Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P＜0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P＜0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P＜0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

Background::Cardiovascular disease (CVD) has emerged as the leading cause of death from prostate cancer (PCa) in recent decades, bringing a great disease burden worldwide. Men with preexisting CVD have an increased risk for major adverse cardiovascular events when treated with androgen deprivation therapy (ADT). The present study aimed to explore the prevalence and risk evaluation of CVD among people with newly diagnosed PCa in China.Methods::Clinical data of newly diagnosed PCa patients were retrospectively collected from 34 centers in China from 2010 to 2022 through convenience sampling. CVD was defined as myocardial infarction, arrhythmia, heart failure, stroke, ischemic heart disease, and others. CVD risk was estimated by calculating Framingham risk scores (FRS). Patients were accordingly divided into low-, medium-, and high-risk groups. χ2 or Fisher’s exact test was used for comparison of categorical variables. Results::A total of 4253 patients were enrolled in the present study. A total of 27.0% (1147/4253) of patients had comorbid PCa and CVD, and 7.2% (307/4253) had two or more CVDs. The enrolled population was distributed in six regions of China, and approximately 71.0% (3019/4253) of patients lived in urban areas. With imaging and pathological evaluation, most PCa patients were diagnosed at an advanced stage, with 20.5% (871/4253) locally progressing and 20.5% (871/4253) showing metastasis. Most of them initiated prostatectomy (46.6%, 1983/4253) or regimens involving ADT therapy (45.7%, 1944/4253) for prostate cancer. In the present PCa cohort, 43.1% (1832/4253) of patients had hypertension, and half of them had poorly controlled blood pressure. With FRS stratification, as expected, a higher risk of CVD was related to aging and metabolic disturbance. However, we also found that patients with treatment involving ADT presented an originally higher risk of CVD than those without ADT. This was in accordance with clinical practice, i.e., aged patients or patients at advanced oncological stages were inclined to accept systematic integrative therapy instead of surgery. Among patients who underwent medical castration, only 4.0% (45/1118) received gonadotropin releasing hormone antagonists, in stark contrast to the grim situation of CVD prevalence and risk.Conclusions::PCa patients in China are diagnosed at an advanced stage. A heavy CVD burden was present at the initiation of treatment. Patients who accepted ADT-related therapy showed an original higher risk of CVD, but the awareness of cardiovascular protection was far from sufficient.

Objective To explore the postmortem diffusion rule of Aconitum alkaloids and their metabo-lites in poisoned rabbits,and to provide a reference for identifying the antemortem poisoning or post-mortem poisoning of Aconitum alkaloids.Methods Twenty-four rabbits were sacrificed by tracheal clamps.After 1 hour,the rabbits were administered with aconitine LD50 in decocting aconite root powder by intragastric administration.Then,they were placed supine and stored at 25℃.The biological samples from 3 randomly selected rabbits were collected including heart blood,peripheral blood,urine,heart,liver,spleen,lung and kidney tissues at 0 h,4 h,8 h,12 h,24 h,48 h,72 h and 96 h after intragastric administration,respectively.Aconitum alkaloids and their metabolites in the biological samples were ana-lyzed by high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS).Results At 4 h after intragastric administration,Aconitum alkaloids and their metabolites could be detected in heart blood,peripheral blood and major organs,and the contents of them changed dynamically with the preservation time.The contents of Aconitum alkaloids and their metabolites were higher in the spleen,liver and lung,especially in the spleen which was closer to the stomach.The average mass fraction of benzoylmesaconine metabolized in rabbit spleen was the highest at 48 h after intragastric administration.In contrast,the contents of Aconitum alkaloids and their metabolites in kidney were all lower.Aconi-tum alkaloids and their metabolites were not detected in urine.Conclusion Aconitum alkaloids and their metabolites have postmortem diffusion in poisoned rabbits,diffusing from high-content organs(stomach)to other major organs and tissues as well as the heart blood.The main mechanism is the dispersion along the concentration gradient,while urine is not affected by postmortem diffusion,which can be used as the basis for the identification of antemortem and postmortem Aconitum alkaloids poisoning.

Objective:To explore the repairing effect and mechanism of tangeretin in rats with spinal cord injury.Methods:The rats were divided into sham-operation group, model group and tangeretin group according to random number table, with 8 rats in each group. Except for the sham-operation group, Allen hit method was used to make rat models in the other groups. After the model was successfully established, the tangeretin group was intragastrically administered with tangeretin 50 mg/kg, and the sham-operation group and the model group were intragastrically administered with an equal volume of normal saline once a day for 14 days. On days 0, 3, 7, and 14 after modeling, the motor function recovery of rats was assessed using the Basso-Beattie-Bresnahan (BBB) score; the morphological changes of the spinal cord tissues were observed using HE staining and Nissl staining; the SOD and GSH activities and MDA, IL-1β, TNF-α, and IL-10 levels in the spinal cord tissues of rats in each group were measured using ELISA kit detection; the GFAP and Neun expressions in the spinal cord tissues were detected by immunofluorescence; the IL-1β, TNF-α, IL-10, nuclear factor E2-related factor 2 (Nrf-2), and NAD (P) H-quinone oxidoreductase 1 (NQO-1) expressions in the spinal cord tissues were detected by Western blot.Results:Compared with the model group, the BBB score increased in the tangeretin group ( P<0.05), HE staining score decreased ( P<0.05), and the number of Nissl bodies increased ( P<0.05); the level of IL-10, SOD and GSH activities increased ( P<0.05), and IL-1β, TNF-α and MDA levels decreased in the spinal cord tissue ( P<0.05); GFAP fluorescence intensity decreased ( P<0.05) and NeuN fluorescence intensity increased ( P<0.05); the relative expression of IL-1β and TNF-α decreased ( P<0.05), and the relative expressions of IL-10, Nrf-2 and NQO-1 protein increased ( P<0.05). Conclusions:Tangeretin can exert anti-inflammatory and anti-oxidative stress effects through the Nrf2/NQO1 signaling pathway and alleviate early spinal cord injury in rats. On the other hand, it may promote the recovery of spinal cord injury by reducing glial scar generation and promoting neural cellogenesis.

Objective To investigate the clinical efficacy of Guiyuan Shujin Mixture in the treatment of patients with lumbar disc herniation(LDH)and to explore its possible therapeutic mechanism.Methods Sixty-eight patients with LDH of qi stagnation and blood stasis syndrome were randomly divided into trial group and control group,with 34 cases in each group.The control group was treated with Celecoxib Tablets and Mecobalamin Tablets orally,and the trial group was treated with Guiyuan Shujin Mixture on the basis of treatment for the control group.The course of treatment lasted for 4 weeks.Before and after treatment,the two groups were observed in the changes of the Visual Analogue Scale(VAS)score of low back pain and lower limb pain,Oswestry Disability Index(ODI)score,modified Japanese Orthopedic Association(JOA)score,serum levels of inflammatory factors of tumor necrosis factor α(TNF-α),interleukin 6(IL-6)and interleukin 1β(IL-1β),and serum nuclear factor-κB p65(NF-κB p65)level.After treatment,the clinical efficacy and safety of the two groups were evaluated.Results(1)During the trial,one case fell off in the trial group and 3 cases fell off in the control group.Eventually,33 cases in the trial group and 31 cases in the control group were included for the efficacy statistics.(2)After 4 weeks of treatment,the total effective rate of the trial group was 96.97%(32/33),and that of the control group was 87.10%(27/31).The intergroup comparison(tested by rank sum test)showed that the curative effect of the trial group was significantly superior to that of the control group(P＜0.05).(3)After treatment,the VAS score and ODI score of low back pain and lower limb pain in the two groups were lower than those before treatment(P＜0.05 or P＜0.01),and the modified JOA score was higher than that before treatment(P＜0.01).The decrease of VAS score and ODI score of low back pain and lower limb pain and the increase of modified JOA score in the trial group were significantly superior to those in the control group(P＜0.05 or P＜0.01).(4)After treatment,the serum levels of inflammation-related indicators of TNF-α,IL-6,IL-1β and NF-κB p65 in the two groups were lower than those before treatment(P＜0.01),and the decrease in the trial group was significantly superior to that in the control group(P＜0.01).(5)During the treatment,the incidence of adverse events in the trial group was 2.94%(1/34)and that in the control group was 8.82%(3/34),and the difference between the two groups was not significant(P＞0.05).Conclusion Guiyuan Shujin Mixture exerts certain effect in the treatment of LDH patients with qi stagnation and blood stasis syndrome.It can effectively relieve the pain symptoms of patients,improve the lumbar function of patients,and reduce the expression levels of serum inflammatory factors and NF-κB p65.The mechanism may be related with the decrease of the level of inflammatory factors and with the inhibition of the activation of NF-κB signaling pathway.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.