ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

OBJECTIVE: To analyze the gene mutation characteristics and survival time of patients with newly diagnosed acute myeloid leukemia (AML) based on next-generation sequencing(NGS) gene detection. METHODS: A retrospective analysis was conducted on the clinical data of 92 patients with AML (non APL) admitted to our hospital from January 2018 to May 2022. AML related genes tested were using NGS, the mutation characteristics and survival time of AML patients were analyzed. RESULTS: Among the 92 patients, 41 were males and 51 were females. A total of 38 types of gene mutations were detected. Six-two patients carried at least one gere mutation, while no gene mutations were detected in 30 patients. In the group with favourable prognosis (n =14), the frequencies of higher gene mutations were NRAS, KIT (21.43%, n =3), KRAS (14.29%, n =2). In the group with intermediate prognosis (n =64), the gene mutation frequencies from high to low were DNMT3A (18.75%, n =12), NPM1 (17.19%, n =11), IDH2, FLT3-ITD, CEBPA (12.50%, n =8), TET2 (10.94%, n =7). In the poor prognosis group (n =14), ASXL1, TP53, EZH2, NRAS had higher gene mutation frequency than others(14.29 %, n =2 ). Statistical analysis revealed that KIT had a relative hotspot of mutations in the intermediate-risk group, and DNMT3A had a relative hotspot of mutations in the high-risk group (P < 0.05). The correlation analysis of genes with high mutation rates in different prognostic groups, such as NRAS, KIT, IDH2, DNMT3A, NPM1, and FLT3-ITD, with prognosis found that KIT was a factor affecting OS (P < 0.05), while no significant differences were observed for the others(P >0.05). CONCLUSION The frequency of gene mutations is high in AML patients, 67.4% of the patients carried at least one gene mutation. The mutation frequency varies among different genes in patients with different karyotypes, and there are obvious dominant mutations. KIT and DNMT3A can be used as factors for evaluating the prognosis of AML.
Humans ; Leukemia, Myeloid, Acute/genetics* ; Nucleophosmin ; Mutation ; Prognosis ; Retrospective Studies ; Male ; Female ; High-Throughput Nucleotide Sequencing ; Middle Aged ; DNA Methyltransferase 3A ; Adult ; Aged ; Survival Analysis ; Proto-Oncogene Proteins c-kit/genetics*

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Background:Postoperative nutritional status and nutritional support therapy are important driving factor for clinical outcomes in patients after lung transplantation.This study aims to evaluate the relationship between mNUTRIC scores and prognosis in patients after lung transplantation.Methods:A retrospective inclusion of 253 patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from January 2020 to December 2022.The nutritional risk in patients after lung transplantation is much higher than in other critically ill patients.To explore the optimal threshold,patients were divided into three groups based on the tertiles of mNUTRIC scores,and clinical outcomes were compared.The predictive ability of the mNUTRIC score was analyzed using receiver operating characteristic(ROC)curve.The appropriate threshold was determined using the Youden index based on the highest combined sensitivity and specificity.Results:Among 253 patients,the 30-day mortality rate was 14.2%.The death group had higher age and BMI,with APACHE II,SOFA,and mNUTRIC scores all higher than those in the survival group.The median mNUTRIC score in the death group was 5.00(3.00～6.00).The higher the mNUTRIC score,the greater the gradual increase in 30-day mortality rate.When the mNUTRIC score was 4～6,the patient mortality rate was 21.21%,and when 7～9,it was 42.31%.The Q3 group had significantly prolonged mechanical ventilation time,was more prone to delayed weaning,had longer ICU length of stay,and higher tracheotomy rate.Multivariate Cox regression analysis and Kaplan-Meier survival curve showed that mNUTRIC score is an independent risk factor for 30-day mortality,with mortality rate increasing as the score increased(P<0.001).The area under the ROC curve(AUC)for mNUTRIC score was 0.765(95%CI:0.686,0.644).According to the Youden index,the optimal cutoff value is when mNUTRIC score equals 3.5,used to predict high nutritional risk and 30-day mortality in lung transplant patients.Conclusion:The mNUTRIC score has a good predictive effect on the prognosis of patients after lung transplantation and is expected to be applied in clinical practice as a routine assessment tool to help clinicians perform postoperative nutritional risk stratification.

Fe/Mn/Gd polymetallic nanooxide(FMGN)were prepared by one-step solvent thermal reaction by using Fe(acac)3,Mn(acac)2 and Gd(acac)3 as reaction precursors.Next,hyaluronic acid(HA)was used to modify FMGN to fabricate tumor-targeting T 1-T 2 dual-mode magnetic resonance imaging(MRI)contrast agent(HA-FMGN)for accurate diagnosis of prostate cancer.The structure and morphology of FMGN were observed by transmission electron microscope(TEM).It was found that FMGN exhibited a uniform nanocluster spherical structure when the feeding ratio of iron acetylacetonate,manganese acetylacetonate,and gadolinium acetylacetonate was 3:2:1.X-ray diffraction(XRD)analysis showed that FMGN had a typical inverse spinel structure of Mn doped Fe 3O 4,with Gd existing in the form of amorphous gadolinium oxide.The longitudinal relaxivity(r 1)and transverse relaxivity(r 2)of FMGN were 13.395 and 428.535 L/(mmol·s),respectively,measured by 0.5 T MRI analyzer,which proved that FMGN had excellent T 1-T 2 dual-mode MRI contrast capability.The cytotoxicity and hemolysis test found that HA-FMGN didn't damage red cells and induce toxicity for normal cells,indicating that HA-FMGN had excellent cell biocompatibility.The internalization efficacy of HA-FMGN was observed by CLSM,and the results showed that HA-FMGN possessed excellent prostate tumor-targeting ability.In vivo MRI experiment showed that HA-FMGN significantly enhanced T 1 and T 2 weighted MRI signal to noise ratio(SNR)of prostate tumor,which promoted the accurate diagnosis of orthotopic prostate cancer.

Objective To construct the demand model of four types of medical resources including beds in hospi-tal,beds in intensive care unit(ICU),ventilators and medical human resources during the major infectious disease epidemic events,simulate and analyze the treatment of infectious diseases when different medical resources are in short supply.Methods Based on the susceptible-exposed-infectious-recovered(SEIR)model,considering the infec-tivity of infected persons,the susceptibility of the population and the immunity of convalescents,the characteristics of asymptomatic COVID-19 patients and different clinical types,the"COVID-19 infection-hospitalization model"was constructed.By collecting and setting the parameters of disease transmission,clinical course and medical re-source shortage scenarios,an analysis model of allocation and supply of urban medical resources during infectious di-sease epidemic events was initially formed based on Anylogic platform,the supply and demand of medical resources during infectious disease events in different scenarios were analyzed.Results In the non-intervention scenario,the peak time of bed demand was on the 107th day,and the peak value was 160.92 beds per thousand people;the peak time of ventilator demand was on the 122nd day,and the peak value was 5.61 units per thousand people;the peak time of ICU bed demand was on the 117th day,and the peak value was 12.78 beds per thousand people;the peak time of the demand for medical human resources was on the 109th day,and the peak value was 151.12 persons per thousand persons.The simulation results suggested that there were some differences in the impact of different medi-cal resources on the outcome of medical treatment.Conclusion This study constructs an analytical tool for the allo-cation and supply of urban medical resources under the epidemic events of infectious diseases,and the results of mul-tiple simulation experiments suggest that bed resources and medical human resources play more important roles in the outcome of medical treatment.

The anti-inflammatory efficacy of Callicarpa nudiflora extract were evaluated upon lipopolysaccharide (LPS)-induced infective inflammation in rats. Pathological changes of lung and colon tissues observed with hematoxylin-eosin (H&E) staining, together with inflammatory factors in serum, including nitric oxide (NO), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), were applied to assess the mitigating effects of C. nudiflora water extract on model rats. The experimental protocol strictly adhered to the guidelines of the Ethics Committee of Animal Research of Guangdong Pharmaceutical University (Approval: gdpulac2022132). Quality markers with anti-inflammatory activities were recognized by network pharmacology analysis. Subsequently, a reliable method for simultaneously quantifying six components was established. As a result, the pathological injury on lung and colon tissues of model rats induced by LPS were improved by C. nudiflora water extract. Compared with model group, C. nudiflora extract had decreased the release of proinflammatory factors in serum, including TNF-α and IL-6, and reduced the NO (P < 0.01). Network pharmacological analysis obtained 83 chemical components, 466 component targets, 584 disease targets and 129 action targets, which were mainly concentrated in 624 biological processes such as inflammatory response and positive regulation of nitric oxide biosynthesis, as well as 162 pathways such as phosphatidylinositol-3-hydroxykinase-protein kinase (PI3K-Akt) signal pathway and Janus kinase-signal transducer and activator of transcription 3 (JAK-STAT3) signal pathway. Upon analyzing their specificity, effectiveness, detectability, and quantity transfer rule from herb to extract, 6-hydroxyluteolin 7-glucoside, cynaroside, caffeic acid, acteoside, isoacteoside, and forsythoaside B were identified as the quality markers. Their anti-inflammatory activities were verified with LPS-induced inflammation model of RAW264.7 cells. Then contents of these 6 quality markers in 16 batches of C. nudiflora were determined. Thereby, the anti-inflammatory efficacy of C. nudiflora extract were confirmed in vivo, 6-hydroxyluteolin 7-glucoside, cynaroside, caffeic acid, acteoside, isoacteoside, and forsythoaside B were identified as anti-inflammatory ingredients, which can be used as quality control indicators for the herb and related formulation.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.