evaluation of military physical function(EMPF)system in predicting the occurrence of military training injuries among new recruits to provide scientific guidance and methodological choice for military training.Methods A total of 527 new recruits from 5 grassroots units from July 2016 to February 2018 were selected for the study.The recruits underwent EMPF testing,and their military training injuries were monitored over a 2-year follow-up period.Those who sustained injuries during training were divided into injury group(n=163),while the remaining recruits were placed in healthy group(n=364).The predictive ability of the total EMPF score for training injuries was assessed using the receiver operating characteristic curve(ROC),and the correlation between the total EMPF score,individual test scores,and military training injuries were analyzed using binary logistic regression.Results The total EMPF score of new recruits in injury group(19.52±1.97)was significantly lower than that of healthy group(24.31±1.54)(P<0.001),which also demonstrated a high diagnostic value in predicting the risk of military training injuries,with an area under the curve(AUC)of ROC of 0.971(P<0.001).A cut-off value of 22 scores was found to have the highest accuracy in predicting future training injuries,with an odds ratio(OR)of 25.63,sensitivity of 0.939,specificity of 0.879,positive likelihood ratio of 7.76,and a post-test probability of 0.67.Binary logistic regression analysis revealed that 6 EMPF tests,including holding the ball over and leaning back,bending forward and touching the ground with the ball,lunge squat and twist,swallow balance with holding the ball afterward,vertical jump,and respiratory pattern assessment,were negatively associated with the risk of military training injuries(P<0.0001).Conclusion The EMPF system can effectively predict the risk of military training injuries,with military personnel whose total EMPF score is less than 22 being at higher risk of sustaining such injuries.

Objective To investigate the effects of a 100 mT static magnetic field(SMF)on emotional behavior and brain damage-related molecules in mice.Methods Fifty-eight C57BL/6N mice were randomly divided into control group(n=25)and observation group(n=33).Mice in observation group were exposed to a 100 mT SMF for 0.5 h/d over 14 consecutive days,while mice in control group underwent pseudo-exposure.On the 7 and 14 days of exposure,anxiety-like behavior was assessed using open field and elevated plus maze tests.Cerebral blood flow was monitored using laser speckle imaging,and the levels of tumor necrosis factor-α(TNF-α),interleukin(IL)-1β,IL-4,central nervous system specific protein β(S100β),neuron-specific enolase(NSE),and brain-derived neurotrophic factor(BDNF)were measured by radioimmunoassay.BDNF expression in the brain was detected by immunofluorescence.Results On the 7 and 14 days of SMF exposure,the open field and elevated plus maze tests showed no statistically significant differences between observation and control groups in the frequencies,durations,and distance entering the central area of the open field and the open arm of the elevated plus maze(P>0.05).Laser speckle imaging revealed no significant difference in cerebral cortical perfusion compared with pre-exposure period(P>0.05).The results of radioimmunoassay showed that compared with control group,on the 7 d of SMF exposure,the serum IL-1β,NSE and S100β levels were significantly increased(P<0.05),the serum BDNF level was significantly decreased(P<0.05),and the IL-1β and TNF-α contents in brain tissues were significantly increased in observation group(P<0.01).On the 14 d of SMF exposure,serum IL-1β,TNF-α,NSE,and S100β levels were significantly increased(P<0.05,P<0.0001),and the brain IL-1β and TNF-α levels were significantly increased(P<0.01)in observation group.No statistically significant differences were found in anti-inflammatory cytokine IL-4 level of serum and brain tissue or BDNF content of brain tissue between the two groups(P>0.05).Conclusion Continuous exposure to a 100 mT SMF for 14 d at 0.5 h/d induces neuroinflammation and brain damage in mice,without inducing anxiety-like behavior.

Objective To investigate the antitumor effects of triptolide against CT26 colon cancer and its impact on the expression of Polo-like kinase-1(PLK-1)protein.Methods Forty clean grade BALB/c mice,each mouse was implanted with 1×106 CT26 cells into the dorsal side of the right forelimb to establish a tumor-bearing mouse model.Experimental animals were randomly divided into four groups,the tumor model group(saline control),the positive drug group[oxaliplatin,5 mg/(kg·d)],the low-dose triptolide group[50 μg/(kg·/d)],and the high-dose triptolide group[100 μg/(kg·d)].The drugs were administered through intraperitoneal injection(10 times in total,once every other day).The in vitro effects of the drugs on the proliferation,migration,invasion,and mitosis of CT26 cells were also assessed.Results Triptolide significantly inhibited the proliferation,migration,and invasion of CT26 colon cancer cells,and disrupted the separation of centrosomes and the correct arrangement of chromosomes during the prophase of mitosis in tumor cells.The binding energy of triptolide and PLK-1 protein was-7.1 kcal/mol,and it could down-regulate the expression of PLK-1 in CT26 cells.Conclusion Triptolide exerts its antitumor effects against CT26 colon cancer by downregulating the expression of PLK-1.

Objective To explore the molecular mechanism by which SOS Ras/Rac guanine nucleotide exchange factor 1-intronic transcript 1(SOS1-IT1)affects enhancer of zeste homolog 2(EZH2)protein expression in endometrial cancer cells Ishikawa and RL95-2.Methods Lentiviral transfection of short hairpin RNA(shRNA)and overexpression plasmid were used in Ishikawa and RL95-2 cell lines to knock down and overexpress SOS1-IT1.The mechanism of EZH2 expression regulation was studied using Real-time PCR,Western blotting,and chromatin immunoprecipitation.Results The expression of SOS1-IT1 and EZH2 genes was positively correlated in endometrial cancer tissues.Knocking down SOS1-IT1 significantly reduces the expression of EZH2,inhibited the proliferation and migration of Ishikawa and RL95-2 cells,and could reduced the acetylation of histone H3 at position 27(H3K27)and the enrichment of CREB binding protein(CBP)in the EZH2 gene promoter region.Overexpression of SOS1-IT1 could increased the expression of EZH2 and enhance the acetylation of H3K27 and the enrichment of CBP.CBP could bind to SOS1-IT1 RNA,and this binding ability was weakened when CBP was knocked down.Conclusion SOS1-IT1 can promote the expression level of EZH2 in endometrial cancer cells Ishikawa and RL95-2 by regulating the acetylation modification level of the EZH2 gene promoter region,thereby affecting the proliferation and migration ability of endometrial cancer cells.

A 53-year-old female patient with type 2 diabetes mellitus,hypertension,and hyperlipidemia,on long-term therapy with metformin,gliclazide,dapagliflozin,sacubitril/valsartan,lercanidipine,and atorvastatin,was initiated on semaglutide due to obesity and suboptimal glycemic control.Patient using semaglutide 0.25 mg and 0.5 mg without adverse effects,and developed gastric discomfort after adjusting dose to 0.75 mg.She remained on this dose for 7 weeks.Upon further dose escalation to 1 mg,she experienced persistent nausea,vomiting,and diarrhea.Fifteen days later,she was admitted to the hospital with impaired consciousness.Laboratory findings revealed blood urea nitrogen of 35.4 mmol·L-1 and serum creatinine of 825 μmol·L-1.The patient was diagnosed with acute kidney injury(AKI),which was considered related to semaglutide,metformin,dapagliflozin,and sacubitril/valsartan.All medications were discontinued.Following symptomatic treatment including fluid resuscitation,volume expansion,and hemodialysis,the patient's renal function gradually recovered.The association between AKI and semaglutide,metformin,dapagliflozin,and sacubitril/valsartan was evaluated using the Naranjo's Assesment Scale,the results were all"probable".This case highlighted that clinical use of semaglutide requires careful consideration of concomitant medications and vigilance for renal impairment.In the event of AKI,prompt assessment,discontinuation of medications with potential renal impairment and symptomatic management were necessary to ensure safe medication administration.

Endometriosis (EMS) is a chronic systemic disease prevalent in women of reproductive age. The signs and symptoms of this disease are not specific, and the severity of the disease varies, leading to clinical heterogeneity, which increases the difficulty of diagnosis. It seriously affects the quality of life of patients and also occupies a large amount of social health resources. Artificial intelligence (AI) refers to the ability of a computer technology to enable machines to simulate human intelligence, including perception, learning, reasoning, decision making and language understanding. AI serves as a powerful data-mining tool capable of processing large amounts of medical data and diagnosing, managing, and treating patients according to their specific conditions. Especially in the diagnostic process of EMS, the use of AI can improve the detection rate and shorten the diagnostic time while increasing the diagnostic sensitivity and specificity. In this paper, we provide an overview of the application of medical big data and AI to the diagnosis and treatment of EMS in order to provide new aids to further improve diagnostic efficiency and therapeutic efficacy.

A 53-year-old female patient with type 2 diabetes mellitus,hypertension,and hyperlipidemia,on long-term therapy with metformin,gliclazide,dapagliflozin,sacubitril/valsartan,lercanidipine,and atorvastatin,was initiated on semaglutide due to obesity and suboptimal glycemic control.Patient using semaglutide 0.25 mg and 0.5 mg without adverse effects,and developed gastric discomfort after adjusting dose to 0.75 mg.She remained on this dose for 7 weeks.Upon further dose escalation to 1 mg,she experienced persistent nausea,vomiting,and diarrhea.Fifteen days later,she was admitted to the hospital with impaired consciousness.Laboratory findings revealed blood urea nitrogen of 35.4 mmol·L-1 and serum creatinine of 825 μmol·L-1.The patient was diagnosed with acute kidney injury(AKI),which was considered related to semaglutide,metformin,dapagliflozin,and sacubitril/valsartan.All medications were discontinued.Following symptomatic treatment including fluid resuscitation,volume expansion,and hemodialysis,the patient's renal function gradually recovered.The association between AKI and semaglutide,metformin,dapagliflozin,and sacubitril/valsartan was evaluated using the Naranjo's Assesment Scale,the results were all"probable".This case highlighted that clinical use of semaglutide requires careful consideration of concomitant medications and vigilance for renal impairment.In the event of AKI,prompt assessment,discontinuation of medications with potential renal impairment and symptomatic management were necessary to ensure safe medication administration.